Pluripotent stem cells-based neural organoids for modelling human brain development and diseases

Lingling Tong; Peiqi Tian; Ruoxi Wang; Shiyun Niu; Ruoming Wang; Yaxuan Ye; Yuxin Wu; Wenjing Zhang; Yueqi Wang; Angelica Foggetti; Di Chen

doi:10.1186/s13578-025-01515-6

. 2025 Dec 24;16:20. doi: 10.1186/s13578-025-01515-6

Pluripotent stem cells-based neural organoids for modelling human brain development and diseases

Lingling Tong ¹, Peiqi Tian ^1,², Ruoxi Wang ^1,², Shiyun Niu ^1,², Ruoming Wang ^1,², Yaxuan Ye ¹, Yuxin Wu ^1,², Wenjing Zhang ¹, Yueqi Wang ¹, Angelica Foggetti ^3,^2,^✉, Di Chen ^1,^2,^4,^5,^6,^7,^✉

PMCID: PMC12917985 PMID: 41444656

Abstract

Brain organoids have emerged as transformative in vitro models for studying human neurodevelopment, neural disorders, and evolutionary brain complexity. This review systematically compares neural development in mice and humans, reflecting the limitations of traditional rodent models and highlights the importance of organoid technology. It synthesizes evolutionary, cellular, and molecular perspectives through comprehensive analysis of literature, detailing the evolution of brain organoid technologies, from early “unguided” whole-brain models to region-specific, vascularized, and assembloid systems that recapitulate inter-regional connectivity. The integration of multi-omics approaches including transcriptomics, epigenomics, and proteomics with organoids has enabled rigorous validation of their fidelity to in vivo development and uncovered novel disease mechanisms. We further explore applications of organoids in modeling cellular dynamics, elucidating gene functions, and replicating neurodevelopmental disorders such as autism, microcephaly, and Rett syndrome. Finally, we discuss their utility in high-throughput drug screening and personalized medicine, while addressing ongoing challenges including vascularization, functional maturation, and ethical considerations. Critically, these advances in organoid technology bridge translational gaps by enabling patient-specific disease modeling, accelerating therapeutic discovery, and providing human-relevant platforms to overcome precision neuroscience. By leveraging mouse and human brain organoids to transcend species limitations in neural research, this review offers unprecedented insights into brain development and pathology.

Introduction

Vertebrate neural development is fundamental‌ to the establishment of the neural circuits that underpin cognition and behavior, while its dysregulation is associated with numerous neurological diseases [1–3]. The past few decades have witnessed remarkable advances in neural development research by using mouse models and, more recently, human neural organoids [4–9]. Nevertheless, translating findings from these experimental models to human neurobiology remains a formidable challenge.

The classic model organism mouse has been the primary system for studying mammalian neurogenesis since the 1960s, owing to its ∼85% genetic similarity to humans and short generation time (19–21 days) [10]. Studies based on mouse models have uncovered fundamental mechanisms governing neural progenitor proliferation, differentiation, and migration [11, 12]. However, significant differences exist between mouse and human neural development. For instance, human neurogenesis extends approximately 15-fold longer than that in mice (approximately 100 days in humans versus 7 days in mice), permitting more refined cell fate determination [13]. Consequently, human neural progenitor populations exhibit greater complexity and diversity, including specific interneuron subtypes absent in mice [14]. To overcome these challenges and better model human-specific neurobiology, this field has increasingly turned to human brain organoids. These systems have emerged as a breakthrough tool for studying human brain development in vitro, offering a powerful alternative where direct human brain research remains ethically and practically constrained [15].

In 2013, the first systematic method for culturing human brain organoids was reported, successfully generating three-dimensional (3D) structures containing multiple brain regions [16]. Subsequently, two main methodological paradigms have become established: the “unguided” approach, which gives rise to whole-brain-like organoids, and “guided” protocols that generate region-specific organoids, such as those resembling the cortex, midbrain, hippocampus, or thalamus [17–19]. Mouse and human neural organoid research have developed in parallel, each offering unique advantages. Mouse organoids develop rapidly and are readily validated against well-characterized in vivo benchmarks, while human organoids provide unique access to human-specific developmental processes. A deeper understanding of these fundamental developmental processes not only enhances basic knowledge but also facilitates the translation of neural organoids into biomedical applications, making them valuable platforms for disease modeling and drug discovery [20–22].

In this review, we systematically summarize the similarities and differences between mouse and human neurogenesis, highlighting the contributions of neural organoids to our understanding of both systems. We outline conserved and species-specific molecular mechanisms, evaluate the capacity of organoids to recapitulate developmental processes, and discuss their applications in neurological disorders.

Neural development in mouse

As one of the earliest model organisms for brain research, mice have provided crucial insights into the fundamental mechanisms of neural development, establishing the basic framework for the understanding of the mammalian brain development.

Embryonic development of neuroectoderm

Mouse embryogenesis begins at fertilization (embryonic day 0, E0). By E3.0, the morula forms, and by E4.0, the blastocyst is established, consisting of an inner cell mass and trophectoderm. Implantation into the uterine wall occurs around E4.5, forming late blastocyst [23, 24]. By E6.5, gastrulation commences, forming the trilaminar germ layers (definitive endoderm, mesoderm, and ectoderm) [25] (Fig. 1A). Following gastrulation, the neuroectoderm, a specialized subset of the ectoderm, undergoes neurulation to form the neural plate [26], shaping the foundational architecture of the central nervous system. The neural plate emerges at E7.0, induced by signals released from the primitive node [27]. Then, the neural plate transforms into the neural groove at E7.5 [28]. Neural fold elevation initiates at the hindbrain cervical boundary (Closure 1), followed by rostral closures (Closures 2 and 3), starting and completing neural tube closure between E8.0 and E10.0, respectively [29] (Fig. 1B). From E9.5 to E11.0, the neural tube starts to differentiate into three primary vesicles: the prosencephalon (forebrain), mesencephalon (midbrain), and rhombencephalon (hindbrain) [30]. From E11.0 to E12.5, these vesicles further divide into five secondary structures: the telencephalon (cerebral hemispheres), diencephalon (thalamus/hypothalamus), mesencephalon, metencephalon (cerebellum/pons), and myelencephalon (medulla oblongata) [31] (Fig. 1C).

Fig. 1 — Neural development in mice and humans. A Early embryonic development in mice (upper) and humans (lower). Schematics are arranged chronologically from left to right, showing progression from the zygote to early embryonic stages. Developmental time points are indicated above each diagram. Key morphological regions and structures are annotated within the embryos. B Neural tube closure in mice and humans. Closure initiation sites are numerically labeled [1–3] in chronological order along the rostral-caudal axis. The right section illustrates schematic views of the neural tube along the rostral-caudal axis (upper) and a longitudinal section (lower), arranged temporally from left to right with corresponding developmental time points indicated below. C Brain vesicle formation in mice and humans. Schematics are arranged chronologically from left to right, showing the progression from the neural tube stage to the three-vesicle and five-vesicle stages of brain development. Developmental time points are indicated below each diagram. E, embryonic day; pcw, postconceptional week

During the formation of forebrain, midbrain, and hindbrain, the neurulation of primary brain vesicles is organized through the coordinated establishment of the anterior-posterior (A-P) and dorsal-ventral (D-V) axes. The establishment of A-P axis is tightly regulated by overlapping gradients of morphogens (Fig. 2A-B), mainly secreted by the primitive node and notochord (Fig. 1B). Among them, the Wingless-Int (Wnt) signaling gradient serves as a key posteriorizing factor. Antagonists such as sine oculis–related homeobox 3 (Six3) and Dickkopf 1 (Dkk1) inhibit Wnt signaling in the anterior region, driving telencephalic formation [32, 33]. The expression of Fibroblast Growth Factor 8 (Fgf8) activated by Wnt signal organizes the midbrain-hindbrain boundary (MHB) region, through inhibiting the expression of the midbrain transcription factor Orthodenticle homeobox 2 (Otx2) and inducing the hindbrain transcription factor Gastrulation brain homeobox 2 (Gbx2) [34]. Segmentation into rhombomeres is controlled by a retinoic acid (RA) gradient produced by the paraxial mesoderm [35]. The cooperation of FGF and RA signals activates nested expression of 13 paralogue of Homeobox (Hox) genes, which define the segmental rhombomere identity (r1–r8) (Fig. 2A). The rhombomere subsequently differentiates into the metencephalon (cerebellum/pons) and myelencephalon (medulla oblongata) [36]. The D-V axis is shaped by opposing gradients of Bone Morphogenetic Proteins (BMPs) from the roof plate and Sonic Hedgehog (SHH) from the floor plate [37]. The D-V morphogen gradient induces the expression of regionalized transcription factors, including Paired box 6/7 (Pax6/Pax7) for dorsal sensory neurons, Pax6 for interneurons, and NK2 homeobox 2 (Nkx2.2) for motor neurons along the D-V axis [38]. Along the D-V axis of the telencephalon, the pallium (dorsal region of telencephalon) develops under Wnt and BMP signaling, generating the neocortex, hippocampus, and olfactory cortex; while the subpallium (ventral region of telencephalon), patterned by Shh from the ventral midline, forms three ganglionic eminences: the medial (MGE), lateral (LGE), and caudal (CGE) [39] (Fig. 2B). Upon the establishment of these fundamental axes and regional patterning, neurogenesis commences to generate the diverse neuronal populations within each brain region.

Neurogenesis

Generation of mouse central nervous system (CNS) initiates from the differentiation of neuroepithelial cells (NECs) in the neural plate (Fig. 2C). From E9.5 to E11.5, NECs in the ventricular surface of the telencephalon differentiate into radial glia cells (RGCs) toward the ventricular zone (VZ) and subventricular zone (SVZ) [40]. RGCs further differentiate into neural intermediate progenitor cells (nIPCs) [41]. During E11.5-E13.5, apical RGCs undergo symmetric self-renewing divisions to expand the progenitor pool. By E13.5, these RGCs switch to asymmetric neurogenic divisions, producing one RGC and one neuron (or nIPC) forming the deep layers [42]. Each RGC gives rise to 8–9 neurons stochastically distributed throughout the different layers in total. The expansion of nIPCs above the VZ predominantly contribute to the extensive production of upper layer pyramidal neurons [43].

The dorsal telencephalon’s six-layered neocortex develops in an “inside-out” fashion: deep-layer neurons (layers VI/V) arise from E11–E13, followed by upper-layer neurons (II–IV) from E14–E17 (Fig. 2C) [40, 44]. Layer I, originating from the marginal zone, begins forming at E10.5–E12.5 [29, 45]. The neocortex broadly contains two functional categories of neurons: projection neurons and interneurons. Projection neurons, the primary excitatory output neurons of the neocortex, originate from dorsolateral telencephalic germinal zones and undergo radial migration to the cortex between E11.5 and E17.5 [46]. Specialized subsets include corticospinal neurons (layer V), which innervate spinal motor neurons via the corticospinal tract, and corticostriatal neurons (predominantly layer V), which integrate cortical inputs into striatal circuits [47]. Interneurons including Parvalbumin-positive (PV+), Somatostatin-positive (SST+), Calretinin-positive (CR+) neurons are primarily GABAergic. They arise from ventral telencephalic progenitors in the ganglionic eminences and distribute broadly across cortical layers [48]. As for specialized neurons, Cajal-Retzius cells, which originate from the cortical hem, secrete reelin to guide cortical lamination [49]. Subplate neurons, which locate in layer Vib (a thin layer between the white matter and layer VI), transiently mediate thalamocortical connectivity [50, 51].

Besides neurons, RGCs also differentiate into oligodendrocyte intermediate progenitors (oIPCs, also called oligodendrocyte precursor cells, OPCs) and astrocyte intermediate progenitors (aIPCs) during late embryogenesis [41]. This process of oligodendrocyte-lineage development is termed oligogenesis. oIPCs arise by E11.5, migrate into the mantle zone (MZ) from E12.5, and mature into myelinating oligodendrocytes by postnatal day 15 (P15). Shh induces Olig2 for lineage commitment, while Wnt maintains oIPC proliferation [52–55]. aIPCs emerge at E16–E18, migrating from the VZ/SVZ to the cortical plate, where they mature at P28 [56] via Notch, BMP, and Interleukin-6 (IL-6) family signaling like Leukemia Inhibitory Factor (LIF) and Ciliary Neurotrophic Factor (CNTF) [53, 57–59] (Fig. 2C). Concurrent with gliogenesis newly generated neurons initiate migration to establish functional circuits.

Neuronal migration

Neural migration overlaps temporally with neurogenesis, peaking between E11.5 and E15.5 as neurons migrate from subcortical regions to the cerebral cortex [29, 31, 60]. Radial migration, essential for forming the six-layered neocortex, involves projection neurons such as pyramidal neurons, Cajal–Retzius cells, and subplate neurons [52, 55]. This process occurs via three modes: [1]somal translocation, which usually happens in early development with short migration distances, is mediated by the neuron itself through the leading process attaching to the pial surface [54]; [2]locomotion, which happens as cortical thickness increases and permits the neurons to travel along the entire cortex thickness through RGC scaffold, relies on end-foot anchorage via adherens junctions (AJs) composed of cadherins/catenins [52]; [3]multipolar migration, which happens while multipolar neurons navigate the intermediate/subventricular zones (IZ/SVZ), rather than advancing directly toward the pial surface, these cells dynamically shift direction and speed [54, 61] (Fig. 3A). Tangential migration, parallel to the ventricular surface, predominates in GABAergic interneurons from GE, which migrate to the cortex, olfactory bulb, and basal ganglia from E12.5, reaching the neocortex by E15.5 and continuing postnatally (P15) [60, 62, 63]. Some glutamatergic neurons (Cajal-Retzius cells, subplate neurons) also undergo tangential migration, aiding cortical circuit assembly [64]. The accurate positioning of neurons via migration sets the stage for the subsequent myelination, synaptogenesis, and circuit maturation required for functional network assembly.

Fig. 3 — Neuronal migration and developmental processes in mice and humans. A Neuronal migration in mice and humans. The left section illustrates radial migration, subdivided into three distinct subtypes: somal translocation, locomotion, and multipolar migration. Gray arrows indicate migration paths. The right section depicts tangential migration, annotated with red arrows showing migration paths. Red boxes highlight final positions of neurons after migration, while dashed gray boxes mark initiation and termination zones of migratory routes. B Developmental processes and their corresponding timeline in mouse (upper) and human (lower) brain. E, embryonic day; pcw, postconceptional week; P, postnatal Day

Neural network maturation

Functional networks, the integrated brain regions enabling information processing, are established through three coordinated maturation processes: myelination of axonal pathways, synaptogenesis between neurons, and activity-dependent circuit refinement (Fig. 3B).

Myelination, driven by oligodendrocytes, arises in three waves: E11.5–12.5 from MGE, E15.5 from LGE, and postnatally from cortex. Myelin basic protein (MBP), which acts as insulator to accelerate impulse conduction and is essential for myelin sheath formation, is detected in the optic tracts by P8 and in the corpus callosum by P15 [65].

Synaptogenesis initiates during migration, extending into adolescence during the first three postnatal weeks. Synaptic density reaches adult levels around P30, but synaptic pruning and refinement continue into adolescence [66]. Early synapses form via N-cadherin and neuroligin/neurexin interactions, initially lacking AMPA receptors (“silent synapses”). Postnatally, activity-dependent AMPA receptor insertion drives maturation, with synaptic density peaking at P14 (cortex) during rapid dendritic growth [67]. Excitatory synapses reach peak levels at early stages, while inhibitory GABAergic connections develop more gradually [68].

Circuit maturation involves synaptic pruning and stabilization, mediated by microglia and astrocytes via phagocytosis and complement signaling. This refinement, peaking postnatally and continuing into adulthood, optimizes network efficiency [69]. This fundamental developmental strategy is highly conserved between mice and humans. Disruptions in these processes are linked to autism and schizophrenia [43]. While the processes of neural development are largely conserved between mice and humans, the unique complexity and disease relevance of the human brain necessitate dedicated study.

Neural development in human

Embryonic development of neuroectoderm

Human embryonic development commences after fertilization (day 0). By 1 pcw (postconceptional week), the zygote progresses through cleavage stages to form a morula. By the end of 1 pcw, the blastocyst is formed and implantation is completed. By the end of 3 pcw, the embryo changes from a two-layer structure to a three-layer structure through gastrulation [52] (Fig. 1A). Following gastrulation, the dorsal ectoderm gives rise to the neuroectoderm through BMP inhibition [70]. This neuroectodermal domain subsequently thickens to form the neural plate at 3 pcw, and the neural tube at 4 pcw [55] (Fig. 1B).The process of brain vesicle formation is highly conserved between humans and mice. By the end of the 4 pcw, the rostral neural tube expands and segments into three primary vesicles: forebrain, midbrain, and hindbrain [55]. At 7 pcw, these vesicles further differentiate into five secondary vesicles (Fig. 1C). During brain vesicle patterning, the A-P and D-V axis specification is regulated by multiple conserved signaling pathways and transcription factors. The primitive node secretes factors including CERBERUS (CER1), DKK1, NOGGIN, and LEFTY1, which inhibit posteriorizing signals including WNT, FGF, BMP, and NODAL to promote the formation of forebrain and midbrain. Antagonism of OTX2 and GBX2 establishes midbrain boundaries, and activation of FGF8 and WNT1 maintains midbrain properties [71]. The HOX gene cluster, activated by WNT, FGF and RA, drives the differentiation of the hindbrain and spinal cord. The dorsal region is characterized by BMP signaling, while ventral region is regulated by SHH [72]. During the establishment of the D-V axis, human neural tube forms the MGE, LGE and CGE structures (Fig. 2A-B). This precise regulation of brain vesicle formation and axis specification lays the essential structural and molecular foundations of neurogenesis.

Neurogenesis

Human neurogenesis spans from 5 pcw to 20 pcw. At the beginning of the neurogenesis, NECs in the VZ are transformed into RGCs, which produce a unique type of neural progenitor cells called the outer radial glial cells (oRGCs) [73] (Fig. 2C). Following gastrulation, RGCs undergo symmetrical division, resulting in a significant expansion in the progenitor pool [52]. From 6 pcw, the pattern of cell division begins to change from symmetric to asymmetric, resulting in the generation of a RGC and an IPC (or neuron) [55]. In early stages, projection neurons that migrate toward the deepest layers are directly generated by RGCs [74], while motor output cone neurons toward layer V are generated by RGCs and IPCs. Superficial neurons toward layer II-IV and human-specific granule neurons toward layer IV are mainly generated by oRGCs. oRGCs constitute an additional outer SVZ (oSVZ) region, which is absent in rodent brains. Before 16.5 pcw, RGCs form a “continuous scaffold stage” with fibers spanning the entire neocortex. From 17 to 24 pcw, RGCs transformed into a “discontinuous scaffold stage”. This type of RGC is called the truncated radial glia cell (tRGC), with one end in the VZ and another in the oSVZ [75]. tRGCs later differentiate into ependymal and astrogenic cells [76]. Similar to mice, human cortex also forms a six-layered ‘inside-out’ structure [52, 78] (Fig. 2C). Cajal-Retzius cells migrate to MZ in layer I, as observed in mice [52]. Interneurons including PV+, SST+, CR + neurons originate from the ventral ganglia and migrate to the cortex to balance network excitability via GABAergic signaling, supporting attention and working memory [77].

RGCs initiate gliogenesis by producing OPCs and aIPCs [55]. Unlike mice, where dorsally derived OPCs prevail, human OPCs originate predominantly from the ventral forebrain, notably the MGE and LGE, during the embryonic period. They continue to be generated postnatally via the SVZ until the age of 2 in neonates [78]. OPCs, which appear at 7 pcw [79], migrate long distances throughout the brain through the vasculature scaffold [78]. After migration, Wnt signaling pathway promotes the proliferation and differentiation of OPCs. Differentiation of astrocytes begins from 6 pcw and continue to mature after birth, mainly regulated by TFG-β signaling pathway [80]. Parallel to gliogenesis, the developing brain also undergoes extensive neuronal migration.

Neuronal migration

Neural migration exhibits substantial temporal overlap with neurogenesis [73]. Compared to mice, human neuronal migration occurs over a longer period, peaking between 13 pcw and 16 pcw. Consistent with murine development, human neural migration proceeds through two principal pathways: radial migration and tangential migration [81, 82] (Fig. 3A). During radial migration, human neurons migrate long distances, with interneurons migrating from the VGE to the cortex or striatum across several millimeters. During tangential migration, inhibitory cortical interneurons travel across the contours of the developing cortical coat [83]. Some populations of glutamatergic neurons, including Cajal-Retzius cells, subplate neurons, and cortical plate transient neurons, are also capable of tangential migration, which play a key role in neural circuits assembly [64]. Following the establishment of neuronal positioning, the foundation is laid for subsequent neural network maturation.

Neural network maturation

Human myelination initiates postnatally and progresses gradually over several years to completion (Fig. 3B). This process is regulated by neuronal activity, microglia and brain-derived neurotrophic factor (BDNF) signaling received by tyrosine receptor kinase B (TrkB) receptors on oligodendrocyte precursor cells (OPCs) [84, 85].

Synaptogenesis commences during late embryonic development and continues through early postnatal stages, experiencing explosive growth following birth and persisting throughout childhood and adolescence [52]. Human-specific synaptic proteins, exemplified by SRGAP2C, promote dendritic spine maturation and prolong the period of heightened plasticity [86]. Neural circuit maturation in human displays pronounced temporal extension compared to other species. This delayed maturation enhances neural adaptability and supports extended learning capacity of the human brain [73]. Therefore, both evolutionary conservation and significant species-specific differences are observed between mice and humans regarding neurogenesis. These similarities and differences are not only key entry points for understanding the core regulatory network of the neurodevelopmental system, but also provide important references for revealing the unique regulatory mechanisms of human neurodevelopment.

Comparison of mouse and human neural development

The core framework of nervous system development exhibits remarkable evolutionary conservation between mice and humans. Both species follow analogous developmental stages. Fundamental brain regionalization and key morphogenetic signaling pathways in neural tube patterning including BMP, WNT/β-catenin, and FGF pathways are conserved. Neuronal migration, myelination, synaptogenesis, and circuit maturation also share conserved regulatory frameworks across species.

On the other hand, there are prominent species-specific divergences during neurodevelopment between mice and humans. At the macroscopic scale, mouse and human brains exhibit different sizes, structure and developmental timing. The mouse brain houses roughly 71 million neurons, while the human brain contains nearly 86 billion neurons [87, 88]. Cell division in the mouse brain is restricted to a small region near the cerebral ventricles [14], while the human brain houses the oSVZ region, which is essential for the formation of cortical folds (Fig. 2C) [89]. In contrast to the sulcusless gyrus of the mouse brain, the human brain gradually develops into a typical mature gyrus and sulcus folding pattern, together with greater brain volume, providing additional space for complex associational areas, is essential for advanced cognitive functions in humans (Fig. 3B). While human neurogenesis begins around 4 pcw and continues to increase in complexity postnatally, the mice undergo rapid neurogenesis, with cortical layers fully formed within days of birth [31, 66], which correlates with cell cycle dynamics. For example, the human neural progenitors, such as RGCs and oRGCs, display a longer mitotic phase, which is linked to proliferative divisions rather than asymmetric neurogenic divisions, while murine progenitors favor rapid, sequential lineage commitment [90]. Besides, human myelination is a prolonged process that extends over several years, whereas in mice, myelination is completed within weeks.

Critical divergences also emerge in the molecular and cellular mechanisms governing these processes. During D-V axis specification, both species utilize BMP and WNT/β-catenin signaling, but human neural plate formation requires prolonged BMP antagonist activity and stronger FGF pathway synergy. Genetic redundancy often differs in the two species. While Noggin deficiency causes severe neural tube closure defects in mice, human embryos exhibit milder phenotypes due to compensatory mechanisms [91]. Paralogs like PAX7 compensate for PAX3 functions in humans, while mice show singular gene dominance [91]. In mice, WNT1 and WNT3a may have overlapping functions, while in humans, WNT3a plays a more dominant role [91].

The disparity between mice and humans also extends to neuronal diversity during forebrain formation. The ratio of excitatory to inhibitory neurons is three times lower in humans than in mice. Intra-telencephalic (IT) neurons are more dominant in human cortex, suggesting a higher proportion of intracortical intercellular communication. For inhibitory neurons, the increased proportion of vasoactive intestinal peptide (VIP) neurons in humans relative to mice suggests a stronger inhibitory effect on inhibitory interneurons, which enhances the activity of excitatory neurons and contributes to advanced sensory processing and learning in humans [92].

Human and mouse neurogenesis also diverges in epigenetic regulation. 499 human-specific chromatin topologically associated domains (TADs) and 1266 human-specific chromatin loops have been discovered in the developing human brains [93]. These loops, enriched for enhancer-enhancer interactions, regulate key genes in subplate (SP) neurons and influence early neural network formation. In contrast, mice lack such structures, with simple SP layer development and a more basic gene regulatory network [93]. Multiple species-specific genes have also been found to cause the diversity between mice and humans. The human-specific gene Rho GTPase-activating protein 11B (ARHGAP11B) promotes massive value-added differentiation of granule cells and the formation of more over-grooved gyrus folds by activating the NOTCH and WNT signaling pathways in human cerebellar development, whereas this gene is absent in mice [94]. BMP6/2, Mothers against decapentaplegic homolog 1 (SMAD1) and Transforming Growth Factor Beta 2 (TGFβ2)-SMAD2 signaling in human brain drives synapse formation in dopaminergic neurons, while these pathways are less robust in mice [95].

There are significant differences in glial-vascular interactions between mice and humans. Compared to mice, human cortical oligodendrocytes and microglia more frequently accumulate in endothelial and mural cells to form perivascular structures (97). Furthermore, a single human astrocyte occupies a volume in the brain that is almost 30 times larger than mice, contacting approximately 2 million synapses [96]. Besides, human-specific accelerated genomic regions (HARs), which do not have direct equivalents in mice, regulate the spatiotemporal expression of gliogenic regulators like SRY-Box Transcription Factor 9 (SOX9) and Oligodendrocyte Transcription Factor 2 (OLIG2), optimizing cortical synaptic pruning and activity-dependent myelin remodeling [97].

These differences necessitate complementary studies in both species, yet ethical constraints limit human embryonic research mostly to in vitro models. Three-dimensional (3D) neural organoid model represents a transformative advance over traditional two-dimensional (2D) culture, offering unprecedented opportunities to investigate human brain development and disease mechanisms in a physiologically relevant context.

Brain organoids in mice

Mouse neural organoids emerge as a critical tool to bridge the gap between traditional in vitro models and in vivo complexity. While conventional 2D cultures and animal studies provide foundational insights into neurodevelopment, they often fail to recapitulate the 3D architecture, multicellular interactions, and dynamic spatiotemporal gradients of the developing brain. By leveraging the genetic tractability and developmental timelines of mice, researchers seek to establish organoid systems that mirror in vivo 3D structure of tissue organization, enabling precise mechanistic studies of neural patterning, cell fate decisions, and disease mechanisms in a controlled and physiologically relevant environment.

The development of mouse neural organoids began with pioneering work in cortical neurogenesis. Eiraku et al. (2008) first demonstrated that mouse embryonic stem cells (mESCs) could self-organize into three dimensional cerebral cortex tissues through quick-aggregation SFEBq (serum-free culture of embryoid body-like aggregates) procedure in 10–14 days [98]. The tissues include four distinct zones, the ventricular, the early and late cortical-plate, and the Cajal-Retzius cell zones. In 2011, Eiraku et al. refined protocols to model optic cup-like development. The optic cup-like structures exhibit apical-basal polarity, with distal invagination forming neural retina and proximal differentiation into pigmented retinal epithelium (RPE) [15]. In 2017, Shiraishi et al. generated mouse thalamic primordium with a rostral-caudal spatial pattern in SFEBq culture [99], while they discovered that mESCs were able to self-differentiate into prethalamus, thalamus and pretectum with basal plate. This finding later inspires the development of human thalamic organoids (hThOs) [20]. In 2022, Park et al. generated mouse neural tube organoids from mESCs in 3D Matrigel [100], which successfully recapitulate the establishment of apical-basal polarity, the expression of neural progenitor cell markers such as SOX1 and PAX6, and the patterning of anterior-posterior axis (Hox1 to Hox9) of the in vivo neural tube. These organoids have also displayed in vivo neural tube-like features, such as apical cilia, interkinetic nuclear migration, and neural tube lumen extension. By day 8-day 10, mature organoids generate multipotent neural crest cells, which differentiated into peripheral neurons, glial cells, and smooth muscle cells. Neural crest cell migration and phagocytosis are observed in real-time in a mammalian model for the first time. However, the organoids lack neural mesodermal progenitors (NMPs), and their axis elongation mechanism differs from that of the embryonic tail bud. Their size is limited by the lack of a vascular system, and long-term culture may lead to hypoxia. In 2023, Ciarpella and colleagues generated mouse hippocampal organoids in 32 days using WNT3a [101]. The organoids develop functional neuronal networks and exhibit region-specific markers for cortical neurons and choroid plexus. However, the hippocampal organoids display limited sizes. They lack vascularization and non-neuronal cell types such as microglia (Fig. 4A; Table 1).

Fig. 4 — Timelines and methods in neural organoids. A Schematic timeline comparing major developmental milestones in mice (upper) and humans (lower) neural organoid technologies. B Illustration depicting various types of mouse and human neural organoids and their generalized generation methods. hPSCs, human pluripotent stem cells; HUVECs, human umbilical vein endothelial cells; MPCs, mesodermal progenitor cells

Table 1.

Protocols of mouse brain organoids

Mouse brain organoids	Culture environment	Neural induction	Differentiation and maturation	References
Cortical Tissue	Orbital shaker	N2, Dkk-1, SB-431,542, FGF8	Wnt3a, DAPT	[98]
Optic Cup	Stationary culture, 40%oxygen	N2, Dkk-1, SB-431,542, FGF8, Nodal protein	IWP2, BIO, Retinoic acid, taurine, DAPT	[15]
Thalamus	Stationary culture	N2, Dkk-1, SB-431,542, gfCDM with insulin, PD0325901, BMP7	Insulin, PD0325901, BMP7, SU5402, CHIR99021	[99]
Neural tube	Stationary culture	CHIR99021, PD0325901, LIF, βFGF, activin A, N2, B27	N2, B27	[100]
Hippocampus	Orbital shaker	βFGF, EGF, WNT3a	BDNF	[101]

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Advantages of mouse neural organoids persist, emphasizing the importance of developing mouse organoids. Their rapid developmental timeline, high reproducibility due to standardized protocols, and compatibility with extensive genetic tools such as CRISPR-edited lines make them indispensable for mechanistic studies and large-scale drug screening. Mouse organoids are also critical in optimizing culture conditions later adapted to human systems. In addition, the lower cost and ethical flexibility further make high-throughput experiments applicable in mouse organoids, but impractical in primate models.

However, mouse neural organoids remain less extensively studied compared to their human counterparts. This discrepancy arises from several interrelated factors. First, in vivo mouse model system has been well-established with its genetic tractability, short gestation period, and conserved mammalian neurodevelopmental mechanisms. This obviates the need for developing complex mouse organoid systems to a large extent. Second, technical challenges, such as achieving vascularization and scaling organoid size to recapitulate tissue complexity, remain unresolved in mouse systems, mirroring limitations seen in human organoids but with fewer dedicated efforts to overcome them. Third, the scientific community’s growing emphasis on human-specific disease modeling and translational applications has shifted resources toward human organoid research, which directly addresses human neurodevelopmental disorders and evolutionary-unique features. This confluence of factors explains the relative underdevelopment of mouse neural organoid models. It is the unique capacity of human neural organoids to model species-specific aspects of the human brain, particularly in development, health, and disease that now commands the forefront of research efforts.

Brain organoids in humans

Currently, research on the human brain is mainly focused on two approaches: animal model including mice and rats and human brain tissues. However, significant differences exist between the animal models and the human brains in aspects of cell types [102, 103], gene expression profiles, neural network connectivity [104] and signal transduction [105, 106]. Consequently, findings from these models are not fully applicable to the human brains. The use of human brain tissues also faces ethical limitations, and the quality of brain tissues obtained from deceased donors is difficult to guarantee. Human pluripotent stem cells (hPSCs), including human embryonic stem cells (hESCs) and human induced pluripotent stem cells (hiPSCs) possess the ability to differentiate into any cell type in the human body under specific culture conditions [107, 108]. Therefore, hPSC-derived organoid model containing multiple cell types represents an excellent and accessible system for modeling human neurogenesis and neural diseases.

The induction of neural differentiation from PSCs to 3D tissues dates back to 1992, when Reynolds et al. first applied the epidermal growth factor (EGF) and/or tumor necrosis factor alpha (TNF-α) to induce pluripotent progenitors dissociated from mice to form 3D-structures containing neurons and astrocytes [109]. However, these aggregates, consisting of several central nervous system cell types, lack cytoarchitectures and are classified as neurospheres rather than brain organoids. In 2001, Zhang et al. successfully induced hESCs to differentiate into neural lineages, generating the rosettes-like structures that recapitulate early steps of brain development and form neural tube-like structures (115). Actually, the pioneering advance of human brain organoid development began in 2008, when Sasai et al. first used the SFEBq culture to establish a primary cortical-like structure generated from neural spheres derived from mESCs and hESCs. These structures include polarized cortical neuroepithelia and functional neurons, enabling recapitulation of early neurogenesis [98]. The SFEBq procedure has subsequently been applied to the derivation of multiple individual brain regions, including retina, cerebral cortex, and pituitary gland [111–113], opening up a new way for the generation of different brain regions. A landmark achievement occurred in 2013 when the first 3D brain organoids model derived from hPSCs was generated successfully [16]. In this method, hPSCs-derived embryoid bodies (EBs) are embedded into Matrigel and cultured in a rotating bioreactor to improve the exchange of gases and tissue expansion. Subsequently, growth factors promoting neurodevelopment are added, minimizing external interference and maximizing self-organization.

These efforts yield sophisticated cerebral organoids containing multiple brain regions, such as the forebrain, midbrain, hindbrain, hippocampus, choroid plexus, and immature retina [114]. Single-cell transcriptome analysis further demonstrates that cerebral organoids contain neuroepithelial progenitors, intermediate progenitor cells, radial glial cells, astrocytes, oligodendrocyte-precursor-like cells, excitatory neurons, inhibitory neurons, and photosensitive cells [115]. Moreover, the genetic programs of cells in organoid cortex-like regions closely resemble the fetal brains [116]. Although unguided methods have reported obvious heterogeneities in morphology, cell types, and spatial distributions across batches [117], supplementing culture media with various external/patterning/nutritional factors to guide the hPSC differentiation towards certain brain regions provides a robust model to improve reproducibility. Moreover, this enables the study of interactions between different brain regions. A variety of organoid models have been developed to simulate distinct regions of the brain, such as the cerebral cortex [17, 18, 118–124], the forebrain [19, 21, 22, 125], the hippocampus [126], the midbrain [22, 127–131], the hindbrain [280–282], the pituitary gland [132], the cerebellum [71, 133], the spinal cord [134–136], the choroid plexus [126, 137], the striatum [138], the thalamus [20], the hypothalamus [22, 139], and the retina [140, 141] (Fig. 4A; Table 2). In summary, significant progress has been made in brain organoid research. Next, we will focus on the achievements in improving the maturity, functionality, and stability of the brain organoids (Fig. 4B).

Table 2.

Protocols of human brain organoids

Human brain organoids	Culture environment	Neural induction	Differentiation/maturation	References
Whole brain	Spinning bioreactor/Orbital shaker	N2, Heparin	N2, B27 without vitamin A, B27 with vitamin A	[16]
Cerebral Cortex	Lumox dish, 40%oxygen, stationary culture	SB431542, IWR1e	Heparin, FBS, B27	[17]
	Stationary culture, without matrigel	Dorsomorphin, SB-431,542, FGF2, EGF, B27 without vitamin A	B27 without vitamin A, BDNF, NT3	[18, 119, 120]
	Stationary culture	SB431542, LDN193189	BDNF, GDNF, GDNF, CNTF	[118]
	Stationary culture	Dorsomorphin, SB-431,542, FGF2, EGF, B27 without vitamin A	Gem21 NeuroPlex, FGF2, BDNF, GDNF, cAMP	[121]
	Microfilament-engineered, orbital shaker	Dorsomorphin, SB-431,542, FGF2, EGF, B27 without vitamin A	B27 without vitamin A, BDNF, NT3	[122]
	Orbital shaker, organoid grafts in mouse brain	N2, Heparin	N2, B27 without vitamin A, B27 with vitamin A	[124]
	Stationary culture	Dorsomorphin, SB-431,542, FGF2, EGF, B27 without vitamin A	Geltrex, BDNF, NT-3, PDGF-AA, IGF-1, 3,3′,5-triiodothronine, Ketoconazole, Clemastine, GSK2656157	[123]
Forebrain	Miniaturized spinning bioreactor (SpinΩ)	Dorsomorphin, A-83, CHIR99021, SB431542	N2, B27, GDNF, bFGF, cAMP	[22]
	Stationary culture, replated aggregates	B27 supplemented with vitamin A, Noggin	FGF2, Noggin, rhDkk1, EGF, N2, B27, BDNF, GDNF, cAMP	[19]
	Stationary culture	SB-431,542, B27 without vitamin A, EGF, FGF2	IWP-2, SAG, retinoic acid, BDNF, NT3	[21]
	Orbital shaker	N2, heparin	IWP2, SAG, CycA, N2, B27 without vitamin A, B27 with vitamin A	[125]
Midbrain	Miniaturized spinning bioreactor (SpinΩ)	SB431542, LDN193189, CHIR99021, SHH, Purmorphamine, FGF-8	TGF-b, cAMP, BDNF, GDNF	[22]
	Orbital shaker	SHH-C25II, FGF8	FGF8, Matrigel, BDNF, GDNF, Ascorbic acid, db-cAMP	[127]
	Stationary culture	SB431542, LDN193189, CHIR99021, SHH, FGF8	cAMP, Ascorbic acid, BDNF, GDNF, TGF-b, FGF20, Trichostatin A, compound E/DAPT	[130]
	Stationary culture	Noggin, SB431542, Dorsomorphin, A83-01, LDN, CHIR99021, IWP2, SAG, FGF8	BDNF, GDNF, Ascorbic acid, cAMP, DA	[128]
	Orbital shaker	CHIR99021, A83-01, LIF, FGF2, EGF	BDNF, GDNF, SHH, Ascorbic acid	[131]
	Orbital shaker	Noggin, B27 supplemented with vitamin A	BDNF, GDNF, Ascorbic acid, cAMP, B27, TGF-b, Purmorphamine	[129]
Hindbrain	Orbital shaker	SB431542, DMH1, CHIR99021, SHH, FGF-4	DAPT, BDNF, GDNF, IGF-I, TGF-β3	[280]
	Orbital shaker	βFGF, Noggin, CHIR99021, SB431542, RA, PMA, SAG	BDNF, GDNF, db-cAMP, Ascorbic acid, SAG, DAPT, TGF-b	[281]
	Stationary culture	Dorsomorphin, SB431542, βFGF, CHIR99021	IWR1, SANT1, BMP4, βFGF	[282]
Cerebellum	Stationary culture	SB431542, FGF2	FGF19, SDF1	[133]
Cerebellum	Orbital shaker	SB431542, Noggin, CHIR, FGF8b	FGF8b, Heparin, AmphoB, T3, BDNF	[71]
Hypothalamus	Miniaturized spinning bioreactor (SpinΩ)	SB431542, LDN193189, WNT3A, SHH, Purmorphamine	FGF2, CNTF	[22]
Hypothalamus	Orbital shaker	LDN193189, A83-01, IWR1, SAG, Purmorphamine, SHH	BDNF, GDNF, cAMP, Ascorbic acid	[139]
Retina	40%oxygen, stationary culture	bFGF, EGF,	bFGF, Retinoic acid, taurine, DAPT	[141]
Retina	Stationary culture	Heparin	B27, PSA	[140]
Choroid plexus	40%oxygen, floating culture	SB431542, IWR1e	condition1: N2 condition2: N2, FBS, CHIR99021, BMP4	[126]
Choroid plexus	Orbital shaker	SB431542, LDN193189, IWP-2	CHIR-99,021, BMP-7, BDNF, GDNF	[137]
Spinal cord	Stationary culture	SB431542, LDN193189, Ascorbic acid, bFGF, CHIR99021, Retinoic acid, SAG	CHIR99021, bFGF, Ascorbic acid, BDNF, GDNF, BMP4, DAPT	[134]
	Stationary culture	SB431542, CHIR99021, bFGF, Retinoic acid	Ascorbic acid	[135]
	Stationary culture	SB431542, LDN193189/FGF2, Retinoic acid, CHIR99021, SAG, DAPT	PD173074, SCH772984, FGF2, Ascorbic acid, IWP2	[136]
Pituitary gland	40%oxygen, stationary culture	SAG, BMP4	FGF2, SAG	[132]
Thalamus	Orbital shaker	SB431542, LDN193189	N2, B27 supplement minus vitamin A, BMP7, PD325901, BDNF, Ascorbic acid	[20]
Hippocampus	Lumox dish, 40% oxygen, stationary culture	SB431542, IWR1e	N2, FBS, CHIR99021, BMP4, B27 without vitamin A	[126]

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Optimization of the culture conditions

The extracellular matrix (ECM) of the brain is a complex network structure, mainly composed of structural proteins, proteoglycans and adhesion proteins. These components provide structural support and guide the activities of both neuronal and non-neuronal cells, which are crucial for brain development. Initially utilizing Matrigel, a natural and complex components of ECM, as the primary material to provide support for organoids [16], researchers have improved the structural integrity and morphological consistency of organoids by adjusting the concentration and composition of Matrigel [17, 142]. The decellularized ECM that retains the key components (including elastin, fibronectin, type I collagen and laminin) also exhibits excellent biocompatibility [143]. Decellularized human-derived brain extracellular matrix (BEM) is used for recreating brain-mimetic niches and promoting neural and glial differentiation, which is deficient in the non-neuronal matrix such as Matrigel [144, 145]. Robin et al. processed decellularized ECM of adult pig brain cells into hydrogel scaffolds for the culture of brain organoids [146]. Concurrently, synthetic hydrogels with controllable mechanical properties and biochemical characteristics have emerged, for example, the gelatin methacrylate (GelMA) is an attractive option for 3D bio-printed neural engineering due to facile fabrication process, inexpensive, and supports neuronal growth [134, 147, 148]. Meanwhile, PEG-based gels could also generate neural organoid tissues [148].

Another significant advancement is the optimization of the culture device. Lancaster et al. first induced whole-brain organoids using a rotating bioreactor [16]. This bulky, large, and infrequently used device has limited the wide application of brain-like organ culture techniques. Scientists have developed a series of alternative solutions. For example, permeable film-based culture plates with 40% oxygen could support the self-formation of multilayered structure including subplate, cortical plate, and Cajal-Retzius cell zones, including three progenitor zones (ventricular, subventricular, and intermediate zones) in a floating culture [17]. Subsequently, a floating stationary culture method was developed, which is more convenient, highly reproducible, and has no extracellular matrix embedding or complex culture environment [119, 142]. However, this method is more inclined to generate only dorsal excitatory neurons. To overcome the heterogeneity of cell differentiation believed in the operation during the culture process, the application of engineering technologies such as bio-printing, and microfluidics in improving the organoid culture system and environment is a new focus. An extrusion-printed iPSC-containing polysaccharide-based bioink is used to construct a 3D structure which differentiated into various mature neurons and glial cells in a neural induction medium [149]. In a bi-directional rocking bar microfluidic system, the brain organoids exhibit the developing of cortical layers, and enhanced electrophysiological functions [145]. Using an octagonal column microcolumn array could achieve an in situ formation and differentiation of hiPSCs to functional brain organoids [150]. In a miniaturized spinning bioreactor (SpinΩ), region-specific brain organoids including forebrain, midbrain, and hypothalamus could be generated, which not only encompass a greater diversity of cell types, but have also been successfully utilized to model Zika virus (ZIKV) infection [22]. Another study utilizes orthogonal WNT/SHH gradients to generate forebrain, midbrain, and hindbrain organoids through the Dual Orthogonal-Morphogen Assisted Patterning System (Duo-MAPS) diffusion device, driving lineage specification based on organoid location in the device [151]. Combining rotating bioreactors with air-liquid interface culture holds the potential to further improve the maturity and functional output of brain organoids, which are capable of generating neurons, astrocytes, and oligodendrocytes, and forming complex neural networks [142].

Co-culture system and vascularized organoids

Brain organoids usually lack non-ectodermal cell types, such as microglia and the vascular system. Meanwhile, cell culture methods often overlook the important cell-cell interactions that regulate the extracellular microenvironment.

Microglia are the main immune cells in the central nervous system (CNS), and play critical roles in neurogenesis, phagocytizing apoptotic cells, regulating axonal growth. The lack of microglia limits the application of organoids in simulating neuroinflammation and immune-related diseases, so microglia-containing organoid method co-culturing hPSC-derived primitive neural progenitor cells and primitive macrophage progenitors could induce appropriate percentage of microglia at proper timepoint, resembling in vivo brain development [152, 153].

Vascularization is extremely necessary for oxygen penetration and neural progenitor differentiation [154], however, brain organoids lack a functional vascular system, which plays a crucial role in neural regulation and brain development, severely limiting the size and maturity of brain organoids. There have been advances in bioengineering oxygen supply to brain-like organs. For example, an organ-on-a-chip technology has mimicked the function of the contractions of blood vessels to deliver oxygen and nutrients [155–157]. In fact, a sliced neocortical organoid (SNO) system also overcomes the limit of diffusion and leads to successfully establishing upper and deep cortical layers with neurons and astrocytes, resembling the third-trimester human neocortex [158]. To establish the vascularized hCOs (vhCOs) by ectopic expression of ETV2 in cultured human cortical organoids (hCOs), coculturing hPSCs with human umbilical vein endothelial cells (HUVECs) or incorporation of mesodermal progenitor cells (MPCs) into organoids could result in a more complex structure and more mature neuronal cells, and even more complexed structure such as the blood-brain barrier (BBB) -like structure [164–166].

However, the complex tissue architecture of the native blood microenvironment is not fully recapitulated in vitro. Thus, transplanting human brain organoids into adult mouse brains enables the generation of functional vascularized organoids that develop in vivo. These organoids contain typical cortical cell types, recapitulate the laminar organization of the neocortex, and exhibit robust vascularization, enhanced survival, and multilineage differentiation [161, 162]. Similar to mice, transplanting the cerebral cortex organoids into the somatosensory cortex of newborn athymic rats, results in various mature cell types integrating into sensory and motivation-related circuits [163], while another study demonstrates feasibility, effectiveness, more neurogenesis, and more cell survival after transplantation into rats [164].

Assembloids system

Compared with the brain-like organs in a single area, fused organoids or ‘assembloid’ systems provide a path to investigate inter-brain-region and inter-organ crosstalk, which overcome the limitations of the random arrangement of regional identities, better simulating human brain development, neuron migration, and established functional circuits.

The first assembloid system was generated by dorsal forebrain and ventral forebrain organoids, generating dorsal-ventral axis, demonstrating a migration of CXCR4-dependent GABAergic interneuron from ventral to dorsal forebrain [125]. Fusing the MGE organoids and cortical organoids as a new system to model human MGE enables the analysis of interneuron migration and integration in humans [165]. Then various fusing different types of brain organoids have been merged, such as the pallium (human cortical spheroids, hCSs) or the subpallium (human subpallium spheroids, hSSs), to simulate functional integration into microcircuits. It is the first time that the saltatory migration of interneurons developed towards the cerebral cortex [21]. By fusing the thalamic organoids (hThOs) and the cortical organoids, researchers create the reciprocal projections and model the circuit organizations between the thalamus and cortex [20]. Other cortico-motor assemblies, resembling the cerebral cortex or hindbrain/spinal cord and skeletal muscle spheroids, formed functional motor circuits in human brain [166]. Assembling the human cortical spheroids (hCSs) and the human striatal spheroids (hStrSs) [138] to form cortico-striatal circuits of the forebrain reveals long-range neuronal connections in the human brains. Recently, the Multi-Region Brain Organoids (MRBOs) platform represents a significant advancement in vascularized assembloid technology by integrating cerebral, midbrain, and hindbrain organoid with a complex vascular component. It demonstrates remarkable molecular similarity to the human fetal brain (Carnegie stages 12–16), providing a robust platform for studying inter-regional interactions within a 3D brain microenvironment [167]. In the future, more improvements of assembloids, including integrating more brain regions and introducing vascular support culture or increasing microenvironment regulation, may make them powerful tools for studying brain diseases and developing new therapies.

The remarkable advancements in human brain organoids have fundamentally transformed their potential as models of the developing and diseased human brain. However, unlocking the full power of these increasingly complex in vitro systems requires a deeper understanding of their molecular composition, cellular heterogeneity, and functional states. This is where multi-omics technologies become indispensable. By providing comprehensive, high-resolution molecular profiles, omics approaches offer the critical lens needed to validate organoid fidelity, dissect developmental mechanisms, identify disease signatures, and ultimately bridge the gap between organoid structure and function.

Application of genomics in neural organoids

Neural organoids have revolutionized developmental biology by recapitulating tissue architecture and functions in vitro. Multi-omics technologies are indispensable for systematically deconvoluting their molecular landscapes, validating biological fidelity, and uncovering mechanistic insights inaccessible through conventional models (Fig. 5).

Fig. 5 — Overview of multi-omics technologies applied in mouse and human brain and neural organoid models. The panels describe four key focus areas across major omics fields, including transcriptomics, proteomics, metabolomics, and epigenomics. Each section highlights the molecular features studied within these disciplines. RNA-seq, RNA-sequencing; scRNA-seq, single cell RNA-sequencing; m⁶A, N⁶-adenosine

Omics in mouse brains, mouse brain organoids and chimeric models

Multi-omics profiling of the endogenous mouse brain is well-established, while applications in mouse neural organoids and chimeric models remain limited—primarily focusing on transcriptomics and constrained by limited human biological relevance.

Transcriptomic studies in mouse brains widely employ RNA-sequencing (RNA-seq) and single-cell RNA sequencing (scRNA-seq). Early RNA-seq-based research identified the critical regulatory roles of long non-coding RNAs (lncRNAs) in mouse survival and brain development [168]. Breakthroughs in single-cell resolution technologies have enabled scRNA-seq to resolve cellular heterogeneity in the adult mouse brain [169–173], uncovering developmental diversity [172], lineage differentiation patterns [170], and clonal dynamics [171]. Spatial transcriptomic techniques have further facilitated the construction of molecular atlases, delineating region-specific transcriptional signatures and cellular distributions, as well as intercellular communication networks when integrated with single-cell data [171]. Besides transcriptomics, the N⁶-adenosine methylation-sequecncing (m⁶A-seq) technology has uncovered brain tissue-specific m⁶A/ N⁶, 2’-O-dimethyladenosine (m⁶Am) modification patterns and their associations with modifying enzymes [174]. In addition, transposase-accessible Chromatin-sequencing (snATAC-seq) atlases of the adult mouse brain map gene regulatory elements by assessing single-cell chromatin accessibility, revealing gene regulatory networks and their connection to neurological disease risk variants [175, 176]. Despite these advances in mouse brain, translating omics approaches to mouse neural organoid models faces significant biological and technical limitations.

To bypass challenges in modeling human biology, researchers shifted to transplanting human brain organoids into mice. Only RNA-seq has been employed to investigate the progressive gene expression patterns, along with reproducibility and robustness [177]. To overcome limitations in obtaining stable human neural cells and maintaining in vitro gene expression/phenotypic fidelity, transplanting human brain organoids into mice to create chimeric models has become an important strategy for simulating human in vivo microenvironments [178, 179]. Current omics applications in these models mainly utilize RNA-seq and scRNA-seq, focusing on transcriptome-level analyses to compare disease-risk gene expression between chimeric models and primary cells, as well as investigating disease pathogenesis drivers [180]. However, these chimeric systems exhibit inherent constraints, including persistent transcriptional differences from primary human cells, impaired expression of human-specific genes patterning cytokines and chemokines, and microenvironmental limitations from murine host biology. These shortcomings underscore the critical need for human-centric model systems that more faithfully replicate species-specific microenvironments.

Omics in human brain and brain organoids

Human brain omics comprises well-established transcriptomic, epigenomic, proteomic, and metabolomic profiling, while neural organoids serve as complementary emerging models with growing multi-omics integration, particularly for developmental and disease contexts.

Transcriptomics methods have progressively advanced to single-cell resolution, enabling comprehensive cellular characterization in human brain and organoid models. The first application for bulk RNA-seq appeared in 2008, when Mudge et al. [181] generated 16.7 billion bases of shotgun cDNA sequences from cerebellar cortex samples from schizophrenia patients and controls. From this, 215 DEGs are discovered, which enriched for GO terms of various crucial neuronal processes, such as transport from the trans-Golgi network to the synaptic vesicle and synaptic vesicle exocytosis. Given the prevalence of alternative splicing (AS) in human brain, early transcriptome analysis prioritized its developmental roles [182, 183]. For example, Johnson et al. in 2009 applied whole-genome exon microarrays to delineate global AS patterns in mid-gestation human brain [184]. Subsequent work by Chen et al. (2011) revealed isoform distribution divergence of 270 commonly expressed genes between brain tissue and cell lines, primarily attributable to AS regulation [185].

Later, the scRNA-seq technology has allowed researchers to decipher the cellular transcriptomic compositions. The pioneering attempts of scRNA-seq for human brain tissues are performed on 430 cells from five primary glioblastomas [186] and 301 cells derived from the normal cerebral cortex [187], respectively, uncovering cellular heterogeneity in diseased and developing brains. Later, improved technology of scRNA-seq is applied to study cell diversity [103, 188–190], developmental trajectories [191, 192], and underlying pathologies [193, 194] in brains. The scRNA-seq is also employed to validate the reliability of brain organoids, including ventral forebrain [21, 165], thalamocortical [20], pituitary gland [195], brainstem [196], and midbrain [197] at single-cell resolution. Integrated scRNA-seq atlases from different datasets demonstrate high reproducibility of neural organoid cell diversity and developmental trajectories across hiPSC lines and protocols. Projects combining scRNA-seq data from different induction protocols and differentiation experiments establish foundational resources for neural organoid research, validating transcriptional consistency despite experimental variations [7, 115, 198–200]. Beyond transcriptional profiling, epigenetic mechanisms such as DNA methylation and chromatin accessibility provide an additional layer of regulatory insight into neural development and disease.

As a fundamental epigenetic mechanism, DNA methylation dynamics have been extensively mapped across neurodevelopment and disease contexts. Early studies have investigated the role of DNA methylation in certain stages or diseases, such as the investigation of methylation on O⁶-methylguanine-DNA methyltransferase gene (MGMT) by Everhard et al. and Kreth et al., through pyrosequencing method in 2009 [201], and methylation-specific PCR (MSP) with bisulfite modification in 2011 [202], respectively. These studies demonstrated the partial inconsistency between DNA methylation and gene expression in glioblastomas (GBM) tissue, identifying CpG regions significantly correlating with MGMT expression.

Building upon prior knowledge and technological advances [203, 204], DNA methylation in the brain has been investigated more comprehensively, particularly in the contexts of hippocampal development and aging [205, 206], thereby providing critical insights into gene regulatory dynamics in neural tissues. Pioneering research is completed by combining DNA modification and 3D chromatin structure analysis for multi-region human brain cells [207], which reveals the co-regulation mechanisms of DNA methylation and chromatin dynamics, and develops a potential tool for cell identification called single-cell methylation barcodes (scMCodes). In 2024, Treble-Barna et al. generalized hundreds of studies on brain-derived neurotrophic factor (BDNF) DNA methylation, and developed a BDNF DNA methylation map with database, thoroughly summarized methylation CpG positions [208]. Complementing DNA modifications, chromatin accessibility profiling has unveiled spatiotemporal regulatory architectures across brain regions and development.

Multiple studies utilize Assay for Transposase Accessible Chromatin with high-throughput sequencing (ATAC-seq) to investigate gene regulatory networks of human endogenous brains [209–212]. Chromatin accessibility atlas of neurotypical brains has been established using ATAC-seq among 14 brain regions [209] and single-cell ATAC-sequencing (scATAC-seq) of 42 brain regions [213] and 25 brain regions [214]. For brain development, the integrative analysis of scRNA-seq and scATAC-seq data is conducted for human prefrontal cortex (PFC) from 22 gestational weeks to 40 years [211] as well as cortex from 18 gestational weeks to 39 years [215], revealing the gene regulatory dynamics of developing and aging brains. For neurological diseases, ATAC-seq has identified gene-regulatory alterations in late-stage Alzheimer’s disease (AD) [212] and schizophrenia-associated non-coding therapeutic targets [216].

The integrated analysis of (sc)ATAC-seq and (sc)RNA-seq data reveals the chromatin dynamic state in the development of cortex organoid [165], forebrain organoids [217, 218], ganglionic eminence (MGE) organoids [165], and dorsolateral prefrontal cortex (PFC) [218, 219]. It is noticeable that hypothesized novel transcription factors for neural development and corresponding active cis-regulatory elements are identified through integration of bulk ATAC-seq and scRNA-seq of hundreds of cells from fibroblasts to NPCs (post-15 days) [220]. Furthermore, scATAC-seq and scRNA-seq data of neural organoids at the scale of 10⁴ cells over 6 months [221] and from 4 days to 2 months [222] have constructed more systematic epigenetic landscapes of neurodevelopment.

Histone modifications provide critical insights into regulatory element activity, exhibiting distinct profiles in development and disease. The Chromatin Immunoprecipitation sequencing (ChIP-seq) for histone modifications reveals the dynamic state of gene regulatory elements [223]. For example, ChIP-seq profiling of H3K4me3 and H3K27ac is combined with ATAC-seq to infer the activity of genes in neurons and glia from post-mortem brain samples, promoting comprehension of neurodegeneration [224].

In neural organoids, the H3K27ac peaks in neural progenitor cell (NPC) organoid exhibit significant enrichment of GWAS-identified SNPs associated with AD and bipolar disorder (BD) [225], while enhancers inferred from histone modifications in organoids and fetal brains display enriched autism spectrum disorder (ASD)-associated de novo mutations [226], suggesting that neural organoids provide a model for studying the role of genetic changes during neurodevelopment in neurological diseases. For neurodevelopment, the transcriptional factors that drive ESCs to NPCs are identified by integrative analysis of RNA-seq, ATAC-seq and CHIP-seq (235). When examined over larger time scales of neural development, the integrative analyses of genomic profiling techniques (ChIP-seq, DNase-seq, ATAC-seq) demonstrate consistent enrichment patterns of neural organoids only with early developmental stages [217]. Thus, a reliable epigenetic atlas for brain organoids at 6 stages from days 5 to 120 is constructed by single-cell cleavage under targets and tagmentation (scCUT&Tag) for histone modifications, also with scATAC-seq and scRNA-seq (236).

Apart from DNA modification and chromosomal dynamics, RNA modification is another crucial part of epigenetic studies. m⁶A, the most prevalent RNA modification, dynamically regulates gene expression through interactions between methyltransferases, demethylases, and reader proteins. A key example is FTO, an m⁶A eraser whose deficiency elevates global m⁶A levels and disrupts gene regulation in hippocampus, highlighting its critical role in neurodevelopment [229–231]. Du et al. in 2021 identified different m⁶A clusters for AD, vascular dementia (VD), and Mild cognitive impairment (MCI), and further predicted associations between m⁶A and cognitive dysfunctions [232]. Castro-Hernández et al. in 2023 also conducted internal relationship between m⁶A and AD, revealing impact of m⁶A decrease on aging and cognitive decline [233]. Collectively, these epigenetic investigations including DNA methylation, chromatin accessibility, histone modifications, and RNA methylation, provide a multi-layered regulatory framework essential for understanding neurodevelopment and disease mechanisms.

Compared with transcriptomics, proteomics and metabolomics developed earlier in the analysis of human brain tissue, with the focus of unraveling neuronal disease mechanisms. The first neuronal analysis by proteomics took place in 1999, when Edgar et al. discovered the protein DBI, a monomeric protein binding to GABAa receptor and down-regulating GABA action, whose differentially expression indicates the ability for hippocampal molecular events to reflect these diseases [234]. In 2020, Johnson et al. performed quantitative mass spectrometry (MS)-based large-scale proteomics analysis on more than 2000 human dorsolateral prefrontal cortex tissues, to generate an AD brain protein co-expression network atlas consisting of 13 modules, which explicit responses towards aging and multiple neurodegenerative diseases [235]. Multi-omics analysis was also applied. According to the large-scale analysis by Johnson et al. in 2022, half of protein modules are unique in AD protein co-expression network, through the comparison between proteome and transcriptome network [236].

Early metabolomic studies of the human brain primarily utilized cerebral-spinal fluid (CSF) or blood plasma as sample sources, aiming to identify diagnostic biomarkers in living patients. However, in 2012, Graham et al. innovatively employed high resolution liquid chromatography-quadrupole time-of-flight-mass spectrometry (UPLC-QTof-MS) to study polar metabolome of post-mortem human brain tissues from AD patients, through which they developed two metabolomic models with abilities to unambiguously distinguish AD samples [237]. Apart from revealing disease patterns, metabolomics offers unparalleled capabilities in deciphering the intrinsic metabolic dynamics of the human brain. Furthermore, Wang et al. in 2025 globally characterized lipid metabolism of the human brain by non-targeted metabolomic analysis on brain arteriovenous blood samples, as well as quantifying hundreds of metabolites absorbed and produced by brain [238].

Proteomics and metabolomics have gradually been integrated into human brain organoid research. The pioneering application of proteomics in brain-derived cells occurred in 2017, when Dezonne et al. demonstrated a high global similarity between hESC-derived astrocytes and human astrocytes [239]. Subsequent research based on real organoids focused on using proteomics to verify crucial regulating factor during human brain development, such as exploring the effect of Lissencephaly-1 (LIS1) on ECM dynamics and tissue stiffness [240], and being involved in multi-omics analysis which uncovers molecular atlas during the formation of early human brain organoid [241]. In 2018, Pamies et al. combined single-cell transcriptomics with metabolomics to delineate the toxic effects of rotenone on a 3D brain organoid model BrainSpheres, which revealed significant metabolic profile differences between differentiation phases and administration situations [242]. This analysis further identified dysregulated metabolic pathways following rotenone exposure, providing mechanistic insights into neurotoxicological impacts.

The deep molecular insights gained from omics profiling have solidified human brain organoids as credible models of the human brain. Leveraging this validated platform, researchers are actively exploring their utility in key translational applications.

The applications of brain organoids

Brain organoids recapitulate key aspects of human brain development and function, allowing direct observation of dynamic cellular processes, such as neural network formation and signaling pathways in vitro [243]. By introducing disease-associated genetic mutations, organoids reveal pathogenic mechanisms and dysregulated gene regulatory networks underlying specific disorders. For example, organoids have been used to model Zika virus-induced microcephaly [244], a neurodevelopmental defect, as well as mechanisms implicated in Parkinson’s disease [245], offering valuable insights into disease initiation and progression. Furthermore, brain organoids support high-throughput drug screening, providing a human-relevant system for assessing compound efficacy and toxicity [246, 247], thereby reducing reliance on animal models. Their multifaceted utility effectively bridges the gap between basic molecular research and clinical translation (Fig. 6).

Fig. 6 — Schematic illustration of brain organoid application. The panels illustrate four key applications of brain organoids: revealing cellular developmental processes, investigating gene function, constructing disease models, and facilitating drug screening. These panels demonstrate the utility of brain organoids for studying neural development, genetic mechanisms, disease phenotypes, and therapeutic discovery

Cellular process

Neural organoids provide a powerful platform for the examination of cellular processes during neurodevelopment. A key advantage is their ability to model neural cell diversity. Under specific inductive conditions, organoids give rise to a wide range of cell types [243]. For example, with the regulation of FGF2, hESCs develop into neural tube-like structures, which subsequently generate neurons and astrocytes [110]. Beyond general neurogenesis, region-specific protocols enable the generation of distinct neuronal subtypes. Inhibition of WNT and SMAD pathways promotes the differentiation of glutamatergic neurons across all cortical layers, closely mirroring in vivo development [21]. Similarly, SHH-patterned ventral forebrain organoids produce GABAergic interneurons capable of migrating into cortical organoids, recapitulating endogenous interneuron migration pathways [21]. Furthermore, midbrain-like organoids, induced by SHH and FGF8, generate functional dopaminergic neurons, offering a highly relevant model for Parkinson’s disease [127]. Beyond generating individual cell types, a pivotal cellular process modeled by organoids is the self-organization of these cells into intricate, human-specific anatomical structures. A notable example is their ability to generate oRGCs, a cell type absence in mice but critical for human cortical expansion and folding [14, 89]. This capability enables more physiologically relevant disease modeling. For example, researchers have used patient-derived iPSCs to model microcephaly, overcoming the limitations of mouse models that completely lack the oSVZ [16]. The emergence of these complex structures is not stochastic but is directed by precise extrinsic signaling cues, which are systematically decoded using organoid models.

Recent advances in sliced cortical organoid cultures have elucidated how extrinsic signals guide cortical development. In these systems, WNT signaling regulates the neurogenic capacity of subplate neurons, particularly in generating deep-layer cortical projection neurons. Mirroring in vivo human cortex, sliced organoids reveal abundant WNT7A expression in deep-layer neurons positive for TBR1 and CTIP2 [145]. Functional experiments demonstrate that WNT inhibition increases upper-layer SATB2 + neurons, whereas WNT activation expands deep-layer TBR1 + populations [145]. These findings suggest WNT pathway activity helps orchestrate cortical layer identity, highlighting the value of organoids in dissecting developmental signaling mechanisms. Further comparative studies with animal models will be essential to validate the conservation of these mechanisms across species. Additionally, given the well-established role of WNT signaling in neural tube patterning [248], WNT inhibitors have been strategically applied to improve rostral brain identity in organoid differentiation protocols [249].

Beyond modeling cell-intrinsic properties, organoids also facilitate the investigation of complex cell interaction networks [250], including neuron-glia communication and long-range circuit formation. Through directed fusion techniques, researchers have successfully constructed thalamocortical and corticostriatal assembloids that recapitulate the organization of sensory, motor, and cognitive pathways [251]. These multi-regional assemblies exhibit functional neural projection and synaptic activity, as confirmed by electrophysiological analyses, offering a novel platform for probing the development, functionality, and pathology of human-specific neural networks.

Having established that organoids recapitulate human-specific cellular architecture and disease phenotypes, the next pivotal step is to decipher the genetic programs governing these processes. The integration of targeted genome editing into 3D human neural organoids now enables the establishment of direct causal links between genotype and developmental phenotype.

Gene function

3D human neural organoids offer a promising alternative for studying gene functions, as they recapitulate key aspects of human neural development and pathology (Table 3). The application of isogenic mutant organoid models has significantly advanced our understanding of how individual genes regulate neurodevelopmental processes. For example, organoids carrying heterozygous mutations in AT-rich interaction domain 1B (ARID1B) revealed impaired formation of long-range axonal projections, providing mechanistic insight into the etiology of adrenocortical carcinoma (ACC) in ARID1B patients [252].

Table 3.

Summary of gene function in brain development revealed through brain organoids

Genes	Cell lines and organoids types	Findings
LHX6	LHX6 knockout hPSC line and LHX6 overexpression hPSC line induced forebrain organoids	LHX6 knockout suppresses human GIs migration, while GIs migration is promoted by LHX6 overexpression [280]
SOX10	Sox10-MCS5::eGFP induced hOLS	Sox10-MCS5::eGFP reporter reveals the maturation of oligodendrocytes, tracing the oligodendrocyte–neuron interaction and myelination in hOLS [255]
ARID1B	ARID1B heterozygous mutation iPSC line induced neural organoids	ARID1B mutation impairs the formation of long-range axonal projections, causing structural underconnectivity [254]
MAPT	MAPT mutant hPSC line induced cortical organoids	MAPT mutations cause early metabolic changes in cortical glutamatergic neurons, characterized by increased glycolysis, oxidative phosphorylation, and proteasome activity, and decreased sphingolipid and ceramide pathways [281]
DISC1	DISC1 mutant hiPSC line induced cerebral organoids	DISC1-disruption displays smaller, disorganized rosette structures [282]
SHANK3	PSCl-derived single neural rosettes induced SHANK3-deficient orgaoids	Cellular and electrophysiological deficits in SHANK3-deficiency depend on SHANK3 expression level. SHANK3 deletion disrupts clustered protocadherin expression [283]
CNTNAP2	CNTNAP2 knockout iPSC line induced cerebral organoid	CNTNAP2 knockout leads to ventricular zone disorganization and disruptions in glutamatergic/GABAergic synaptic pathways and neurodevelopment [268]
Olig2	Olig2-GFP knockin hPSC reporter line induced dorsal forebrain organoids and ventral forebrain organoids	Olig2 knockin leads to more neuronal differentiation from Olig2⁺ cells and the formation of glutamatergic synapses [284]
NEUROG2	NEUROG2-mCherry knockin hESC line induced cortical organoids	NEUROG2 induces ectopic expression of COL1A1, COL3A1 and PPP1R17 regulatory elements [285]
PTCH1	PTCH1 mutant hiPSC line induced cerebellar organoids	PTCH1 mutation causes loss of function [LOF]. Homozygous PTCH1 LOF inhibits cerebellar differentiation of iPSCs, while heterozygous PTCH1 LOF promotes proliferation and expansion of the glutamatergic lineage [286]
ARHGAP11B	ARHGAP11B interference in human cerebral organoids	Interfering with ARHGAP11B function reduces basal progenitor cells and decreases the abundance of basal radial glial cells [287]
NOTCH2NL	Cortical organoids of hESC origin with NOTCH2NL gene deletion	NOTCH2NL ectopic expression delays differentiation of neuronal progenitors, while deletion accelerates differentiation into cortical neurons [288]
GSK3	GSK3 activity inhibitIon hPSC line induced cortical brain organoids	GSK3 inhibition increases the proliferation of neural progenitors and causes massive derangement of cortical tissue architecture [289]
GLI3	GLI3 knockout hiPSC lines induced brain organoids	CLI3 knockout leads to disruption of dorsal telencephalic regulatory network and down-regulation of key genes in ventral telencephalic identity, such as HES4, HES5, and PAX6 [223]
circFAT3	circFAT3 knockdown hESC line induced cerebral organoids	circFAT3-knockdown leads to a reduction or loss of telencephalic radial glial cells and mature cortical neurons and an increase in non-telencephalic NPCs and astrocyte-like cells [290]
HARE5	HARE5 mutant NPC line induced cortical organoids	HARE5 variant increases enhancer activity that promotes progenitor proliferation. Hs-HARE5 increases progenitor proliferation by amplifying canonical WNT signaling [291]
FMR1	Fragile X hiPSC cell line induced organoids	FMRP loss causes reduced neural progenitors, abnormal neuronal differentiation, and neuronal hyperexcitability [292]

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hPSC, human pluripotent stem cell; GIs, GABAergic interneurons; hOLs, human oligodendrocyte spheroids; iPSC, induced pluripotent stem cell; hiPSC, human induced pluripotent stem cell

While such single-gene studies highlight the utility of organoids, they also underscore a broader challenge: the need to systematically investigate entire gene families and functional networks. For example, although the SOX transcription factor family is critically important in neural development, only SOX10 has been extensively studied in human neural organoids to date [253]. This indicates that comprehensive exploration of gene families in organoids remains an ongoing and substantial effort. Moreover, genes such as TBR1 are well studied in mouse models but still not investigated in human organoids [254]. Identifying these understudied regulators thus sets the stage for the next wave of organoid experiments designed in human organoids.

In summary, these findings underscore the potential of organoid models to elucidate key signaling pathways and transcriptional regulators governing human neural development. By providing a human-relevant context to study how perturbations in these mechanisms contribute to pathogenesis, these organoids also offer a powerful and complementary approach for modelling neurological disorders.

Disease modeling

The complexity of human brain disorders has long challenged traditional model systems. While animal models offer insights into conserved pathways, species-specific differences in neurodevelopment and gene regulation limit their translational relevance. Human neural organoids, which self-organize into brain-region-specific structures, now enable the study of patient-specific mutations in a near-physiological context. In this case, neural organoids have become an important tool for the study of human neural and psychiatric diseases, by simulating the brain development process in vitro. We summarize the mechanism, gene function and potential therapeutic targets of diseases based on integrate data from over 45 studies (Table 4). We notice that some neural developmental diseases have an overlap of partial etiology. For example, the mutation of the same gene PTEN could lead to ASD and microcephaly, although they belong to different disease entities [255, 256]. Microcephaly may be comorbidities or complications of some ASD cases but is not necessarily associated [257]. Recognizing how one gene resides at the crossroads of multiple disorders naturally raises another question that different gene mutations could affect and lead to a same neural disorder. For example, comparison of different mutations in neural developmental disorders reveals that mutations in PTEN [256], CHD8 [258, 259], or MECP2 [260] could disrupt the synchronized neuron maturation, suggesting that there might be a common axis for regulating this process. Pinpointing such a convergent pathway not only deepens our mechanistic understanding but also shifts the spotlight toward therapeutic strategies that could correct this shared defect. In recent years, neural organoids have also emerged as powerful and rapidly adopted tools for the studies of infectious diseases, particularly in uncovering the mechanisms governing SARS-CoV-2 invasion of the central nervous system. Multiple research teams have used human brain organoids to demonstrate that SARS-CoV-2 can directly infect neural progenitor cells and mature neurons, triggering cytotoxicity, metabolic reprogramming, and impaired synaptic function. These findings provide critical experimental evidence that helps explain the neuropsychological complications associated with COVID-19 [261, 262]. Moreover, organoids enable rapid testing of candidate’s drugs, and some screenings have already demonstrated efficacy, for example, pifithrin-α for Rett syndrome [263] and IGF-1 for ASD [264]. Nonetheless, current organoid models face limitations, including the absence of vascularization and insufficient glial cell populations [265], highlighting the need for more advanced and long-term culture systems. Overall, as more and more patient-derived organoids have been modeled successfully and provided remarkable discoveries, they also begin to deliver clinically actionable drug which leads the shifts from biological discovery to scalable implementation.

Table 4.

Summary of brain organoid applications for disease modelling

Disease Category	Gene	Cell lines	Findings
	Autism spectrum disorders (ASD)
Neurodevelopmental disorders	16p11.2 Copy Number Variant	16p11.2 deletions (DEL) and duplications (DUP) patient-derived iPSC lines	16p11.2 DEL cortical organoids are larger with accelerated neuronal maturation, while DUP organoids are smaller. Both exhibit impaired neuronal migration, reduced migration distance, fewer migrating neurons, and elevated active RhoA levels [293]
	FOXG1	4 severe idiopathic ASD patient-derived iPSC lines	FOXG1 overexpression accelerates cell cycle and overproduction of inhibitory neurons [19]
	–	13 idiopathic ASD patient-derived iPSC lines	ASD pathogenesis in macrocephalic vs. normocephalic probands exhibits opposite disruptions in excitatory neurons and dorsal cortical plate balance [294]
	PTEN	Mito210 PTEN edited line, PGP1 PTEN mutant line	PTEN heterozygous mutations cause unusual developmental timing in oRGs and deep-layer neurons, and alters circuit activity [258]
	CNTNAP2	Patient-derived iPSC line with a homozygous protein-truncating mutation in CNTNAP2	CNTNAP2 mutation increases abnormal neural progenitor proliferation, volume and total cell number [295]
	CHD8	hESC CHD8 mutant lines, CHD8 gene mutation inserted in 4 iPSC lines	CHD8 haploinsufficiency leads to accelerated inhibitory neurons, delayed excitatory neurons, improve proliferation and macrocephaly [261];
			Mutation of CHD8 confers asynchronous development of GABAergic neurons and deep-layer excitatory projection neuron [260]
	ARID1B	1 hESC and 2 patient-derived ARID1B mutant iPSC lines; ARID1B mutant iPSC lines	ARID1B loss promotes ventral radial glia expansion and accelerates OPC transition, while inducing asynchronous development between GABA neuromeric and deep-layer excitatory projection neurons [260, 296]
	SHANK3	SHANK3-deficient human pluripotent stem cell lines	Hemizygous SHANK3 deletion leads to defective intrinsic and excitatory synapses and impaired protocadherin cluster expression [283]
	SYNGAP1	1 SYNGAP1 haplo-insufficient patient-derived iPSC line, 2 wildtype (03231) SYNGAP1 mutant lines; 1 SYNGAP1 haploinsufficiency cell line	SYNGAP1 haploinsufficiency dysregulates cytoskeletal dynamics, reduces progenitor cell division, disrupts cortical lamination, and accelerates projection neuron maturation, causing an imbalance in the cortical progenitor-to-neuron ratio [297, 298]
	Microcephaly
	CDK5RAP2	CDK5RAP2 mutations patient-derived iPSC line	CDK5RAP2 loss leads to early neural differentiation at the expense of progenitors [16]
	WDR62	WDR62-deficient hPSC line	WDR62 deletion retards cilium disassembly, long cilium, delays cell cycle progression, furtherly decreases proliferation and premature differentiation of NPCs and oRGs, reduces organoid size (306)
	PTEN	hESC line with different PTEN dosage	Mild PTEN overexpression leads to reduced neural precursor proliferation, premature neuronal differentiation, smaller organoids; PTEN overexpression leads to decreased AKT activation [257]
	KNL1	KNL1 homozygous missense coding-variant hESC line	KNL1c.6673 − 19 T > A mutation affects splicing, differentiating prematurely into neurons and astrocytes [300]
	AUTS2	1 patient-derived iPSC line carrying missense mutation in AUTS2	AUTS2 missense variant leads to reduced growth, deficits in neural progenitor cell proliferation and disrupted NPC polarity within VZ [301]
	ASPM	ASPM dysfunction patient-derived iPSC line	Down-regulated ASPM leads to abnormal cortical lamination resulting in defective neuronal activity [302]
	NARS1	7 patient-derived iPSCs carrying frameshift mutations in NARS1	Reduced NARS1 protein impairs proliferation of radial glial cells, and smaller organoids. NARS1 knockout reduces radial glial cells proliferation [303]
	IER3IP1	CRISPR-LICHT hESC line	Identifying 25 microcephaly candidate genes, IER3IP1 knockout results in dysregulated ECM protein deposition, tissue integrity deficits, also leads to microcephaly [304]
	Macrocephaly
	STRADA	Pretzel syndrome patient-derived iPSC lines with STRADA mutation	STRADA mutation leads to mTOR pathway hyperactivity, abnormally in neural rosette structures, delayed neurogenesis, decrease subventricular zone progenitors, abnormal architecture of primary cilia [305]
	RAB39B	RAB39B mutant PSC lines	RAB39B mutation leads to over proliferation and impaired differentiation of neural progenitor cells [306]
	Focal Cortical Dysplasia (FCD)
	Look into features of FCD	FCD type II patient-derived iPSC line into personalized dorsal and ventral forebrain organoids (DFOs/VFOs)	DFOs derived from FCD patient astrocytes effectively recapitulate heterogeneous pathological features [307]
	Timothy syndrome
	CACNA1C-pG406R	TS patient-derived iPSCs or CRISPR-edited CACNA1C-pG406R iPSCs into forebrain organoids	CACNA1C-p.G406R mutations lead to defective neuronal migration and abnormal electrical activity of neural networks [21]
	CACNA1C	CACNA1C mutation patient-derived iPSC line	CACNA1C mutation leads to abnormal migratory salutations in interneurons and functionally integration with glutamatergic neurons [308]
	Rett syndrome (RTT)
	MECP2	1 patient-derived iPSC line and 1 hESC line CRISPR–Cas9 modified with MECP2 knockout	MECP2 mutation/knockout causes synaptic dysregulation, epileptiform activity, and transcriptomic abnormalities in organoids, rescued by pifithrin-α [263, 309], it also induces premature deep cortical differentiation, impaired interneuron migration [262], BRD4-mediated dysregulation (correctable by JQ1) [310], structural deficits like disrupted VZ organization and impaired radial migration [311]. MECP2 knockdown increases progenitor proliferation, reduces neuronal maturation, and modulates ERK/MAPK and AKT signaling via miR-199 and miR-214 upregulation [312]
		RTT patient-derived iPSC line with MECP2 mutation
		1 MECP2 mutant hESC line edited by CRISPR–Cas9 into guided organoids
		MECP2 mutation patient-derived iPSCs and isogenic corrected iPSCs
		2 patient-derived iPSC lines and MECP2 short hairpin RNA knockdown
	–	RTT patient-derived iPSC lines	RTT hiPSCs undergo a premature transition into early born neurons, medial ganglionic eminence progenitors are impaired and might effect on interneuron’s migration [262]
	Look into features of RTT	RTT patient-derived iPSC lines	Defects in synapse formation, hyperexcitability and hypersyncronicity driven by interneuron deficiency;
			drug screen: rescue key physiological activities with pifithrin-α [263]
	Down Syndrome (DS)
	OLIG2	DS patient-derived iPSCs into forebrain organoids	DS hiPSC-derived ventral forebrain organoids exhibit higher percentage of OLIG2 + cells and GABAergic interneurons, particularly the CR + and SST + subtypes [181]
	–	DS patient-derived iPSCs into cortical organoids	DS cerebral organoids exhibit features that resemble aspects of AD, including Aβ deposition, tau protein lesion, and neuronal death [313]
	DSCAM, PAK1	iPSC-derived cerebral organoids	Suppression of the overactivated DSCAM/PAK1 pathway rescues impaired neurogenesis and cortical development in DS models; organoids exhibit increased size and restored marker expression [314]
Psychiatric disorders	Schizophrenia
	PCCB	PCCB knockdown in human forebrain organoids	PCCB knockdown inhibits tricarboxylic acid cycle, decreases GABA levels [315]
	Look into features of Schizophrenia	17 patient-derived iPSC lines into minimally guided organoids	Four GWAS factors (PTN, COMT, PLCL1, and PODXL) and peptide fragments are altered, and increase in apoptosis and decrease neurogenesis [316]
	DISC1	1 patient-derived iPSC line carrying a DISC1 heterozygous mutation into guided organoids;	DISC1 regulates neurogenesis through the NDEL1–NDE1 complex, and its mutation disrupts interaction, leading to radial glial cell cycle deficits [317] and impaired cortical neuronal fate specification [159]
		2 patient-derived iPSC lines carrying mutations in DISC1 into sliced guided organoids
	Bipolar disorder (BPI)
	Look into features of BPI	8 patient-derived iPSC lines into minimally guided organoids	The first time to identify the synergistic defects of multi-cell types (neurons, glial cells, synapses, generations) in BPI organoids [318]
	PLXNB1	1 PLXNB1 homozygous loss variant paediatric patient-derived iPSC line into single rosette guided organoids	Homozygous of PLXNB1 leads to dysregulated PLXNB1 signaling and neurite outgrowth deficits [319]
	Clinical effects of Li	11 patient-derived iPSC lines into minimally guided organoids treated with Li Alzheimer's disease (AD)	Lithium treatment restores neuronal excitability; upregulates kidney and ion associated genes and decreases the apoptotic TNF cascade via IL-1β [320]
	Neurodegenerative disease
	PHGDH	PHGDH knockdown hESC line induced brain organoids	Suppression of astrocytic PHGDH reduces Aβ aggregates and synaptic loss [321]
	PSEN1	AD patients harboring a missense mutation (A246E) in the presenilin 1 (PSN1) gene	patient-derived iPSC induced cortical organoids exhibit Aβ deposition, tau protein lesion, and neuronal death [313, 322]
	APOE4	CRISPR/Cas9 corrected isogenic iPSC lines harboring homozygous APOE4 alleles	APOE4 drives the AD phenotype through the lipid metabolization-inflammation-synaptic damage axis [269]
	APP duplication/PSEN1	AD patients harboring amyloid precursor protein (APP) duplication or presenilin1 (PSEN1) mutation	APP duplication and PSEN1 mutation derived organoids model key pathological features of AD, such as Aβ deposition, tau protein lesion, neuronal death [322]
	Parkinson's disease (PD)
	LRRK2	G2019S mutation in LRRK2 iPSC line with an environment similar to aged brain; G2019S mutation in LRRK2 iPSC patient-derived iPSC line	LRRK2 mutation promotes α-synuclein aggregation and impairs its clearance through TXNIP-mediated mechanisms [132], while simultaneously reducing the number and complexity of mDANs and causing functional defects in LRRK2-G2019S-expressing mDANs [246]
	PINK1	PINK1 mutation PD patient-derived iPSC line	PINK1 mutation reduces differentiation, increases proliferative activity, apoptosis of TH + neurons, and reduces autophagy and mitophagy capacity [323]
	SNCA	SNCA triplication patient-derived iPSC line	SNCA triplication elevates accumulation of a-synuclein, reduces dopaminergic neurons [324]

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RhoA, ras homolog gene family, member A; ASD, autism spectrum disorder; OPC, oligodendrocyte precursor cell; GABA, gama-aminobutyric acid; ECM, extracellular matrix; GWAS, genome-wide association study

Drug screen

Human organoids play an essential role in drug screen and have already yielded promising results. Several remarkable studies leverage organoid models to identify therapeutic interventions for neurodevelopmental defects. For example, PTEN mutations have been extensively investigated in this context. Loss of PTEN impairs its phosphatase activity, leading to hyperactivation of AKT and suppression of epithelial-mesenchymal transition, defects that could be rescued by Perifosine, an AKT inhibitor [266]. A subsequent study demonstrates that PTEN deficiency synergistically activates both mTORC1 and mTORC2 pathways, which could be restored by rapamycin treatment [267]. Beyond single-gene defects, organoid-based platforms are increasingly applied to complex disease entities. In Rett syndrome, patient-derived organoids with MECP2 deletions exhibit downregulation of the PI3K-AKT pathway and abnormal dendritic morphology. These deficits could be ameliorated by treatment with PI3K-AKT inhibitors such as KV-2449 or VPA, suggesting this pathway represents a therapeutic target for Rett syndrome [268]. Encouraged by these mechanistic–to–therapeutic arcs, investigators have turned to more complex paradigms.

In sporadic Alzheimer’s disease (sAD), isogenic conversion of Apolipoprotein E4 (APOE4) to APOE3 in patient-derived iPSCs alleviates most of the AD-related phenotypes observed in sAD iPSC-derived neurons, glia, and organoids [269]. In Rett syndrome patient-derived forebrain-subpallial organoids, valproate and the TP53 inhibitor pifithrin-α demonstrates the ability to rescue hypersynchronous calcium oscillations [263]. Similarly, in fragile X syndrome organoids, phosphoinositide 3-kinase (PI3K) antagonist reverses FMRP translational regulator 1 (FMR1)-repeat-expansion-driven progenitor depletion and hyperexcitability [270]. Organoids have also been proven valuable in modeling infectious causes of neuropathology: Zika virus (ZIKV)-induced microcephaly phenotypes, mediated through TLR3 upregulation, are mitigated by TLR3 inhibition [271], while maribavir partially restores rosette architecture and calcium activity in Cytomegalovirus (CMV)-infected organoids [272, 273]. Although these independent studies have substantially enriched the clinical insights into potential therapeutic targets for neurological diseases, further efforts remain essential prior to their translation into clinical practice.

In addition to the need for clinical verification, conventional organoid culture methods pose practical challenges for drug screening. They are labor-intensive, operationally complex, and exhibit batch-to-batch variability. These limitations hinder the production of sufficient, consistent organoids for large-scale screening. Therefore, the development of robust, high-throughput platforms for reproducible organoid generation is of great significance. Recent advances have started to address these needs. High-quality brain organoids (Hi-Q organoids) compatible with high-throughput screening (HTS) systems now enable the efficient production of hundreds of organoids per batch across multiple hiPSC lines [246, 247]. Hi-Q organoids recapitulate key developmental process and functional properties with high reproducibility and reduced cellular stress, enhancing their suitability for disease modeling and screening. They also support personalized medicine applications, allowing reproducible evaluation of patient-specific mutations and efficient identification of individualized treatments. Moreover, Hi-Q organoids have been employed in neurotoxicity assessments of environmental chemicals, providing robust insights into developmental neurotoxicology [274]. In a study, a web-based drug screening platform combining mathematical modeling and Alzheimer’s pathology in iPSC-derived cortical organoids (iCOs) are used to evaluate over 1,300 organoids from 11 participants. This high-content screening (HCS) system identifies FDA-approved blood-brain-barrier-permeable drugs, highlighting a strategy for precision medicine [275].

Despite these advances, there is still room for further optimization of the drug screening platform. Integration of cutting-edge technologies such as organ-on-a-chip and microfluidic systems may support more complex microenvironment simulations. The introduction of vascularization strategies is expected to solve the problem of insufficient nutrient supply within organoids. Combining organoids with CRISPR-based gene editing enables more precise disease modeling, while Artificial intelligence (AI)-assisted image analysis and data mining boost experimental throughput and discovery. In future, high-throughput drug screening platforms will significantly accelerate the screening and optimization process of neurological drugs. In the field of personalized medicine, patient-derived hiPSC-based organoids could forecast individual drug responses and guide therapeutic selection. In addition, high-throughput screening technology could also be extended to the research of other neurological diseases, offering new mechanistic and therapeutic insights. We anticipate that continued innovation will soon bridge the gap between laboratory research and clinical implementation, ultimately improving outcomes for patients with neurological diseases.

Conclusion and perspectives

Due to ethical and practical limitations associated with human embryos, investigating early human brain development remains challenging. For decades, mice have served as the primary model organism in this field, contributing substantially to our understanding of neurogenesis, the functional roles of key genes in brain development, and the mechanisms underlying neurodevelopmental disorders. Mouse brain organoids now offer a promising alternative that significantly reduces the number of animals used in studies. They also enable detailed observation of cellular behavior and function within a controlled environment, providing access to early developmental stages that are difficult to study in intact embryos. Additionally, generating mouse brain organoids takes about 10–14 days, whereas human brain organoids require months, making protocol optimization in human organoids both costly and time-consuming, especially since hPSCs are highly sensitive to the concentration and timing of signaling molecules. Therefore, refining protocols in mouse brain organoids in advance could significantly improve later protocol refinement in human brain organoids [17, 98].

While the mouse brain shares fundamental similarities with its human counterpart, critical differences in size, structure and developmental timing limit its direct translational relevance. Most recent studies have utilized brain organoids derived from hPSCs rather than mESCs, as hPSC-derived organoids better recapitulate human-specific developmental timelines and structural features. These models simulate various internal brain structures across developmental stages, offering a versatile platform to investigate neurogenesis and neural maturation [16, 115]. The capacity of human brain organoids to differentiate, self-organize, and form complex, biologically relevant structures make them an ideal system for studying disease mechanisms and conducting drug screening. Notably, given the cellular heterogeneity within organoids, the application of high-throughput technologies, particularly large-scale single-cell transcriptomic analyses, has yielded unprecedented resolution, revealing the extent of cellular diversity and molecular identity [114, 115, 226, 276]. These techniques have not only improved the validation of organoid fidelity but also enabled deeper insights into fetal transcriptional programs and normal developmental processes, thereby bridging gaps between in vitro models and in vivo development.

However, it is essential to confront the limitations inherent in current organoid modeling systems. Key shortcomings include high heterogeneity across protocols, incomplete recapitulation of architectural complexity, and slow neuronal maturation. To address these issues, automated culture systems could minimize experimental variability [277, 278], while bioengineering approaches may improve neuronal maturation, connectivity, and functional circuit formation across region-specific organoids. These advances would extend the modeling window to later fetal stages. Looking ahead, the field of brain organoids is transitioning from “structural mimicry” to “functional mimicry,” demanding more sophisticated omics technologies. In the future, the development of automated readout systems for high throughput analysis will be essential to transform organoid models into scalable platforms suitable for compound screening and drug discovery [166, 279].

Acknowledgements

We thank the Core Facility of Zhejiang University of Edinburgh (ZJE) Institute, the Biomed-X Laboratory of ZJE Institute, School of Medicine, Zhejiang Key Laboratory of Medical Imaging Artificial Intelligence, and State Key Laboratory of Biobased Transportation Fuel Technology, Zhejiang University, for continuous support.

Author contributions

Lingling Tong, Peiqi Tian and Di Chen designed the structure of this review. Lingling Tong, Peiqi Tian, Ruoxi Wang, Shiyun Niu, Ruoming Wang, Yaxuan Ye, Yuxin Wu, Wenjing Zhang and Yueqi Wang wrote and revised the manuscript. Lingling Tong, Peiqi Tian, Shiyun Niu, Ruoxi Wang, Ruoming Wang, Angelica Foggetti and Di Chen drafted and revised the figures and tables. All authors wrote and discussed the manuscript. All authors read and approved the final manuscript.

Funding

This work was supported by the National Key R&D Program of China awarded to DC (Grant No. 2024YFA1108100), National Natural Science Foundation of China awarded to DC (Grant No. 32270835), and Zhejiang Natural Science Foundation awarded to DC (Grant No. Z22C129553).

Data availability

Not applicable.

Declarations

Ethics approval and consent to participate

Not applicable.

Consent for publication

All authors consent for publication.

Competing interests

The authors declare that they have no competing interests.

Footnotes

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Lingling Tong and Peiqi Tian have contributed equally to this work.

Contributor Information

Angelica Foggetti, Email: foggetti@intl.zju.edu.cn.

Di Chen, Email: dichen@intl.zju.edu.cn.

References

1.Eriksson PS, Perfilieva E, Björk-Eriksson T, Alborn AM, Nordborg C, Peterson DA, et al. Neurogenesis in the adult human hippocampus. Nat Med. 1998;4(11):1313–7. [DOI] [PubMed] [Google Scholar]
2.Moreno-Jiménez EP, Flor-García M, Terreros-Roncal J, Rábano A, Cafini F, Pallas-Bazarra N, et al. Adult hippocampal neurogenesis is abundant in neurologically healthy subjects and drops sharply in patients with alzheimer’s disease. Nat Med. 2019;25(4):554–60. [DOI] [PubMed] [Google Scholar]
3.Santarelli L, Saxe M, Gross C, Surget A, Battaglia F, Dulawa S, et al. Requirement of hippocampal neurogenesis for the behavioral effects of antidepressants. Science. 2003;301(5634):805–9. [DOI] [PubMed] [Google Scholar]
4.Sorrells SF, Paredes MF, Cebrian-Silla A, Sandoval K, Qi D, Kelley KW, et al. Human hippocampal neurogenesis drops sharply in children to undetectable levels in adults. Nature. 2018;555(7696):377–81. [DOI] [PMC free article] [PubMed] [Google Scholar]
5.Boldrini M, Fulmore CA, Tartt AN, Simeon LR, Pavlova I, Poposka V, et al. Hum Hippocampal Neurogenesis Persists Throughout Aging Cell Stem Cell. 2018;22(4):589–e5995. [DOI] [PMC free article] [PubMed] [Google Scholar]
6.Ming GL, Song H. Adult neurogenesis in the mammalian brain: significant answers and significant questions. Neuron. 2011;70(4):687–702. [DOI] [PMC free article] [PubMed] [Google Scholar]
7.Velasco S, Kedaigle AJ, Simmons SK, Nash A, Rocha M, Quadrato G, et al. Individual brain organoids reproducibly form cell diversity of the human cerebral cortex. Nature. 2019;570(7762):523–7. [DOI] [PMC free article] [PubMed] [Google Scholar]
8.Llorens-Bobadilla E, Zhao S, Baser A, Saiz-Castro G, Zwadlo K, Martin-Villalba A. Single-Cell transcriptomics reveals a population of dormant neural stem cells that become activated upon brain injury. Cell Stem Cell. 2015;17(3):329–40. [DOI] [PubMed] [Google Scholar]
9.Baur K, Abdullah Y, Mandl C, Hölzl-Wenig G, Shi Y, Edelkraut U, et al. A novel stem cell type at the basal side of the subventricular zone maintains adult neurogenesis. EMBO Rep. 2022;23(9):e54078. [DOI] [PMC free article] [PubMed] [Google Scholar]
10.Shen Q, Wang Y, Dimos JT, Fasano CA, Phoenix TN, Lemischka IR, et al. The timing of cortical neurogenesis is encoded within lineages of individual progenitor cells. Nat Neurosci. 2006;9(6):743–51. [DOI] [PubMed] [Google Scholar]
11.Tropepe V, Sibilia M, Ciruna BG, Rossant J, Wagner EF, van der Kooy D. Distinct neural stem cells proliferate in response to EGF and FGF in the developing mouse telencephalon. Dev Biol. 1999;208(1):166–88. [DOI] [PubMed] [Google Scholar]
12.Chazal G, Durbec P, Jankovski A, Rougon G, Cremer H. Consequences of neural cell adhesion molecule deficiency on cell migration in the rostral migratory stream of the mouse. J Neurosci Off J Soc Neurosci. 2000;20(4):1446–57. [DOI] [PMC free article] [PubMed] [Google Scholar]
13.Workman AD, Charvet CJ, Clancy B, Darlington RB, Finlay BL. Modeling transformations of neurodevelopmental sequences across mammalian species. J Neurosci. 2013;33(17):7368–83. [DOI] [PMC free article] [PubMed] [Google Scholar]
14.Hansen DV, Lui JH, Parker PRL, Kriegstein AR. Neurogenic radial glia in the outer subventricular zone of human neocortex. Nature. 2010;464(7288):554–61. [DOI] [PubMed] [Google Scholar]
15.Eiraku M, Takata N, Ishibashi H, Kawada M, Sakakura E, Okuda S, et al. Self-organizing optic-cup morphogenesis in three-dimensional culture. Nature. 2011;472(7341):51–6. [DOI] [PubMed] [Google Scholar]
16.Lancaster MA, Renner M, Martin CA, Wenzel D, Bicknell LS, Hurles ME, et al. Cerebral organoids model human brain development and microcephaly. Nature. 2013;501(7467):373–9. [DOI] [PMC free article] [PubMed] [Google Scholar]
17.Kadoshima T, Sakaguchi H, Nakano T, Soen M, Ando S, Eiraku M, et al. Self-organization of axial polarity, inside-out layer pattern, and species-specific progenitor dynamics in human ES cell-derived neocortex. Proc Natl Acad Sci U S A. 2013;110(50):20284–9. [DOI] [PMC free article] [PubMed] [Google Scholar]
18.Paşca AM, Sloan SA, Clarke LE, Tian Y, Makinson CD, Huber N, et al. Functional cortical neurons and astrocytes from human pluripotent stem cells in 3D culture. Nat Methods. 2015;12(7):671–8. [DOI] [PMC free article] [PubMed] [Google Scholar]
19.Mariani J, Coppola G, Zhang P, Abyzov A, Provini L, Tomasini L, et al. FOXG1-Dependent dysregulation of GABA/Glutamate neuron differentiation in autism spectrum disorders. Cell. 2015;162(2):375–90. [DOI] [PMC free article] [PubMed] [Google Scholar]
20.Xiang Y, Tanaka Y, Cakir B, Patterson B, Kim KY, Sun P, et al. hESC-Derived thalamic organoids form reciprocal projections when fused with cortical organoids. Cell Stem Cell. 2019;24(3):487–e4977. [DOI] [PMC free article] [PubMed] [Google Scholar]
21.Birey F, Andersen J, Makinson CD, Islam S, Wei W, Huber N, et al. Assembly of functionally integrated human forebrain spheroids. Nature. 2017;545(7652):54–9. [DOI] [PMC free article] [PubMed] [Google Scholar]
22.Qian X, Nguyen HN, Song MM, Hadiono C, Ogden SC, Hammack C, et al. Brain-Region-Specific organoids using Mini-bioreactors for modeling ZIKV exposure. Cell. 2016;165(5):1238–54. [DOI] [PMC free article] [PubMed] [Google Scholar]
23.Wang F, Hao S, Park K, Ahmady A, Zhou C. Label-free evaluation of mouse embryo quality using time-lapse bright field and optical coherence microscopy. Commun Biol. 2025;8(1):1–12. [DOI] [PMC free article] [PubMed] [Google Scholar]
24.Rivera-Pérez JA, Hadjantonakis AK. The dynamics of morphogenesis in the early mouse embryo. Cold Spring Harb Perspect Biol. 2015;7(11):a015867. [DOI] [PMC free article] [PubMed] [Google Scholar]
25.Aguilera-Castrejon A, Oldak B, Shani T, Ghanem N, Itzkovich C, Slomovich S, et al. Ex utero mouse embryogenesis from pre-gastrulation to late organogenesis. Nature. 2021;593(7857):119–24. [DOI] [PubMed] [Google Scholar]
26.Arnold SJ, Robertson EJ. Making a commitment: cell lineage allocation and axis patterning in the early mouse embryo. Nat Rev Mol Cell Biol. 2009;10(2):91–103. [DOI] [PubMed] [Google Scholar]
27.Colas JF, Schoenwolf GC. Towards a cellular and molecular Understanding of neurulation. Dev Dyn. 2001;221(2):117–45. [DOI] [PubMed] [Google Scholar]
28.Rubenstein JLR, Shimamura K, Martinez S, Puelles L. REGIONALIZATION OF THE PROSENCEPHALIC NEURAL PLATE. Annu Rev Neurosci. 1998;21(Volume 21, 1998):445–77. [DOI] [PubMed]
29.Greene NDE, Copp AJ. Development of the vertebrate central nervous system: formation of the neural tube. Prenat Diagn. 2009;29(4):303–11. [DOI] [PubMed] [Google Scholar]
30.Kaufman MH, Bard JBL. The anatomical basis of mouse development. Gulf Professional Publishing; 1999. p. 306.
31.Chen VS, Morrison JP, Southwell MF, Foley JF, Bolon B, Elmore SA. Histology atlas of the developing prenatal and postnatal mouse central nervous System, with emphasis on prenatal days E7.5 to E18.5. Toxicol Pathol. 2017;45(6):705–44. [DOI] [PMC free article] [PubMed] [Google Scholar]
32.Liu W, Lagutin O, Swindell E, Jamrich M, Oliver G. Neuroretina specification in mouse embryos requires Six3-mediated suppression of Wnt8b in the anterior neural plate. J Clin Invest. 2010;120(10):3568–77. [DOI] [PMC free article] [PubMed] [Google Scholar]
33.Wang J, Sinha T, Wynshaw-Boris A. Wnt signaling in mammalian development: lessons from mouse genetics. Cold Spring Harb Perspect Biol. 2012;4(5):a007963. [DOI] [PMC free article] [PubMed] [Google Scholar]
34.Gibbs HC, Chang-Gonzalez A, Hwang W, Yeh AT, Lekven AC. Midbrain-Hindbrain boundary morphogenesis: at the intersection of Wnt and Fgf signaling. Front Neuroanat. 2017;11:64. [DOI] [PMC free article] [PubMed] [Google Scholar]
35.Bedois AMH, Parker HJ, Krumlauf R. Retinoic acid signaling in vertebrate hindbrain segmentation: evolution and diversification. Diversity. 2021;13(8):398. [Google Scholar]
36.De Bakker BS, De Jong KH, Hagoort J, De Bree K, Besselink CT, De Kanter FEC, et al. An interactive three-dimensional digital atlas and quantitative database of human development. Science. 2016;354(6315):aag0053. [DOI] [PubMed] [Google Scholar]
37.Vetter R, Iber D. Precision of morphogen gradients in neural tube development. Nat Commun. 2022;13(1):1145. [DOI] [PMC free article] [PubMed] [Google Scholar]
38.Gupta S, Butler SJ. Getting in touch with your senses: mechanisms specifying sensory interneurons in the dorsal spinal cord. Wires Mech Dis. 2021;13(5):e1520. [DOI] [PMC free article] [PubMed] [Google Scholar]
39.Eto H, Kishi Y, Yakushiji-Kaminatsui N, Sugishita H, Utsunomiya S, Koseki H, et al. The polycomb group protein Ring1 regulates dorsoventral patterning of the mouse telencephalon. Nat Commun. 2020;11(1):5709. [DOI] [PMC free article] [PubMed] [Google Scholar]
40.Angevine JB Jr, Bodian D, Coulombre AJ, Edds MV Jr., Hamburger V, Jacobson M, et al. Embryonic vertebrate central nervous system: revised terminology. Anat Rec. 1970;166(2):257–61. [DOI] [PubMed] [Google Scholar]
41.Kriegstein A, Alvarez-Buylla A. The glial nature of embryonic and adult neural stem cells. Annu Rev Neurosci. 2009;32(32, 2009):149–84. [DOI] [PMC free article] [PubMed] [Google Scholar]
42.Koo B, Lee KH, Ming G, li, Yoon KJ, Song H. Setting the clock of neural progenitor cells during mammalian corticogenesis. Semin Cell Dev Biol. 2023;142:43–53. [DOI] [PMC free article] [PubMed] [Google Scholar]
43.Jiang X, Nardelli J. Cellular and molecular introduction to brain development. Neurobiol Dis. 2016;92:3–17. [DOI] [PMC free article] [PubMed] [Google Scholar]
44.Molyneaux BJ, Arlotta P, Menezes JRL, Macklis JD. Neuronal subtype specification in the cerebral cortex. Nat Rev Neurosci. 2007;8(6):427–37. [DOI] [PubMed] [Google Scholar]
45.Marín-Padilla M. Cajal-Retzius cells and the development of the neocortex. Trends Neurosci. 1998;21(2):64–71. [DOI] [PubMed] [Google Scholar]
46.Gorski JA, Talley T, Qiu M, Puelles L, Rubenstein JLR, Jones KR. Cortical excitatory neurons and glia, but not GABAergic neurons, are produced in the Emx1-expressing lineage. J Neurosci Off J Soc Neurosci. 2002;22(15):6309–14. [DOI] [PMC free article] [PubMed] [Google Scholar]
47.Ueno M, Nakamura Y, Li J, Gu Z, Niehaus J, Maezawa M, et al. Corticospinal circuits from the sensory and motor cortices differentially regulate skilled movements through distinct spinal interneurons. Cell Rep. 2018;23(5):1286–e13007. [DOI] [PMC free article] [PubMed] [Google Scholar]
48.Lavdas AA, Grigoriou M, Pachnis V, Parnavelas JG. The medial ganglionic eminence gives rise to a population of early neurons in the developing cerebral cortex. J Neurosci. 1999;19(18):7881–8. [DOI] [PMC free article] [PubMed] [Google Scholar]
49.Viollet C, Lepousez G, Loudes C, Videau C, Simon A, Epelbaum J. Somatostatinergic systems in brain: networks and functions. Mol Cell Endocrinol. 2008;286(1):75–87. [DOI] [PubMed] [Google Scholar]
50.Wang WZ, Hoerder-Suabedissen A, Oeschger FM, Bayatti N, Ip BK, Lindsay S, et al. Subplate in the developing cortex of mouse and human. J Anat. 2010;217(4):368–80. [DOI] [PMC free article] [PubMed] [Google Scholar]
51.Hoerder-Suabedissen A, Molnár Z. Development, evolution and pathology of neocortical subplate neurons. Nat Rev Neurosci. 2015;16(3):133–46. [DOI] [PubMed] [Google Scholar]
52.Stiles J, Jernigan TL. The basics of brain development. Neuropsychol Rev. 2010;20(4):327–48. [DOI] [PMC free article] [PubMed] [Google Scholar]
53.Jiang M, Yu D, Xie B, Huang H, Lu W, Qiu M, et al. WNT signaling suppresses oligodendrogenesis via Ngn2-dependent direct Inhibition of Olig2 expression. Mol Brain. 2020;13:155. [DOI] [PMC free article] [PubMed] [Google Scholar]
54.Tabata H, Nakajima K. Multipolar migration: the third mode of radial neuronal migration in the developing cerebral cortex. J Neurosci Off J Soc Neurosci. 2003;23(31):9996–10001. [DOI] [PMC free article] [PubMed] [Google Scholar]
55.Accogli A, Addour-Boudrahem N, Srour M. Neurogenesis, neuronal migration, and axon guidance. Handb Clin Neurol. 2020;173:25–42. [DOI] [PubMed] [Google Scholar]
56.Vivi E, Di Benedetto B. Brain stars take the lead during critical periods of early postnatal brain development: relevance of astrocytes in health and mental disorders. Mol Psychiatry. 2024;29(9):2821–33. [DOI] [PMC free article] [PubMed] [Google Scholar]
57.Lattke M, Guillemot F. Understanding astrocyte differentiation: clinical relevance, technical challenges, and new opportunities in the omics era. Wires Mech Dis. 2022;14(5):e1557. [DOI] [PMC free article] [PubMed] [Google Scholar]
58.Yabut OR, Pleasure SJ. Sonic Hedgehog signaling rises to the surface: emerging roles in neocortical development. Brain Plast. 2018;3(2):119–28. [DOI] [PMC free article] [PubMed] [Google Scholar]
59.Bocchi R, Thorwirth M, Simon-Ebert T, Koupourtidou C, Clavreul S, Kolf K, et al. Astrocyte heterogeneity reveals region-specific astrogenesis in the white matter. Nat Neurosci. 2025;28(3):457–69. [DOI] [PMC free article] [PubMed] [Google Scholar]
60.Kronman FN, Liwang JK, Betty R, Vanselow DJ, Wu YT, Tustison NJ, et al. Developmental mouse brain common coordinate framework. Nat Commun. 2024;15(1):9072. [DOI] [PMC free article] [PubMed] [Google Scholar]
61.Nadarajah B. Radial glia and somal translocation of radial neurons in the developing cerebral cortex. Glia. 2003;43(1):33–6. [DOI] [PubMed] [Google Scholar]
62.Luskin MB. Restricted proliferation and migration of postnatally generated neurons derived from the forebrain subventricular zone. Neuron. 1993;11(1):173–89. [DOI] [PubMed] [Google Scholar]
63.Kim JY, Paredes MF. Implications of extended inhibitory neuron development. Int J Mol Sci. 2021;22(10):5113. [DOI] [PMC free article] [PubMed] [Google Scholar]
64.Barber M, Pierani A. Tangential migration of glutamatergic neurons and cortical patterning during development: lessons from Cajal-Retzius cells. Dev Neurobiol. 2016;76(8):847–81. [DOI] [PubMed] [Google Scholar]
65.Foran DR, Peterson AC. Myelin acquisition in the central nervous system of the mouse revealed by an MBP-Lac Z transgene. J Neurosci Off J Soc Neurosci. 1992;12(12):4890–7. [DOI] [PMC free article] [PubMed] [Google Scholar]
66.Semple BD, Blomgren K, Gimlin K, Ferriero DM, Noble-Haeusslein LJ. Brain development in rodents and humans: identifying benchmarks of maturation and vulnerability to injury across species. Prog Neurobiol. 2013;0:1–16. [DOI] [PMC free article] [PubMed] [Google Scholar]
67.Waites CL, Craig AM, Garner CC. Mechanisms of vertebrate synaptogenesis. Annu Rev Neurosci. 2005;28:251–74. [DOI] [PubMed] [Google Scholar]
68.Li Y, Aimone JB, Xu X, Callaway EM, Gage FH. Development of GABAergic inputs controls the contribution of maturing neurons to the adult hippocampal network. Proc Natl Acad Sci U S A. 2012;109(11):4290–5. [DOI] [PMC free article] [PubMed] [Google Scholar]
69.Birnie MT, Baram TZ. Principles of emotional brain circuit maturation. Science. 2022;376(6597):1055–6. [DOI] [PMC free article] [PubMed] [Google Scholar]
70.Bond AM, Bhalala OG, Kessler JA. The dynamic role of bone morphogenetic proteins in neural stem cell fate and maturation. Dev Neurobiol. 2012;72(7):1068–84. [DOI] [PMC free article] [PubMed] [Google Scholar]
71.Atamian A, Birtele M, Hosseini N, Nguyen T, Seth A, Del Dosso A, et al. Human cerebellar organoids with functional purkinje cells. Cell Stem Cell. 2024;31(1):39–e516. [DOI] [PMC free article] [PubMed] [Google Scholar]
72.Xue X, Kim YS, Ponce-Arias AI, O’Laughlin R, Yan RZ, Kobayashi N, et al. A patterned human neural tube model using microfluidic gradients. Nature. 2024;628(8007):391–9. [DOI] [PMC free article] [PubMed] [Google Scholar]
73.Zhou Y, Song H, Ming G. li. Genetics of human brain development. Nat Rev Genet. 2024;25(1):26–45. [DOI] [PMC free article] [PubMed]
74.Fietz SA, Kelava I, Vogt J, Wilsch-Bräuninger M, Stenzel D, Fish JL, et al. OSVZ progenitors of human and ferret neocortex are epithelial-like and expand by integrin signaling. Nat Neurosci. 2010;13(6):690–9. [DOI] [PubMed] [Google Scholar]
75.Nowakowski TJ, Pollen AA, Sandoval-Espinosa C, Kriegstein AR. Transformation of the radial glia scaffold demarcates two stages of human cerebral cortex development. Neuron. 2016;91(6):1219–27. [DOI] [PMC free article] [PubMed] [Google Scholar]
76.Bilgic M, Wu Q, Suetsugu T, Shitamukai A, Tsunekawa Y, Shimogori T et al. Truncated radial glia as a common precursor in the late corticogenesis of gyrencephalic mammals. eLife 12:RP91406. [DOI] [PMC free article] [PubMed]
77.Yu D, Jain S, Wangzhou A, Zhu B, Shao W, Coley-O’Rourke EJ et al. Microglia regulate GABAergic neurogenesis in prenatal human brain through IGF1. Nature. 2025. [DOI] [PMC free article] [PubMed]
78.Taverna E, Götz M, Huttner WB. The cell biology of neurogenesis: toward an Understanding of the development and evolution of the neocortex. Annu Rev Cell Dev Biol. 2014;30:465–502. [DOI] [PubMed] [Google Scholar]
79.Jakovcevski I, Filipovic R, Mo Z, Rakic S, Zecevic N. Oligodendrocyte development and the onset of myelination in the human fetal brain. Front Neuroanat. [DOI] [PMC free article] [PubMed]
80.Frazel PW, Labib D, Fisher T, Brosh R, Pirjanian N, Marchildon A, et al. Longitudinal scRNA-seq analysis in mouse and human informs optimization of rapid mouse astrocyte differentiation protocols. Nat Neurosci. 2023;26(10):1726–38. [DOI] [PMC free article] [PubMed] [Google Scholar]
81.Marín O, Rubenstein JLR. Cell migration in the forebrain. Annu Rev Neurosci. 2003;26(26, 2003):441–83. [DOI] [PubMed] [Google Scholar]
82.Ayala R, Shu T, Tsai LH. Trekking across the brain: the journey of neuronal migration. Cell. 2007;128(1):29–43. [DOI] [PubMed] [Google Scholar]
83.Nadarajah B, Parnavelas JG. Modes of neuronal migration in the developing cerebral cortex. Nat Rev Neurosci. 2002;3(6):423–32. [DOI] [PubMed] [Google Scholar]
84.Taylor KR, Monje M. Neuron–oligodendroglial interactions in health and malignant disease. Nat Rev Neurosci. 2023;24(12):733–46. [DOI] [PMC free article] [PubMed] [Google Scholar]
85.McNamara NB, Munro DAD, Bestard-Cuche N, Uyeda A, Bogie JFJ, Hoffmann A, et al. Microglia regulate central nervous system Myelin growth and integrity. Nature. 2023;613(7942):120–9. [DOI] [PMC free article] [PubMed] [Google Scholar]
86.Schmidt ERE, Zhao HT, Park JM, Dipoppa M, Monsalve-Mercado MM, Dahan JB, et al. A human-specific modifier of cortical connectivity and circuit function. Nature. 2021;599(7886):640–4. [DOI] [PMC free article] [PubMed] [Google Scholar]
87.Azevedo FAC, Carvalho LRB, Grinberg LT, Farfel JM, Ferretti REL, Leite REP, et al. Equal numbers of neuronal and nonneuronal cells make the human brain an isometrically scaled-up primate brain. J Comp Neurol. 2009;513(5):532–41. [DOI] [PubMed] [Google Scholar]
88.Herculano-Houzel S. The remarkable, yet not extraordinary, human brain as a scaled-up primate brain and its associated cost. Proc Natl Acad Sci U S A. 2012;109(Suppl 1):10661–8. [DOI] [PMC free article] [PubMed] [Google Scholar]
89.Zarzor MS, Blumcke I, Budday S. Exploring the role of the outer subventricular zone during cortical folding through a physics-based model. eLife. 2023;12:e82925. [DOI] [PMC free article] [PubMed] [Google Scholar]
90.Prodromidou K, Matsas R. Evolving features of human cortical development and the emerging roles of non-coding RNAs in neural progenitor cell diversity and function. Cell Mol Life Sci CMLS. 2021;79(1):56. [DOI] [PMC free article] [PubMed] [Google Scholar]
91.Jacobson M, Rao MS, editors. Developmental neurobiology. 4th ed. New York: Kluwer Academic/Plenum; 2005. p. 424. [Google Scholar]
92.Fang R, Xia C, Close JL, Zhang M, He J, Huang Z, et al. Conservation and divergence of cortical cell organization in human and mouse revealed by MERFISH. Science. 2022;377(6601):56–62. [DOI] [PMC free article] [PubMed] [Google Scholar]
93.Luo X, Liu Y, Dang D, Hu T, Hou Y, Meng X, et al. 3D genome of macaque fetal brain reveals evolutionary innovations during primate corticogenesis. Cell. 2021;184(3):723–e74021. [DOI] [PubMed] [Google Scholar]
94.Zhong S, Wang M, Huang L, Chen Y, Ge Y, Zhang J, et al. Single-cell epigenomics and Spatiotemporal transcriptomics reveal human cerebellar development. Nat Commun. 2023;14(1):7613. [DOI] [PMC free article] [PubMed] [Google Scholar]
95.Terauchi A, Yee P, Johnson-Venkatesh EM, Seiglie MP, Kim L, Pitino JC, et al. The projection-specific signals that Establish functionally segregated dopaminergic synapses. Cell. 2023;186(18):3845–e386124. [DOI] [PMC free article] [PubMed] [Google Scholar]
96.Freeman MR. Specification and morphogenesis of astrocytes. Science. 2010;330(6005):774–8. [DOI] [PMC free article] [PubMed] [Google Scholar]
97.Ruiz-Jiménez JM, Santpere G. The impact of human accelerated regions on neuronal development. Trends Genet TIG. 2025;41(6):459–61. [DOI] [PubMed] [Google Scholar]
98.Eiraku M, Watanabe K, Matsuo-Takasaki M, Kawada M, Yonemura S, Matsumura M, et al. Self-Organized formation of polarized cortical tissues from ESCs and its active manipulation by extrinsic signals. Cell Stem Cell. 2008;3(5):519–32. [DOI] [PubMed] [Google Scholar]
99.Shiraishi A, Muguruma K, Sasai Y. Generation of thalamic neurons from mouse embryonic stem cells. Development. 2017;144(7):1211–20. [DOI] [PubMed] [Google Scholar]
100.Park J, Hsiung HA, Khven I, La Manno G, Lutolf MP. Self-organizing in vitro mouse neural tube organoids mimic embryonic development. Development. 2022;149(20):dev201052. [DOI] [PubMed] [Google Scholar]
101.Ciarpella F, Zamfir RG, Campanelli A, Pedrotti G, Di Chio M, Bottani E, et al. Generation of mouse hippocampal brain organoids from primary embryonic neural stem cells. STAR Protoc. 2023;4(3):102413. [DOI] [PMC free article] [PubMed] [Google Scholar]
102.Hodge RD, Bakken TE, Miller JA, Smith KA, Barkan ER, Graybuck LT, et al. Conserved cell types with divergent features in human versus mouse cortex. Nature. 2019;573(7772):61–8. [DOI] [PMC free article] [PubMed] [Google Scholar]
103.Lake BB, Ai R, Kaeser GE, Salathia NS, Yung YC, Liu R, et al. Neuronal subtypes and diversity revealed by single-nucleus RNA sequencing of the human brain. Science. 2016;352(6293):1586–90. [DOI] [PMC free article] [PubMed] [Google Scholar]
104.van den Heuvel MP, Sporns O. Rich-club organization of the human connectome. J Neurosci Off J Soc Neurosci. 2011;31(44):15775–86. [DOI] [PMC free article] [PubMed] [Google Scholar]
105.Miller JA, Ding SL, Sunkin SM, Smith KA, Ng L, Szafer A, et al. Transcriptional landscape of the prenatal human brain. Nature. 2014;508(7495):199–206. [DOI] [PMC free article] [PubMed] [Google Scholar]
106.Sousa AMM, Meyer KA, Santpere G, Gulden FO, Sestan N. Evolution of the human nervous system Function, Structure, and development. Cell. 2017;170(2):226–47. [DOI] [PMC free article] [PubMed] [Google Scholar]
107.Yu J, Vodyanik MA, Smuga-Otto K, Antosiewicz-Bourget J, Frane JL, Tian S, et al. Induced pluripotent stem cell lines derived from human somatic cells. Science. 2007;318(5858):1917–20. [DOI] [PubMed] [Google Scholar]
108.Stadtfeld M, Hochedlinger K. Induced pluripotency: history, mechanisms, and applications. Genes Dev. 2010;24(20):2239–63. [DOI] [PMC free article] [PubMed] [Google Scholar]
109.Reynolds BA, Tetzlaff W, Weiss S. A multipotent EGF-responsive striatal embryonic progenitor cell produces neurons and astrocytes. J Neurosci Off J Soc Neurosci. 1992;12(11):4565–74. [DOI] [PMC free article] [PubMed] [Google Scholar]
110.Zhang SC, Wernig M, Duncan ID, Brüstle O, Thomson JA. In vitro differentiation of transplantable neural precursors from human embryonic stem cells. Nat Biotechnol. 2001;19(12):1129–33. [DOI] [PubMed] [Google Scholar]
111.Sasai Y. Next-generation regenerative medicine: organogenesis from stem cells in 3D culture. Cell Stem Cell. 2013;12(5):520–30. [DOI] [PubMed] [Google Scholar]
112.Hu BY, Zhang SC. Directed differentiation of neural-stem cells and subtype-specific neurons from hESCs. Methods Mol Biol Clifton NJ. 2010;636:123–37. [DOI] [PMC free article] [PubMed] [Google Scholar]
113.Wu Y, Liu Y, Chesnut JD, Rao MS. Isolation of neural stem and precursor cells from rodent tissue. Methods Mol Biol Clifton NJ. 2008;438:39–53. [DOI] [PubMed] [Google Scholar]
114.Lancaster MA, Knoblich JA. Generation of cerebral organoids from human pluripotent stem cells. Nat Protoc. 2014;9(10):2329–40. [DOI] [PMC free article] [PubMed] [Google Scholar]
115.Quadrato G, Nguyen T, Macosko EZ, Sherwood JL, Min Yang S, Berger DR, et al. Cell diversity and network dynamics in photosensitive human brain organoids. Nature. 2017;545(7652):48–53. [DOI] [PMC free article] [PubMed] [Google Scholar]
116.Camp JG, Badsha F, Florio M, Kanton S, Gerber T, Wilsch-Bräuninger M, et al. Human cerebral organoids recapitulate gene expression programs of fetal neocortex development. Proc Natl Acad Sci U S A. 2015;112(51):15672–7. [DOI] [PMC free article] [PubMed] [Google Scholar]
117.Sun AX, Ng HH, Tan EK. Translational potential of human brain organoids. Ann Clin Transl Neurol. 2018;5(2):226–35. [DOI] [PMC free article] [PubMed] [Google Scholar]
118.Rigamonti A, Repetti GG, Sun C, Price FD, Reny DC, Rapino F, et al. Large-Scale production of mature neurons from human pluripotent stem cells in a Three-Dimensional suspension culture system. Stem Cell Rep. 2016;6(6):993–1008. [DOI] [PMC free article] [PubMed] [Google Scholar]
119.Sloan SA, Darmanis S, Huber N, Khan TA, Birey F, Caneda C, et al. Human astrocyte maturation captured in 3D cerebral cortical spheroids derived from pluripotent stem cells. Neuron. 2017;95(4):779–e7906. [DOI] [PMC free article] [PubMed] [Google Scholar]
120.Schukking M, Miranda HC, Trujillo CA, Negraes PD, Muotri AR. Direct generation of human cortical organoids from primary cells. Stem Cells Dev. 2018;27(22):1549–56. [DOI] [PMC free article] [PubMed] [Google Scholar]
121.Trujillo CA, Gao R, Negraes PD, Gu J, Buchanan J, Preissl S, et al. Complex oscillatory waves emerging from cortical organoids model early human brain network development. Cell Stem Cell. 2019;25(4):558–e5697. [DOI] [PMC free article] [PubMed] [Google Scholar]
122.Lancaster MA, Corsini NS, Wolfinger S, Gustafson EH, Phillips AW, Burkard TR, et al. Guided self-organization and cortical plate formation in human brain organoids. Nat Biotechnol. 2017;35(7):659–66. [DOI] [PMC free article] [PubMed] [Google Scholar]
123.Madhavan M, Nevin ZS, Shick HE, Garrison E, Clarkson-Paredes C, Karl M, et al. Induction of myelinating oligodendrocytes in human cortical spheroids. Nat Methods. 2018;15(9):700–6. [DOI] [PMC free article] [PubMed] [Google Scholar]
124.Mansour AA, Gonçalves JT, Bloyd CW, Li H, Fernandes S, Quang D, et al. An in vivo model of functional and vascularized human brain organoids. Nat Biotechnol. 2018;36(5):432–41. [DOI] [PMC free article] [PubMed] [Google Scholar]
125.Bagley JA, Reumann D, Bian S, Lévi-Strauss J, Knoblich JA. Fused cerebral organoids model interactions between brain regions. Nat Methods. 2017;14(7):743–51. [DOI] [PMC free article] [PubMed] [Google Scholar]
126.Sakaguchi H, Kadoshima T, Soen M, Narii N, Ishida Y, Ohgushi M, et al. Generation of functional hippocampal neurons from self-organizing human embryonic stem cell-derived dorsomedial telencephalic tissue. Nat Commun. 2015;6:8896. [DOI] [PMC free article] [PubMed] [Google Scholar]
127.Jo J, Xiao Y, Sun AX, Cukuroglu E, Tran HD, Göke J, et al. Midbrain-like organoids from human pluripotent stem cells contain functional dopaminergic and Neuromelanin-Producing neurons. Cell Stem Cell. 2016;19(2):248–57. [DOI] [PMC free article] [PubMed] [Google Scholar]
128.Kwak TH, Kang JH, Hali S, Kim J, Kim KP, Park C, et al. Generation of homogeneous midbrain organoids with in vivo-like cellular composition facilitates neurotoxin-based parkinson’s disease modeling. Stem Cells Dayt Ohio. 2020;38(6):727–40. [DOI] [PubMed] [Google Scholar]
129.Monzel AS, Smits LM, Hemmer K, Hachi S, Moreno EL, van Wuellen T, et al. Derivation of human Midbrain-Specific organoids from neuroepithelial stem cells. Stem Cell Rep. 2017;8(5):1144–54. [DOI] [PMC free article] [PubMed] [Google Scholar]
130.Tieng V, Stoppini L, Villy S, Fathi M, Dubois-Dauphin M, Krause KH. Engineering of midbrain organoids containing long-lived dopaminergic neurons. Stem Cells Dev. 2014;23(13):1535–47. [DOI] [PubMed] [Google Scholar]
131.Kim H, Park HJ, Choi H, Chang Y, Park H, Shin J, et al. Modeling G2019S-LRRK2 sporadic parkinson’s disease in 3D midbrain organoids. Stem Cell Rep. 2019;12(3):518–31. [DOI] [PMC free article] [PubMed] [Google Scholar]
132.Ozone C, Suga H, Eiraku M, Kadoshima T, Yonemura S, Takata N, et al. Functional anterior pituitary generated in self-organizing culture of human embryonic stem cells. Nat Commun. 2016;7:10351. [DOI] [PMC free article] [PubMed] [Google Scholar]
133.Muguruma K, Nishiyama A, Kawakami H, Hashimoto K, Sasai Y. Self-organization of polarized cerebellar tissue in 3D culture of human pluripotent stem cells. Cell Rep. 2015;10(4):537–50. [DOI] [PubMed] [Google Scholar]
134.Ogura T, Sakaguchi H, Miyamoto S, Takahashi J. Three-dimensional induction of dorsal, intermediate and ventral spinal cord tissues from human pluripotent stem cells. Dev Camb Engl. 2018;145(16):dev162214. [DOI] [PMC free article] [PubMed] [Google Scholar]
135.Lee JH, Shin H, Shaker MR, Kim HJ, Park SH, Kim JH, et al. Production of human spinal-cord organoids recapitulating neural-tube morphogenesis. Nat Biomed Eng. 2022;6(4):435–48. [DOI] [PubMed] [Google Scholar]
136.Gribaudo S, Robert R, van Sambeek B, Mirdass C, Lyubimova A, Bouhali K, et al. Self-organizing models of human trunk organogenesis recapitulate spinal cord and spine co-morphogenesis. Nat Biotechnol. 2024;42(8):1243–53. [DOI] [PubMed] [Google Scholar]
137.Jacob F, Pather SR, Huang WK, Zhang F, Wong SZH, Zhou H, et al. Human pluripotent stem Cell-Derived neural cells and brain organoids reveal SARS-CoV-2 neurotropism predominates in choroid plexus epithelium. Cell Stem Cell. 2020;27(6):937–e9509. [DOI] [PMC free article] [PubMed] [Google Scholar]
138.Miura Y, Li MY, Birey F, Ikeda K, Revah O, Thete MV, et al. Generation of human striatal organoids and cortico-striatal assembloids from human pluripotent stem cells. Nat Biotechnol. 2020;38(12):1421–30. [DOI] [PMC free article] [PubMed] [Google Scholar]
139.Huang WK, Wong SZH, Pather SR, Nguyen PTT, Zhang F, Zhang DY, et al. Generation of hypothalamic arcuate organoids from human induced pluripotent stem cells. Cell Stem Cell. 2021;28(9):1657–e167010. [DOI] [PMC free article] [PubMed] [Google Scholar]
140.Fligor CM, Langer KB, Sridhar A, Ren Y, Shields PK, Edler MC, et al. Three-Dimensional retinal organoids facilitate the investigation of retinal ganglion cell Development, organization and neurite outgrowth from human pluripotent stem cells. Sci Rep. 2018;8(1):14520. [DOI] [PMC free article] [PubMed] [Google Scholar]
141.Kuwahara A, Ozone C, Nakano T, Saito K, Eiraku M, Sasai Y. Generation of a ciliary margin-like stem cell niche from self-organizing human retinal tissue. Nat Commun. 2015;6:6286. [DOI] [PubMed] [Google Scholar]
142.Giandomenico SL, Mierau SB, Gibbons GM, Wenger LMD, Masullo L, Sit T, et al. Cerebral organoids at the air–liquid interface generate diverse nerve tracts with functional output. Nat Neurosci. 2019;22(4):669–79. [DOI] [PMC free article] [PubMed] [Google Scholar]
143.Wu W, Liu Y, Liu R, Wang Y, Zhao Y, Li H, et al. Decellularized brain extracellular matrix hydrogel aids the formation of human Spinal-Cord organoids recapitulating the complex Three-Dimensional organization. ACS Biomater Sci Eng. 2024;10(5):3203–17. [DOI] [PubMed] [Google Scholar]
144.Faissner A, Reinhard J. The extracellular matrix compartment of neural stem and glial progenitor cells. Glia. 2015;63(8):1330–49. [DOI] [PubMed] [Google Scholar]
145.Cho AN, Jin Y, An Y, Kim J, Choi YS, Lee JS, et al. Microfluidic device with brain extracellular matrix promotes structural and functional maturation of human brain organoids. Nat Commun. 2021;12(1):4730. [DOI] [PMC free article] [PubMed] [Google Scholar]
146.Simsa R, Rothenbücher T, Gürbüz H, Ghosheh N, Emneus J, Jenndahl L, et al. Brain organoid formation on decellularized Porcine brain ECM hydrogels. PLoS ONE. 2021;16(1):e0245685. [DOI] [PMC free article] [PubMed] [Google Scholar]
147.Shirahama H, Lee BH, Tan LP, Cho NJ. Precise tuning of facile One-Pot gelatin methacryloyl (GelMA) synthesis. Sci Rep. 2016;6:31036. [DOI] [PMC free article] [PubMed] [Google Scholar]
148.Heinrich MA, Bansal R, Lammers T, Zhang YS, Michel Schiffelers R, Prakash J. 3D-Bioprinted Mini-Brain: A glioblastoma model to study cellular interactions and therapeutics. Adv Mater Deerfield Beach Fla. 2019;31(14):e1806590. [DOI] [PubMed] [Google Scholar]
149.Faulkner-Jones A, Fyfe C, Cornelissen DJ, Gardner J, King J, Courtney A, et al. Bioprinting of human pluripotent stem cells and their directed differentiation into hepatocyte-like cells for the generation of mini-livers in 3D. Biofabrication. 2015;7(4):044102. [DOI] [PubMed] [Google Scholar]
150.Zhu Y, Wang L, Yu H, Yin F, Wang Y, Liu H, et al. In situ generation of human brain organoids on a micropillar array. Lab Chip. 2017;17(17):2941–50. [DOI] [PubMed] [Google Scholar]
151.Scuderi S, Kang TY, Jourdon A, Nelson A, Yang L, Wu F, et al. Specification of human brain regions with orthogonal gradients of WNT and SHH in organoids reveals patterning variations across cell lines. Cell Stem Cell. 2025;32(6):970–e98911. [DOI] [PMC free article] [PubMed] [Google Scholar]
152.Brownjohn PW, Smith J, Solanki R, Lohmann E, Houlden H, Hardy J, et al. Functional studies of missense TREM2 mutations in human stem Cell-Derived microglia. Stem Cell Rep. 2018;10(4):1294–307. [DOI] [PMC free article] [PubMed] [Google Scholar]
153.Xu R, Boreland AJ, Li X, Erickson C, Jin M, Atkins C, et al. Developing human pluripotent stem cell-based cerebral organoids with a controllable microglia ratio for modeling brain development and pathology. Stem Cell Rep. 2021;16(8):1923–37. [DOI] [PMC free article] [PubMed] [Google Scholar]
154.Shen Q, Goderie SK, Jin L, Karanth N, Sun Y, Abramova N, et al. Endothelial cells stimulate self-renewal and expand neurogenesis of neural stem cells. Science. 2004;304(5675):1338–40. [DOI] [PubMed] [Google Scholar]
155.Yin X, Mead BE, Safaee H, Langer R, Karp JM, Levy O. Eng Stem Cell Organoids Cell Stem Cell. 2016;18(1):25–38. [DOI] [PMC free article] [PubMed] [Google Scholar]
156.Bhatia SN, Ingber DE. Microfluidic organs-on-chips. Nat Biotechnol. 2014;32(8):760–72. [DOI] [PubMed] [Google Scholar]
157.Huh D, Matthews BD, Mammoto A, Montoya-Zavala M, Hsin HY, Ingber DE. Reconstituting organ-level lung functions on a chip. Science. 2010;328(5986):1662–8. [DOI] [PMC free article] [PubMed] [Google Scholar]
158.Qian X, Su Y, Adam CD, Deutschmann AU, Pather SR, Goldberg EM, et al. Sliced human cortical organoids for modeling distinct cortical layer formation. Cell Stem Cell. 2020;26(5):766–e7819. [DOI] [PMC free article] [PubMed] [Google Scholar]
159.Cakir B, Xiang Y, Tanaka Y, Kural MH, Parent M, Kang YJ, et al. Engineering of human brain organoids with a functional vascular-like system. Nat Methods. 2019;16(11):1169–75. [DOI] [PMC free article] [PubMed] [Google Scholar]
160.Wörsdörfer P, Dalda N, Kern A, Krüger S, Wagner N, Kwok CK, et al. Generation of complex human organoid models including vascular networks by incorporation of mesodermal progenitor cells. Sci Rep. 2019;9(1):15663. [DOI] [PMC free article] [PubMed] [Google Scholar]
161.Chalkiadaki K, Statoulla E, Zafeiri M, Voudouri G, Amvrosiadis T, Typou A, et al. GABA/Glutamate neuron differentiation imbalance and increased AKT/mTOR signaling in CNTNAP2–/– cerebral organoids. Biol Psychiatry Glob Open Sci. 2025;5(1):100413. [DOI] [PMC free article] [PubMed] [Google Scholar]
162.Daviaud N, Friedel RH, Zou H. Vascularization and engraftment of transplanted human cerebral organoids in mouse cortex. eNeuro. 2018;5(6):ENEURO0219–182018. [DOI] [PMC free article] [PubMed] [Google Scholar]
163.Revah O, Gore F, Kelley KW, Andersen J, Sakai N, Chen X, et al. Maturation and circuit integration of transplanted human cortical organoids. Nature. 2022;610(7931):319–26. [DOI] [PMC free article] [PubMed] [Google Scholar]
164.Wang Z, Wang SN, Xu TY, Hong C, Cheng MH, Zhu PX, et al. Cerebral organoids transplantation improves neurological motor function in rat brain injury. CNS Neurosci Ther. 2020;26(7):682–97. [DOI] [PMC free article] [PubMed] [Google Scholar]
165.Xiang Y, Tanaka Y, Patterson B, Kang YJ, Govindaiah G, Roselaar N, et al. Fusion of regionally specified hPSC-Derived organoids models human brain development and interneuron migration. Cell Stem Cell. 2017;21(3):383–e3987. [DOI] [PMC free article] [PubMed] [Google Scholar]
166.Andersen J, Revah O, Miura Y, Thom N, Amin ND, Kelley KW, et al. Generation of functional human 3D Cortico-Motor assembloids. Cell. 2020;183(7):1913–e192926. [DOI] [PMC free article] [PubMed] [Google Scholar]
167.Kshirsagar A, Mnatsakanyan H, Kulkarni S, Guo J, Cheng K, Ofria LD et al. Multi-Region Brain Organoids Integrating Cerebral, Mid-Hindbrain, and Endothelial Systems. Adv Sci. n/a(n/a):e03768. [DOI] [PMC free article] [PubMed]
168.Sauvageau M, Goff LA, Lodato S, Bonev B, Groff AF, Gerhardinger C, et al. Multiple knockout mouse models reveal LincRNAs are required for life and brain development. eLife. 2013;2:e01749. [DOI] [PMC free article] [PubMed] [Google Scholar]
169.Li Q, Cheng Z, Zhou L, Darmanis S, Neff NF, Okamoto J, et al. Developmental heterogeneity of microglia and brain myeloid cells revealed by deep Single-Cell RNA sequencing. Neuron. 2019;101(2):207–e22310. [DOI] [PMC free article] [PubMed] [Google Scholar]
170.Anderson DJ, Pauler FM, McKenna A, Shendure J, Hippenmeyer S, Horwitz MS. Simultaneous brain cell type and lineage determined by scRNA-seq reveals stereotyped cortical development. Cell Syst. 2022;13(6):438–e4535. [DOI] [PMC free article] [PubMed] [Google Scholar]
171.Bandler RC, Vitali I, Delgado RN, Ho MC, Dvoretskova E, Ibarra Molinas JS, et al. Single-cell delineation of lineage and genetic identity in the mouse brain. Nature. 2022;601(7893):404–9. [DOI] [PMC free article] [PubMed] [Google Scholar]
172.Tiklová K, Björklund ÅK, Lahti L, Fiorenzano A, Nolbrant S, Gillberg L, et al. Single-cell RNA sequencing reveals midbrain dopamine neuron diversity emerging during mouse brain development. Nat Commun. 2019;10(1):581. [DOI] [PMC free article] [PubMed] [Google Scholar]
173.Saunders A, Macosko EZ, Wysoker A, Goldman M, Krienen FM, de Rivera H, et al. Molecular diversity and specializations among the cells of the adult mouse brain. Cell. 2018;174(4):1015–e103016. [DOI] [PMC free article] [PubMed] [Google Scholar]
174.Liu J, Li K, Cai J, Zhang M, Zhang X, Xiong X, et al. Landscape and regulation of m6A and m6Am methylome across human and mouse tissues. Mol Cell. 2020;77(2):426–e4406. [DOI] [PubMed] [Google Scholar]
175.Li YE, Preissl S, Hou X, Zhang Z, Zhang K, Qiu Y, et al. An atlas of gene regulatory elements in adult mouse cerebrum. Nature. 2021;598(7879):129–36. [DOI] [PMC free article] [PubMed] [Google Scholar]
176.Zu S, Li YE, Wang K, Armand EJ, Mamde S, Amaral ML, et al. Single-cell analysis of chromatin accessibility in the adult mouse brain. Nature. 2023;624(7991):378–89. [DOI] [PMC free article] [PubMed] [Google Scholar]
177.Wang M, Zhang L, Novak SW, Yu J, Gallina IS, Xu LL, et al. Morphological diversification and functional maturation of human astrocytes in glia-enriched cortical organoid transplanted in mouse brain. Nat Biotechnol. 2025;43(1):52–62. [DOI] [PMC free article] [PubMed] [Google Scholar]
178.Hasselmann J, Coburn MA, England W, Figueroa Velez DX, Kiani Shabestari S, Tu CH, et al. Development of a chimeric model to study and manipulate human microglia in vivo. Neuron. 2019;103(6):1016–e103310. [DOI] [PMC free article] [PubMed] [Google Scholar]
179.Fattorelli N, Martinez-Muriana A, Wolfs L, Geric I, De Strooper B, Mancuso R. Stem-cell-derived human microglia transplanted into mouse brain to study human disease. Nat Protoc. 2021;16(2):1013–33. [DOI] [PubMed] [Google Scholar]
180.Xu R, Brawner AT, Li S, Liu JJ, Kim H, Xue H, et al. OLIG2 drives abnormal neurodevelopmental phenotypes in human iPSC-Based organoid and chimeric mouse models of down syndrome. Cell Stem Cell. 2019;24(6):908–e9268. [DOI] [PMC free article] [PubMed] [Google Scholar]
181.Mudge J, Miller NA, Khrebtukova I, Lindquist IE, May GD, Huntley JJ, et al. Genomic convergence analysis of schizophrenia: mRNA sequencing reveals altered synaptic vesicular transport in post-mortem cerebellum. PLoS ONE. 2008;3(11):e3625. [DOI] [PMC free article] [PubMed] [Google Scholar]
182.Yeo G, Holste D, Kreiman G, Burge CB. Variation in alternative splicing across human tissues. Genome Biol. 2004;5(10):R74. [DOI] [PMC free article] [PubMed] [Google Scholar]
183.Licatalosi DD, Darnell RB. Splicing regulation in neurologic disease. Neuron. 2006;52(1):93–101. [DOI] [PubMed] [Google Scholar]
184.Johnson MB, Kawasawa YI, Mason CE, Krsnik Z, Coppola G, Bogdanović D, et al. Functional and evolutionary insights into human brain development through global transcriptome analysis. Neuron. 2009;62(4):494–509. [DOI] [PMC free article] [PubMed] [Google Scholar]
185.Chen G, Yin K, Shi L, Fang Y, Qi Y, Li P, et al. Comparative analysis of human protein-coding and noncoding RNAs between brain and 10 mixed cell lines by RNA-Seq. PLoS ONE. 2011;6(11):e28318. [DOI] [PMC free article] [PubMed] [Google Scholar]
186.Patel AP, Tirosh I, Trombetta JJ, Shalek AK, Gillespie SM, Wakimoto H, et al. Single-cell RNA-seq highlights intratumoral heterogeneity in primary glioblastoma. Science. 2014;344(6190):1396–401. [DOI] [PMC free article] [PubMed] [Google Scholar]
187.Pollen AA, Nowakowski TJ, Shuga J, Wang X, Leyrat AA, Lui JH, et al. Low-coverage single-cell mRNA sequencing reveals cellular heterogeneity and activated signaling pathways in developing cerebral cortex. Nat Biotechnol. 2014;32(10):1053–8. [DOI] [PMC free article] [PubMed] [Google Scholar]
188.Darmanis S, Sloan SA, Zhang Y, Enge M, Caneda C, Shuer LM, et al. A survey of human brain transcriptome diversity at the single cell level. Proc Natl Acad Sci U S A. 2015;112(23):7285–90. [DOI] [PMC free article] [PubMed] [Google Scholar]
189.Tasic B, Yao Z, Graybuck LT, Smith KA, Nguyen TN, Bertagnolli D, et al. Shared and distinct transcriptomic cell types across neocortical areas. Nature. 2018;563(7729):72–8. [DOI] [PMC free article] [PubMed] [Google Scholar]
190.Raj B, Wagner DE, McKenna A, Pandey S, Klein AM, Shendure J, et al. Simultaneous single-cell profiling of lineages and cell types in the vertebrate brain. Nat Biotechnol. 2018;36(5):442–50. [DOI] [PMC free article] [PubMed] [Google Scholar]
191.Zhong S, Zhang S, Fan X, Wu Q, Yan L, Dong J, et al. A single-cell RNA-seq survey of the developmental landscape of the human prefrontal cortex. Nature. 2018;555(7697):524–8. [DOI] [PubMed] [Google Scholar]
192.Zhong S, Ding W, Sun L, Lu Y, Dong H, Fan X, et al. Decoding the development of the human hippocampus. Nature. 2020;577(7791):531–6. [DOI] [PubMed] [Google Scholar]
193.Mathys H, Davila-Velderrain J, Peng Z, Gao F, Mohammadi S, Young JZ, et al. Single-cell transcriptomic analysis of alzheimer’s disease. Nature. 2019;570(7761):332–7. [DOI] [PMC free article] [PubMed] [Google Scholar]
194.Grubman A, Chew G, Ouyang JF, Sun G, Choo XY, McLean C, et al. A single-cell atlas of entorhinal cortex from individuals with alzheimer’s disease reveals cell-type-specific gene expression regulation. Nat Neurosci. 2019;22(12):2087–97. [DOI] [PubMed] [Google Scholar]
195.Zimmer B, Piao J, Ramnarine K, Tomishima MJ, Tabar V, Studer L. Derivation of diverse Hormone-Releasing pituitary cells from human pluripotent stem cells. Stem Cell Rep. 2016;6(6):858–72. [DOI] [PMC free article] [PubMed] [Google Scholar]
196.Eura N, Matsui TK, Luginbühl J, Matsubayashi M, Nanaura H, Shiota T, et al. Brainstem organoids from human pluripotent stem cells. Front Neurosci. 2020;14:538. [DOI] [PMC free article] [PubMed] [Google Scholar]
197.Smits LM, Magni S, Kinugawa K, Grzyb K, Luginbühl J, Sabate-Soler S, et al. Single-cell transcriptomics reveals multiple neuronal cell types in human midbrain-specific organoids. Cell Tissue Res. 2020;382(3):463–76. [DOI] [PMC free article] [PubMed] [Google Scholar]
198.Yoon SJ, Elahi LS, Pașca AM, Marton RM, Gordon A, Revah O, et al. Reliability of human cortical organoid generation. Nat Methods. 2019;16(1):75–8. [DOI] [PMC free article] [PubMed] [Google Scholar]
199.Tanaka Y, Cakir B, Xiang Y, Sullivan GJ, Park IH. Synthetic analyses of Single-Cell transcriptomes from multiple brain organoids and fetal brain. Cell Rep. 2020;30(6):1682–e16893. [DOI] [PMC free article] [PubMed] [Google Scholar]
200.He Z, Dony L, Fleck JS, Szałata A, Li KX, Slišković I, et al. An integrated transcriptomic cell atlas of human neural organoids. Nature. 2024;635(8039):690–8. [DOI] [PMC free article] [PubMed] [Google Scholar]
201.Everhard S, Tost J, El Abdalaoui H, Crinière E, Busato F, Marie Y, et al. Identification of regions correlating MGMT promoter methylation and gene expression in glioblastomas. Neuro-Oncol. 2009;11(4):348–56. [DOI] [PMC free article] [PubMed] [Google Scholar]
202.Kreth S, Thon N, Eigenbrod S, Lutz J, Ledderose C, Egensperger R, et al. O-methylguanine-DNA methyltransferase (MGMT) mRNA expression predicts outcome in malignant glioma independent of MGMT promoter methylation. PLoS ONE. 2011;6(2):e17156. [DOI] [PMC free article] [PubMed] [Google Scholar]
203.Lee DS, Luo C, Zhou J, Chandran S, Rivkin A, Bartlett A, et al. Simultaneous profiling of 3D genome structure and DNA methylation in single human cells. Nat Methods. 2019;16(10):999–1006. [DOI] [PMC free article] [PubMed] [Google Scholar]
204.Luo C, Rivkin A, Zhou J, Sandoval JP, Kurihara L, Lucero J, et al. Robust single-cell DNA methylome profiling with snmC-seq2. Nat Commun. 2018;9(1):3824. [DOI] [PMC free article] [PubMed] [Google Scholar]
205.Heffel MG, Zhou J, Zhang Y, Lee DS, Hou K, Pastor-Alonso O, et al. Temporally distinct 3D multi-omic dynamics in the developing human brain. Nature. 2024;635(8038):481–9. [DOI] [PMC free article] [PubMed] [Google Scholar]
206.Oh G, Ebrahimi S, Wang SC, Cortese R, Kaminsky ZA, Gottesman II, et al. Epigenetic assimilation in the aging human brain. Genome Biol. 2016;17:76. [DOI] [PMC free article] [PubMed] [Google Scholar]
207.Tian W, Zhou J, Bartlett A, Zeng Q, Liu H, Castanon RG, et al. Single-cell DNA methylation and 3D genome architecture in the human brain. Science. 2023;382(6667):eadf5357. [DOI] [PMC free article] [PubMed] [Google Scholar]
208.Treble-Barna A, Heinsberg LW, Stec Z, Breazeale S, Davis TS, Kesbhat AA, et al. Brain-derived neurotrophic factor (BDNF) epigenomic modifications and brain-related phenotypes in humans: A systematic review. Neurosci Biobehav Rev. 2023;147:105078. [DOI] [PMC free article] [PubMed] [Google Scholar]
209.Fullard JF, Giambartolomei C, Hauberg ME, Xu K, Voloudakis G, Shao Z, et al. Open chromatin profiling of human postmortem brain infers functional roles for non-coding schizophrenia loci. Hum Mol Genet. 2017;26(10):1942–51. [DOI] [PMC free article] [PubMed] [Google Scholar]
210.Fullard JF, Hauberg ME, Bendl J, Egervari G, Cirnaru MD, Reach SM, et al. An atlas of chromatin accessibility in the adult human brain. Genome Res. 2018;28(8):1243–52. [DOI] [PMC free article] [PubMed] [Google Scholar]
211.Herring CA, Simmons RK, Freytag S, Poppe D, Moffet JJD, Pflueger J, et al. Human prefrontal cortex gene regulatory dynamics from gestation to adulthood at single-cell resolution. Cell. 2022;185(23):4428–e444728. [DOI] [PubMed] [Google Scholar]
212.Morabito S, Miyoshi E, Michael N, Shahin S, Martini AC, Head E, et al. Single-nucleus chromatin accessibility and transcriptomic characterization of alzheimer’s disease. Nat Genet. 2021;53(8):1143–55. [DOI] [PMC free article] [PubMed] [Google Scholar]
213.Li YE, Preissl S, Miller M, Johnson ND, Wang Z, Jiao H, et al. A comparative atlas of single-cell chromatin accessibility in the human brain. Science. 2023;382(6667):eadf7044. [DOI] [PMC free article] [PubMed] [Google Scholar]
214.Dong P, Song L, Bendl J, Misir R, Shao Z, Edelstien J, et al. A multi-regional human brain atlas of chromatin accessibility and gene expression facilitates promoter-isoform resolution genetic fine-mapping. Nat Commun. 2024;15(1):10113. [DOI] [PMC free article] [PubMed] [Google Scholar]
215.Zhu K, Bendl J, Rahman S, Vicari JM, Coleman C, Clarence T, et al. Multi-omic profiling of the developing human cerebral cortex at the single-cell level. Sci Adv. 2023;9(41):eadg3754. [DOI] [PMC free article] [PubMed] [Google Scholar]
216.Bryois J, Garrett ME, Song L, Safi A, Giusti-Rodriguez P, Johnson GD, et al. Evaluation of chromatin accessibility in prefrontal cortex of individuals with schizophrenia. Nat Commun. 2018;9(1):3121. [DOI] [PMC free article] [PubMed] [Google Scholar]
217.Trevino AE, Sinnott-Armstrong N, Andersen J, Yoon SJ, Huber N, Pritchard JK, et al. Chromatin accessibility dynamics in a model of human forebrain development. Science. 2020;367(6476):eaay1645. [DOI] [PMC free article] [PubMed] [Google Scholar]
218.Ziffra RS, Kim CN, Ross JM, Wilfert A, Turner TN, Haeussler M, et al. Single-cell epigenomics reveals mechanisms of human cortical development. Nature. 2021;598(7879):205–13. [DOI] [PMC free article] [PubMed] [Google Scholar]
219.Lewis EMA, Kaushik K, Sandoval LA, Antony I, Dietmann S, Kroll KL. Epigenetic regulation during human cortical development: Seq-ing answers from the brain to the organoid. Neurochem Int. 2021;147:105039. [DOI] [PMC free article] [PubMed] [Google Scholar]
220.Shang Z, Chen D, Wang Q, Wang S, Deng Q, Wu L, et al. Single-cell RNA-seq reveals dynamic transcriptome profiling in human early neural differentiation. GigaScience. 2018;7(11):giy117. [DOI] [PMC free article] [PubMed] [Google Scholar]
221.Uzquiano A, Kedaigle AJ, Pigoni M, Paulsen B, Adiconis X, Kim K, et al. Proper acquisition of cell class identity in organoids allows definition of fate specification programs of the human cerebral cortex. Cell. 2022;185(20):3770–e378827. [DOI] [PMC free article] [PubMed] [Google Scholar]
222.Fleck JS, Jansen SMJ, Wollny D, Zenk F, Seimiya M, Jain A, et al. Inferring and perturbing cell fate regulomes in human brain organoids. Nature. 2023;621(7978):365–72. [DOI] [PMC free article] [PubMed] [Google Scholar]
223.Barral A, Déjardin J. The chromatin signatures of enhancers and their dynamic regulation. Nucl Austin Tex. 2023;14(1):2160551. [DOI] [PMC free article] [PubMed] [Google Scholar]
224.Koshi-Mano K, Mano T, Morishima M, Murayama S, Tamaoka A, Tsuji S, et al. Neuron-specific analysis of histone modifications with post-mortem brains. Sci Rep. 2020;10(1):3767. [DOI] [PMC free article] [PubMed] [Google Scholar]
225.Ziller MJ, Edri R, Yaffe Y, Donaghey J, Pop R, Mallard W, et al. Dissecting neural differentiation regulatory networks through epigenetic footprinting. Nature. 2015;518(7539):355–9. [DOI] [PMC free article] [PubMed] [Google Scholar]
226.Amiri A, Coppola G, Scuderi S, Wu F, Roychowdhury T, Liu F, et al. Transcriptome and epigenome landscape of human cortical development modeled in organoids. Science. 2018;362(6420):eaat6720. [DOI] [PMC free article] [PubMed] [Google Scholar]
227.Inoue F, Kreimer A, Ashuach T, Ahituv N, Yosef N. Identification and massively parallel characterization of regulatory elements driving neural induction. Cell Stem Cell. 2019;25(5):713–e72710. [DOI] [PMC free article] [PubMed] [Google Scholar]
228.Zenk F, Fleck JS, Jansen SMJ, Kashanian B, Eisinger B, Santel M, et al. Single-cell epigenomic reconstruction of developmental trajectories from pluripotency in human neural organoid systems. Nat Neurosci. 2024;27(7):1376–86. [DOI] [PMC free article] [PubMed] [Google Scholar]
229.Hess ME, Hess S, Meyer KD, Verhagen LAW, Koch L, Brönneke HS, et al. The fat mass and obesity associated gene (Fto) regulates activity of the dopaminergic midbrain circuitry. Nat Neurosci. 2013;16(8):1042–8. [DOI] [PubMed] [Google Scholar]
230.Li L, Zang L, Zhang F, Chen J, Shen H, Shu L, et al. Fat mass and obesity-associated (FTO) protein regulates adult neurogenesis. Hum Mol Genet. 2017;26(13):2398–411. [DOI] [PMC free article] [PubMed] [Google Scholar]
231.Walters BJ, Mercaldo V, Gillon CJ, Yip M, Neve RL, Boyce FM, et al. The role of the RNA demethylase FTO (Fat mass and Obesity-Associated) and mRNA methylation in hippocampal memory formation. Neuropsychopharmacol Off Publ Am Coll Neuropsychopharmacol. 2017;42(7):1502–10. [DOI] [PMC free article] [PubMed] [Google Scholar]
232.Du B, Zhang Y, Liang M, Du Z, Li H, Fan C, et al. N6-methyladenosine (m6A) modification and its clinical relevance in cognitive dysfunctions. Aging. 2021;13(16):20716–37. [DOI] [PMC free article] [PubMed] [Google Scholar]
233.Castro-Hernández R, Berulava T, Metelova M, Epple R, Peña Centeno T, Richter J, et al. Conserved reduction of m6A RNA modifications during aging and neurodegeneration is linked to changes in synaptic transcripts. Proc Natl Acad Sci U S A. 2023;120(9):e2204933120. [DOI] [PMC free article] [PubMed] [Google Scholar]
234.Edgar PF, Schonberger SJ, Dean B, Faull RL, Kydd R, Cooper GJ. A comparative proteome analysis of hippocampal tissue from schizophrenic and alzheimer’s disease individuals. Mol Psychiatry. 1999;4(2):173–8. [DOI] [PubMed] [Google Scholar]
235.Johnson ECB, Dammer EB, Duong DM, Ping L, Zhou M, Yin L, et al. Large-scale proteomic analysis of alzheimer’s disease brain and cerebrospinal fluid reveals early changes in energy metabolism associated with microglia and astrocyte activation. Nat Med. 2020;26(5):769–80. [DOI] [PMC free article] [PubMed] [Google Scholar]
236.Johnson ECB, Carter EK, Dammer EB, Duong DM, Gerasimov ES, Liu Y, et al. Large-scale deep multi-layer analysis of alzheimer’s disease brain reveals strong proteomic disease-related changes not observed at the RNA level. Nat Neurosci. 2022;25(2):213–25. [DOI] [PMC free article] [PubMed] [Google Scholar]
237.Graham SF, Chevallier OP, Roberts D, Hölscher C, Elliott CT, Green BD. Investigation of the human brain metabolome to identify potential markers for early diagnosis and therapeutic targets of alzheimer’s disease. Anal Chem. 2013;85(3):1803–11. [DOI] [PubMed] [Google Scholar]
238.Wang Y, Zhou L, Wang N, Qiu B, Yao D, Yu J, et al. Comprehensive characterization of metabolic consumption and production by the human brain. Neuron. 2025;113(11):1708–e17225. [DOI] [PubMed] [Google Scholar]
239.Dezonne RS, Sartore RC, Nascimento JM, Saia-Cereda VM, Romão LF, Alves-Leon SV, et al. Derivation of functional human astrocytes from cerebral organoids. Sci Rep. 2017;7:45091. [DOI] [PMC free article] [PubMed] [Google Scholar]
240.Karlinski Zur M, Bhattacharya B, Solomonov I, Ben Dror S, Savidor A, Levin Y, et al. Altered extracellular matrix structure and elevated stiffness in a brain organoid model for disease. Nat Commun. 2025;16(1):4094. [DOI] [PMC free article] [PubMed] [Google Scholar]
241.Chen C, Lee S, Zyner KG, Fernando M, Nemeruck V, Wong E, et al. Trans-omic profiling uncovers molecular controls of early human cerebral organoid formation. Cell Rep. 2024;43(5):114219. [DOI] [PubMed] [Google Scholar]
242.Pamies D, Block K, Lau P, Gribaldo L, Pardo CA, Barreras P, et al. Rotenone exerts developmental neurotoxicity in a human brain spheroid model. Toxicol Appl Pharmacol. 2018;354:101–14. [DOI] [PMC free article] [PubMed] [Google Scholar]
243.Guy B, Zhang JS, Duncan LH, Johnston RJ. Human neural organoids: models for developmental neurobiology and disease. Dev Biol. 2021;478:102–21. [DOI] [PMC free article] [PubMed] [Google Scholar]
244.Qian X, Nguyen HN, Jacob F, Song H, Ming GL. Using brain organoids to understand Zika virus-induced microcephaly. Dev Camb Engl. 2017;144(6):952–7. [DOI] [PMC free article] [PubMed] [Google Scholar]
245.Smits LM, Reinhardt L, Reinhardt P, Glatza M, Monzel AS, Stanslowsky N, et al. Modeling parkinson’s disease in midbrain-like organoids. NPJ Park Dis. 2019;5:5. [DOI] [PMC free article] [PubMed] [Google Scholar]
246.Ramani A, Pasquini G, Gerkau NJ, Jadhav V, Vinchure OS, Altinisik N, et al. Reliability of high-quantity human brain organoids for modeling microcephaly, glioma invasion and drug screening. Nat Commun. 2024;15(1):10703. [DOI] [PMC free article] [PubMed] [Google Scholar]
247.Struzyna LA, Watt ML. The emerging role of neuronal organoid models in drug discovery: potential applications and hurdles to implementation. Mol Pharmacol. 2021;99(4):256–65. [DOI] [PubMed] [Google Scholar]
248.McMahon AP, Bradley A. The Wnt-1 (int-1) proto-oncogene is required for development of a large region of the mouse brain. Cell. 1990;62(6):1073–85. [DOI] [PubMed] [Google Scholar]
249.Chiaradia I, Lancaster MA. Brain organoids for the study of human neurobiology at the interface of in vitro and in vivo. Nat Neurosci. 2020;23(12):1496–508. [DOI] [PubMed] [Google Scholar]
250.Onesto MM, Kim JI, Pasca SP. Assembloid models of cell-cell interaction to study tissue and disease biology. Cell Stem Cell. 2024;31(11):1563–73. [DOI] [PMC free article] [PubMed] [Google Scholar]
251.Nityanandam A, Patton MH, Bayazitov IT, Newman KD, Thomas KT, Zakharenko SS. Protocol for generating human assembloids to investigate thalamocortical and corticothalamic synaptic transmission and plasticity. STAR Protoc. 2025;6(1):103630. [DOI] [PMC free article] [PubMed] [Google Scholar]
252.Martins-Costa C, Wiegers A, Pham VA, Sidhaye J, Doleschall B, Novatchkova M, et al. ARID1B controls transcriptional programs of axon projection in an organoid model of the human corpus callosum. Cell Stem Cell. 2024;31(6):866–e88514. [DOI] [PubMed] [Google Scholar]
253.Marton RM, Miura Y, Sloan SA, Li Q, Revah O, Levy RJ, et al. Differentiation and maturation of oligodendrocytes in human three-dimensional neural cultures. Nat Neurosci. 2019;22(3):484–91. [DOI] [PMC free article] [PubMed] [Google Scholar]
254.Nambot S, Faivre L, Mirzaa G, Thevenon J, Bruel AL, Mosca-Boidron AL, et al. De Novo TBR1 variants cause a neurocognitive phenotype with ID and autistic traits: report of 25 new individuals and review of the literature. Eur J Hum Genet EJHG. 2020;28(6):770–82. [DOI] [PMC free article] [PubMed] [Google Scholar]
255.Dhaliwal N, Choi WWY, Muffat J, Li Y. Modeling PTEN overexpression-induced microcephaly in human brain organoids. Mol Brain. 2021;14(1):131. [DOI] [PMC free article] [PubMed] [Google Scholar]
256.Pigoni M, Uzquiano A, Paulsen B, Kedaigle AJ, Yang SM, Symvoulidis P, et al. Cell-type specific defects in PTEN-mutant cortical organoids converge on abnormal circuit activity. Hum Mol Genet. 2023;32(18):2773–86. [DOI] [PMC free article] [PubMed] [Google Scholar]
257.Cederlund M. Microcephaly in preschool children with autism spectrum disorder. Res Autism Spectr Disord. 2021;88:101845. [Google Scholar]
258.Paulsen B, Velasco S, Kedaigle AJ, Pigoni M, Quadrato G, Deo AJ, et al. Autism genes converge on asynchronous development of shared neuron classes. Nature. 2022;602(7896):268–73. [DOI] [PMC free article] [PubMed] [Google Scholar]
259.Villa CE, Cheroni C, Dotter CP, López-Tóbon A, Oliveira B, Sacco R, et al. CHD8 haploinsufficiency links autism to transient alterations in excitatory and inhibitory trajectories. Cell Rep. 2022;39(1):110615. [DOI] [PubMed] [Google Scholar]
260.Gomes AR, Fernandes TG, Vaz SH, Silva TP, Bekman EP, Xapelli S, et al. Modeling Rett syndrome with human Patient-Specific forebrain organoids. Front Cell Dev Biol. 2020;8:610427. [DOI] [PMC free article] [PubMed] [Google Scholar]
261.Zhang BZ, Chu H, Han S, Shuai H, Deng J, Hu Y et al. fan,. SARS-CoV-2 infects human neural progenitor cells and brain organoids. Cell Res. 2020;30(10):928–31. [DOI] [PMC free article] [PubMed]
262.Ramani A, Müller L, Ostermann PN, Gabriel E, Abida-Islam P, Müller‐Schiffmann A, et al. SARS ‐CoV‐2 targets neurons of 3D human brain organoids. EMBO J. 2020;39(20):e106230. [DOI] [PMC free article] [PubMed] [Google Scholar]
263.Samarasinghe RA, Miranda OA, Buth JE, Mitchell S, Ferando I, Watanabe M, et al. Identification of neural oscillations and epileptiform changes in human brain organoids. Nat Neurosci. 2021;24(10):1488–500. [DOI] [PMC free article] [PubMed] [Google Scholar]
264.Marchetto MC, Belinson H, Tian Y, Freitas BC, Fu C, Vadodaria K, et al. Altered proliferation and networks in neural cells derived from idiopathic autistic individuals. Mol Psychiatry. 2017;22(6):820–35. [DOI] [PMC free article] [PubMed] [Google Scholar]
265.Pagliaro A, Artegiani B, Hendriks D. Emerging approaches to enhance human brain organoid physiology. Trends Cell Biol. 2025;35(6):483–99. [DOI] [PubMed] [Google Scholar]
266.Kang SC, Sarn NB, Venegas J, Tan Z, Hitomi M, Eng C. Germline PTEN genotype-dependent phenotypic divergence during the early neural developmental process of forebrain organoids. Mol Psychiatry. 2024;29(6):1767–81. [DOI] [PubMed] [Google Scholar]
267.Dhaliwal NK, Weng OY, Dong X, Bhattacharya A, Ahmed M, Nishimura H, et al. Synergistic hyperactivation of both mTORC1 and mTORC2 underlies the neural abnormalities of PTEN-deficient human neurons and cortical organoids. Cell Rep. 2024;43(5):114173. [DOI] [PubMed] [Google Scholar]
268.Xu YJ, Liu PP, Yan ZZ, Mi TW, Wang YY, Li Q, et al. KW-2449 and VPA exert therapeutic effects on human neurons and cerebral organoids derived from MECP2-null hESCs. Stem Cell Res Ther. 2022;13(1):534. [DOI] [PMC free article] [PubMed] [Google Scholar]
269.Lin YT, Seo J, Gao F, Feldman HM, Wen HL, Penney J, et al. APOE4 causes widespread molecular and cellular alterations associated with alzheimer’s disease phenotypes in human iPSC-Derived brain cell types. Neuron. 2018;98(6):1141–e11547. [DOI] [PMC free article] [PubMed] [Google Scholar]
270.Raj N, McEachin ZT, Harousseau W, Zhou Y, Zhang F, Merritt-Garza ME, et al. Cell-type-specific profiling of human cellular models of fragile X syndrome reveal PI3K-dependent defects in translation and neurogenesis. Cell Rep. 2021;35(2):108991. [DOI] [PMC free article] [PubMed] [Google Scholar]
271.Dang J, Tiwari SK, Lichinchi G, Qin Y, Patil VS, Eroshkin AM, et al. Zika virus depletes neural progenitors in human cerebral organoids through activation of the innate immune receptor TLR3. Cell Stem Cell. 2016;19(2):258–65. [DOI] [PMC free article] [PubMed] [Google Scholar]
272.Sison SL, O’Brien BS, Johnson AJ, Seminary ER, Terhune SS, Ebert AD. Human cytomegalovirus disruption of calcium signaling in neural progenitor cells and organoids. J Virol. 2019;93(17):e00954–19. [DOI] [PMC free article] [PubMed] [Google Scholar]
273.Sun G, Chiuppesi F, Chen X, Wang C, Tian E, Nguyen J, et al. Modeling human Cytomegalovirus-Induced microcephaly in human iPSC-Derived brain organoids. Cell Rep Med. 2020;1(1):100002. [DOI] [PMC free article] [PubMed] [Google Scholar]
274.Zheng Y, Zhang F, Xu S, Wu L. Advances in neural organoid systems and their application in neurotoxicity testing of environmental chemicals. Genes Environ Off J Jpn Environ Mutagen Soc. 2021;43(1):39. [DOI] [PMC free article] [PubMed] [Google Scholar]
275.Park JC, Jang SY, Lee D, Lee J, Kang U, Chang H, et al. A logical network-based drug-screening platform for alzheimer’s disease representing pathological features of human brain organoids. Nat Commun. 2021;12(1):280. [DOI] [PMC free article] [PubMed] [Google Scholar]
276.Eze UC, Bhaduri A, Haeussler M, Nowakowski TJ, Kriegstein AR. Single-cell atlas of early human brain development highlights heterogeneity of human neuroepithelial cells and early radial glia. Nat Neurosci. 2021;24(4):584–94. [DOI] [PMC free article] [PubMed] [Google Scholar]
277.Brandenberg N, Hoehnel S, Kuttler F, Homicsko K, Ceroni C, Ringel T, et al. High-throughput automated organoid culture via stem-cell aggregation in microcavity arrays. Nat Biomed Eng. 2020;4(9):863–74. [DOI] [PubMed] [Google Scholar]
278.Hofer M, Lutolf MP. Engineering organoids. Nat Rev Mater. 2021;6(5):402–20. [DOI] [PMC free article] [PubMed] [Google Scholar]
279.Renner H, Grabos M, Becker KJ, Kagermeier TE, Wu J, Otto M, et al. A fully automated high-throughput workflow for 3D-based chemical screening in human midbrain organoids. eLife. 2020;9:e52904. [DOI] [PMC free article] [PubMed] [Google Scholar]
280.Zivko C, Sagar R, Xydia A, Lopez-Montes A, Mintzer J, Rosenberg PB, et al. iPSC-derived hindbrain organoids to evaluate Escitalopram oxalate treatment responses targeting neuropsychiatric symptoms in alzheimer’s disease. Mol Psychiatry. 2024;29(11):3644–52. [DOI] [PMC free article] [PubMed] [Google Scholar]
281.Gomez-Giro G, Frangenberg D, Vega D, Zagare A, Barmpa K, Antony PMA, et al. α‐Synuclein pathology spreads in a Midbrain–Hindbrain assembloid model. Adv Sci. 2025;12(20):2409040. [DOI] [PMC free article] [PubMed] [Google Scholar]
282.Kshirsagar A, Mnatsakanyan H, Kulkarni S, Guo J, Cheng K, Ofria LD, et al. Multi-Region brain organoids integrating Cerebral, Mid‐Hindbrain, and endothelial systems. Adv Sci. 2025;12(33):e03768. [DOI] [PMC free article] [PubMed] [Google Scholar]
283.Yuan F, Fang KH, Hong Y, Xu SB, Xu M, Pan Y, et al. LHX6 is essential for the migration of human pluripotent stem cell-derived GABAergic interneurons. Protein Cell. 2020;11(4):286–91. [DOI] [PMC free article] [PubMed] [Google Scholar]
284.Bertucci T, Bowles KR, Lotz S, Qi L, Stevens K, Goderie SK et al. Improved protocol for reproducible human cortical organoids reveals early alterations in metabolism with MAPT mutations. BioRxiv Prepr Serv Biol. 2023;2023.07.11.548571.
285.Srikanth P, Lagomarsino VN, Muratore CR, Ryu SC, He A, Taylor WM, et al. Shared effects of DISC1 disruption and elevated WNT signaling in human cerebral organoids. Transl Psychiatry. 2018;8(1):77. [DOI] [PMC free article] [PubMed] [Google Scholar]
286.Wang Y, Chiola S, Yang G, Russell C, Armstrong CJ, Wu Y, et al. Modeling human telencephalic development and autism-associated SHANK3 deficiency using organoids generated from single neural rosettes. Nat Commun. 2022;13(1):5688. [DOI] [PMC free article] [PubMed] [Google Scholar]
287.Szu J, Wojcinski A, Jiang P, Kesari S. Impact of the Olig family on neurodevelopmental disorders. Front Neurosci. 2021;15:659601. [DOI] [PMC free article] [PubMed] [Google Scholar]
288.Vasan L, Chinchalongporn V, Saleh F, Zinyk D, Ke C, Suresh H, et al. Examining the NEUROG2 lineage and associated gene expression in human cortical organoids. Dev Camb Engl. 2025;152(2):dev202703. [DOI] [PMC free article] [PubMed] [Google Scholar]
289.van Essen MJ, Apsley EJ, Riepsaame J, Xu R, Northcott PA, Cowley SA, et al. PTCH1-mutant human cerebellar organoids exhibit altered neural development and recapitulate early Medulloblastoma tumorigenesis. Dis Model Mech. 2024;17(2):dmm050323. [DOI] [PMC free article] [PubMed] [Google Scholar]
290.Fischer J, Fernández Ortuño E, Marsoner F, Artioli A, Peters J, Namba T, et al. Human-specific ARHGAP11B ensures human-like basal progenitor levels in hominid cerebral organoids. EMBO Rep. 2022;23(11):e54728. [DOI] [PMC free article] [PubMed] [Google Scholar]
291.Fiddes IT, Lodewijk GA, Mooring M, Bosworth CM, Ewing AD, Mantalas GL, et al. Human-Specific NOTCH2NL genes affect Notch signaling and cortical neurogenesis. Cell. 2018;173(6):1356–e136922. [DOI] [PMC free article] [PubMed] [Google Scholar]
292.López-Tobón A, Villa CE, Cheroni C, Trattaro S, Caporale N, Conforti P, et al. Human cortical organoids expose a differential function of GSK3 on cortical neurogenesis. Stem Cell Rep. 2019;13(5):847–61. [DOI] [PMC free article] [PubMed] [Google Scholar]
293.Seeler S, Andersen MS, Sztanka-Toth T, Rybiczka-Tešulov M, van den Munkhof MH, Chang CC, et al. A circular RNA expressed from the FAT3 locus regulates neural development. Mol Neurobiol. 2023;60(6):3239–60. [DOI] [PMC free article] [PubMed] [Google Scholar]
294.Liu J, Mosti F, Zhao HT, Lollis D, Sotelo-Fonseca JE, Escobar-Tomlienovich CF, et al. A human-specific enhancer fine-tunes radial glia potency and corticogenesis. Nature. 2025;643(8074):1321–32. [DOI] [PMC free article] [PubMed] [Google Scholar]
295.Kang Y, Zhou Y, Li Y, Han Y, Xu J, Niu W, et al. A human forebrain organoid model of fragile X syndrome exhibits altered neurogenesis and highlights new treatment strategies. Nat Neurosci. 2021;24(10):1377–91. [DOI] [PMC free article] [PubMed] [Google Scholar]
296.Urresti J, Zhang P, Moran-Losada P, Yu NK, Negraes PD, Trujillo CA, et al. Cortical organoids model early brain development disrupted by 16p11.2 copy number variants in autism. Mol Psychiatry. 2021;26(12):7560–80. [DOI] [PMC free article] [PubMed] [Google Scholar]
297.Jourdon A, Wu F, Mariani J, Capauto D, Norton S, Tomasini L, et al. Modeling idiopathic autism in forebrain organoids reveals an imbalance of excitatory cortical neuron subtypes during early neurogenesis. Nat Neurosci. 2023;26(9):1505–15. [DOI] [PMC free article] [PubMed] [Google Scholar]
298.de Jong JO, Llapashtica C, Genestine M, Strauss K, Provenzano F, Sun Y, et al. Cortical overgrowth in a preclinical forebrain organoid model of CNTNAP2-associated autism spectrum disorder. Nat Commun. 2021;12(1):4087. [DOI] [PMC free article] [PubMed] [Google Scholar]
299.Li C, Fleck JS, Martins-Costa C, Burkard TR, Themann J, Stuempflen M, et al. Single-cell brain organoid screening identifies developmental defects in autism. Nature. 2023;621(7978):373–80. [DOI] [PMC free article] [PubMed] [Google Scholar]
300.Birtele M, Del Dosso A, Xu T, Nguyen T, Wilkinson B, Hosseini N, et al. Non-synaptic function of the autism spectrum disorder-associated gene SYNGAP1 in cortical neurogenesis. Nat Neurosci. 2023;26(12):2090–103. [DOI] [PMC free article] [PubMed] [Google Scholar]
301.Discovery of. A non-canonical function of SYNGAP1 at early stages of human cortical neurogenesis. Nat Neurosci. 2023;26(12):2050–1. [DOI] [PubMed] [Google Scholar]
302.Zhang W, Yang SL, Yang M, Herrlinger S, Shao Q, Collar JL, et al. Modeling microcephaly with cerebral organoids reveals a WDR62-CEP170-KIF2A pathway promoting cilium disassembly in neural progenitors. Nat Commun. 2019;10(1):2612. [DOI] [PMC free article] [PubMed] [Google Scholar]
303.Omer Javed A, Li Y, Muffat J, Su KC, Cohen MA, Lungjangwa T, et al. Microcephaly modeling of kinetochore mutation reveals a Brain-Specific phenotype. Cell Rep. 2018;25(2):368–e3825. [DOI] [PMC free article] [PubMed] [Google Scholar]
304.Fair SR, Schwind W, Julian DL, Biel A, Guo G, Rutherford R, et al. Cerebral organoids containing an AUTS2 missense variant model microcephaly. Brain J Neurol. 2023;146(1):387–404. [DOI] [PMC free article] [PubMed] [Google Scholar]
305.Li R, Sun L, Fang A, Li P, Wu Q, Wang X. Recapitulating cortical development with organoid culture in vitro and modeling abnormal spindle-like (ASPM related primary) microcephaly disease. Protein Cell. 2017;8(11):823–33. [DOI] [PMC free article] [PubMed] [Google Scholar]
306.Wang L, Li Z, Sievert D, Smith DEC, Mendes MI, Chen DY, et al. Loss of NARS1 impairs progenitor proliferation in cortical brain organoids and leads to microcephaly. Nat Commun. 2020;11(1):4038. [DOI] [PMC free article] [PubMed] [Google Scholar]
307.Esk C, Lindenhofer D, Haendeler S, Wester RA, Pflug F, Schroeder B, et al. A human tissue screen identifies a regulator of ER secretion as a brain-size determinant. Science. 2020;370(6519):935–41. [DOI] [PubMed] [Google Scholar]
308.Dang LT, Vaid S, Lin G, Swaminathan P, Safran J, Loughman A, et al. STRADA-mutant human cortical organoids model megalencephaly and exhibit delayed neuronal differentiation. Dev Neurobiol. 2021;81(5):696–709. [DOI] [PMC free article] [PubMed] [Google Scholar]
309.Zhang W, Ma L, Yang M, Shao Q, Xu J, Lu Z, et al. Cerebral organoid and mouse models reveal a RAB39b-PI3K-mTOR pathway-dependent dysregulation of cortical development leading to macrocephaly/autism phenotypes. Genes Dev. 2020;34(7–8):580–97. [DOI] [PMC free article] [PubMed] [Google Scholar]
310.Xu J, Kong Y, Wang N, Li H, Li Y, Liu Z, et al. Personalized human Astrocyte-Derived Region-Specific forebrain organoids recapitulate endogenous pathological features of focal cortical dysplasia. Adv Sci Weinh Baden-Wurtt Ger. 2025;12(8):e2409774. [DOI] [PMC free article] [PubMed] [Google Scholar]
311.Birey F, Li MY, Gordon A, Thete MV, Valencia AM, Revah O, et al. Dissecting the molecular basis of human interneuron migration in forebrain assembloids from timothy syndrome. Cell Stem Cell. 2022;29(2):248–e2647. [DOI] [PMC free article] [PubMed] [Google Scholar]
312.Trujillo CA, Adams JW, Negraes PD, Carromeu C, Tejwani L, Acab A, et al. Pharmacological reversal of synaptic and network pathology in human MECP2-KO neurons and cortical organoids. EMBO Mol Med. 2021;13(1):e12523. [DOI] [PMC free article] [PubMed] [Google Scholar]
313.Xiang Y, Tanaka Y, Patterson B, Hwang SM, Hysolli E, Cakir B, et al. Dysregulation of BRD4 function underlies the functional abnormalities of MeCP2 mutant neurons. Mol Cell. 2020;79(1):84–e989. [DOI] [PMC free article] [PubMed] [Google Scholar]
314.Yildirim M, Delepine C, Feldman D, Pham VA, Chou S, Ip J, et al. Label-free three-photon imaging of intact human cerebral organoids for tracking early events in brain development and deficits in Rett syndrome. eLife. 2022;11:e78079. [DOI] [PMC free article] [PubMed] [Google Scholar]
315.Mellios N, Feldman DA, Sheridan SD, Ip JPK, Kwok S, Amoah SK, et al. MeCP2-regulated MiRNAs control early human neurogenesis through differential effects on ERK and AKT signaling. Mol Psychiatry. 2018;23(4):1051–65. [DOI] [PMC free article] [PubMed] [Google Scholar]
316.Gonzalez C, Armijo E, Bravo-Alegria J, Becerra-Calixto A, Mays CE, Soto C. Modeling amyloid beta and Tau pathology in human cerebral organoids. Mol Psychiatry. 2018;23(12):2363–74. [DOI] [PMC free article] [PubMed] [Google Scholar]
317.Tang XY, Xu L, Wang J, Hong Y, Wang Y, Zhu Q, et al. DSCAM/PAK1 pathway suppression reverses neurogenesis deficits in iPSC-derived cerebral organoids from patients with down syndrome. J Clin Invest. 2021;131(12):e135763. [DOI] [PMC free article] [PubMed] [Google Scholar]
318.Zhang W, Zhang M, Xu Z, Yan H, Wang H, Jiang J, et al. Human forebrain organoid-based multi-omics analyses of PCCB as a schizophrenia associated gene linked to GABAergic pathways. Nat Commun. 2023;14(1):5176. [DOI] [PMC free article] [PubMed] [Google Scholar]
319.Notaras M, Lodhi A, Dündar F, Collier P, Sayles NM, Tilgner H, et al. Schizophrenia is defined by cell-specific neuropathology and multiple neurodevelopmental mechanisms in patient-derived cerebral organoids. Mol Psychiatry. 2022;27(3):1416–34. [DOI] [PMC free article] [PubMed] [Google Scholar]
320.Ye F, Kang E, Yu C, Qian X, Jacob F, Yu C, et al. DISC1 regulates neurogenesis via modulating kinetochore attachment of Ndel1/Nde1 during mitosis. Neuron. 2017;96(5):1041–e10545. [DOI] [PMC free article] [PubMed] [Google Scholar]
321.Kathuria A, Lopez-Lengowski K, Vater M, McPhie D, Cohen BM, Karmacharya R. Transcriptome analysis and functional characterization of cerebral organoids in bipolar disorder. Genome Med. 2020;12(1):34. [DOI] [PMC free article] [PubMed] [Google Scholar]
322.Yang G, Ullah HMA, Parker E, Gorsi B, Libowitz M, Maguire C, et al. Neurite outgrowth deficits caused by rare PLXNB1 mutation in pediatric bipolar disorder. Mol Psychiatry. 2023;28(6):2525–39. [DOI] [PubMed] [Google Scholar]
323.Osete JR, Akkouh IA, Ievglevskyi O, Vandenberghe M, de Assis DR, Ueland T, et al. Transcriptional and functional effects of lithium in bipolar disorder iPSC-derived cortical spheroids. Mol Psychiatry. 2023;28(7):3033–43. [DOI] [PMC free article] [PubMed] [Google Scholar]
324.Chen J, Hadi F, Wen X, Zhao W, Xu M, Xue S, et al. Transcriptional regulation by PHGDH drives amyloid pathology in alzheimer’s disease. Cell. 2025;188(13):3513–e352926. [DOI] [PMC free article] [PubMed] [Google Scholar]

Associated Data

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Data Availability Statement

Not applicable.

[CR1] 1.Eriksson PS, Perfilieva E, Björk-Eriksson T, Alborn AM, Nordborg C, Peterson DA, et al. Neurogenesis in the adult human hippocampus. Nat Med. 1998;4(11):1313–7. [DOI] [PubMed] [Google Scholar]

[CR2] 2.Moreno-Jiménez EP, Flor-García M, Terreros-Roncal J, Rábano A, Cafini F, Pallas-Bazarra N, et al. Adult hippocampal neurogenesis is abundant in neurologically healthy subjects and drops sharply in patients with alzheimer’s disease. Nat Med. 2019;25(4):554–60. [DOI] [PubMed] [Google Scholar]

[CR3] 3.Santarelli L, Saxe M, Gross C, Surget A, Battaglia F, Dulawa S, et al. Requirement of hippocampal neurogenesis for the behavioral effects of antidepressants. Science. 2003;301(5634):805–9. [DOI] [PubMed] [Google Scholar]

[CR4] 4.Sorrells SF, Paredes MF, Cebrian-Silla A, Sandoval K, Qi D, Kelley KW, et al. Human hippocampal neurogenesis drops sharply in children to undetectable levels in adults. Nature. 2018;555(7696):377–81. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR5] 5.Boldrini M, Fulmore CA, Tartt AN, Simeon LR, Pavlova I, Poposka V, et al. Hum Hippocampal Neurogenesis Persists Throughout Aging Cell Stem Cell. 2018;22(4):589–e5995. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR6] 6.Ming GL, Song H. Adult neurogenesis in the mammalian brain: significant answers and significant questions. Neuron. 2011;70(4):687–702. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR7] 7.Velasco S, Kedaigle AJ, Simmons SK, Nash A, Rocha M, Quadrato G, et al. Individual brain organoids reproducibly form cell diversity of the human cerebral cortex. Nature. 2019;570(7762):523–7. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR8] 8.Llorens-Bobadilla E, Zhao S, Baser A, Saiz-Castro G, Zwadlo K, Martin-Villalba A. Single-Cell transcriptomics reveals a population of dormant neural stem cells that become activated upon brain injury. Cell Stem Cell. 2015;17(3):329–40. [DOI] [PubMed] [Google Scholar]

[CR9] 9.Baur K, Abdullah Y, Mandl C, Hölzl-Wenig G, Shi Y, Edelkraut U, et al. A novel stem cell type at the basal side of the subventricular zone maintains adult neurogenesis. EMBO Rep. 2022;23(9):e54078. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR10] 10.Shen Q, Wang Y, Dimos JT, Fasano CA, Phoenix TN, Lemischka IR, et al. The timing of cortical neurogenesis is encoded within lineages of individual progenitor cells. Nat Neurosci. 2006;9(6):743–51. [DOI] [PubMed] [Google Scholar]

[CR11] 11.Tropepe V, Sibilia M, Ciruna BG, Rossant J, Wagner EF, van der Kooy D. Distinct neural stem cells proliferate in response to EGF and FGF in the developing mouse telencephalon. Dev Biol. 1999;208(1):166–88. [DOI] [PubMed] [Google Scholar]

[CR12] 12.Chazal G, Durbec P, Jankovski A, Rougon G, Cremer H. Consequences of neural cell adhesion molecule deficiency on cell migration in the rostral migratory stream of the mouse. J Neurosci Off J Soc Neurosci. 2000;20(4):1446–57. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR13] 13.Workman AD, Charvet CJ, Clancy B, Darlington RB, Finlay BL. Modeling transformations of neurodevelopmental sequences across mammalian species. J Neurosci. 2013;33(17):7368–83. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR14] 14.Hansen DV, Lui JH, Parker PRL, Kriegstein AR. Neurogenic radial glia in the outer subventricular zone of human neocortex. Nature. 2010;464(7288):554–61. [DOI] [PubMed] [Google Scholar]

[CR15] 15.Eiraku M, Takata N, Ishibashi H, Kawada M, Sakakura E, Okuda S, et al. Self-organizing optic-cup morphogenesis in three-dimensional culture. Nature. 2011;472(7341):51–6. [DOI] [PubMed] [Google Scholar]

[CR16] 16.Lancaster MA, Renner M, Martin CA, Wenzel D, Bicknell LS, Hurles ME, et al. Cerebral organoids model human brain development and microcephaly. Nature. 2013;501(7467):373–9. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR17] 17.Kadoshima T, Sakaguchi H, Nakano T, Soen M, Ando S, Eiraku M, et al. Self-organization of axial polarity, inside-out layer pattern, and species-specific progenitor dynamics in human ES cell-derived neocortex. Proc Natl Acad Sci U S A. 2013;110(50):20284–9. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR18] 18.Paşca AM, Sloan SA, Clarke LE, Tian Y, Makinson CD, Huber N, et al. Functional cortical neurons and astrocytes from human pluripotent stem cells in 3D culture. Nat Methods. 2015;12(7):671–8. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR19] 19.Mariani J, Coppola G, Zhang P, Abyzov A, Provini L, Tomasini L, et al. FOXG1-Dependent dysregulation of GABA/Glutamate neuron differentiation in autism spectrum disorders. Cell. 2015;162(2):375–90. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR20] 20.Xiang Y, Tanaka Y, Cakir B, Patterson B, Kim KY, Sun P, et al. hESC-Derived thalamic organoids form reciprocal projections when fused with cortical organoids. Cell Stem Cell. 2019;24(3):487–e4977. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR21] 21.Birey F, Andersen J, Makinson CD, Islam S, Wei W, Huber N, et al. Assembly of functionally integrated human forebrain spheroids. Nature. 2017;545(7652):54–9. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR22] 22.Qian X, Nguyen HN, Song MM, Hadiono C, Ogden SC, Hammack C, et al. Brain-Region-Specific organoids using Mini-bioreactors for modeling ZIKV exposure. Cell. 2016;165(5):1238–54. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR23] 23.Wang F, Hao S, Park K, Ahmady A, Zhou C. Label-free evaluation of mouse embryo quality using time-lapse bright field and optical coherence microscopy. Commun Biol. 2025;8(1):1–12. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR24] 24.Rivera-Pérez JA, Hadjantonakis AK. The dynamics of morphogenesis in the early mouse embryo. Cold Spring Harb Perspect Biol. 2015;7(11):a015867. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR25] 25.Aguilera-Castrejon A, Oldak B, Shani T, Ghanem N, Itzkovich C, Slomovich S, et al. Ex utero mouse embryogenesis from pre-gastrulation to late organogenesis. Nature. 2021;593(7857):119–24. [DOI] [PubMed] [Google Scholar]

[CR26] 26.Arnold SJ, Robertson EJ. Making a commitment: cell lineage allocation and axis patterning in the early mouse embryo. Nat Rev Mol Cell Biol. 2009;10(2):91–103. [DOI] [PubMed] [Google Scholar]

[CR27] 27.Colas JF, Schoenwolf GC. Towards a cellular and molecular Understanding of neurulation. Dev Dyn. 2001;221(2):117–45. [DOI] [PubMed] [Google Scholar]

[CR28] 28.Rubenstein JLR, Shimamura K, Martinez S, Puelles L. REGIONALIZATION OF THE PROSENCEPHALIC NEURAL PLATE. Annu Rev Neurosci. 1998;21(Volume 21, 1998):445–77. [DOI] [PubMed]

[CR29] 29.Greene NDE, Copp AJ. Development of the vertebrate central nervous system: formation of the neural tube. Prenat Diagn. 2009;29(4):303–11. [DOI] [PubMed] [Google Scholar]

[CR30] 30.Kaufman MH, Bard JBL. The anatomical basis of mouse development. Gulf Professional Publishing; 1999. p. 306.

[CR31] 31.Chen VS, Morrison JP, Southwell MF, Foley JF, Bolon B, Elmore SA. Histology atlas of the developing prenatal and postnatal mouse central nervous System, with emphasis on prenatal days E7.5 to E18.5. Toxicol Pathol. 2017;45(6):705–44. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR32] 32.Liu W, Lagutin O, Swindell E, Jamrich M, Oliver G. Neuroretina specification in mouse embryos requires Six3-mediated suppression of Wnt8b in the anterior neural plate. J Clin Invest. 2010;120(10):3568–77. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR33] 33.Wang J, Sinha T, Wynshaw-Boris A. Wnt signaling in mammalian development: lessons from mouse genetics. Cold Spring Harb Perspect Biol. 2012;4(5):a007963. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR34] 34.Gibbs HC, Chang-Gonzalez A, Hwang W, Yeh AT, Lekven AC. Midbrain-Hindbrain boundary morphogenesis: at the intersection of Wnt and Fgf signaling. Front Neuroanat. 2017;11:64. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR35] 35.Bedois AMH, Parker HJ, Krumlauf R. Retinoic acid signaling in vertebrate hindbrain segmentation: evolution and diversification. Diversity. 2021;13(8):398. [Google Scholar]

[CR36] 36.De Bakker BS, De Jong KH, Hagoort J, De Bree K, Besselink CT, De Kanter FEC, et al. An interactive three-dimensional digital atlas and quantitative database of human development. Science. 2016;354(6315):aag0053. [DOI] [PubMed] [Google Scholar]

[CR37] 37.Vetter R, Iber D. Precision of morphogen gradients in neural tube development. Nat Commun. 2022;13(1):1145. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR38] 38.Gupta S, Butler SJ. Getting in touch with your senses: mechanisms specifying sensory interneurons in the dorsal spinal cord. Wires Mech Dis. 2021;13(5):e1520. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR39] 39.Eto H, Kishi Y, Yakushiji-Kaminatsui N, Sugishita H, Utsunomiya S, Koseki H, et al. The polycomb group protein Ring1 regulates dorsoventral patterning of the mouse telencephalon. Nat Commun. 2020;11(1):5709. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR40] 40.Angevine JB Jr, Bodian D, Coulombre AJ, Edds MV Jr., Hamburger V, Jacobson M, et al. Embryonic vertebrate central nervous system: revised terminology. Anat Rec. 1970;166(2):257–61. [DOI] [PubMed] [Google Scholar]

[CR41] 41.Kriegstein A, Alvarez-Buylla A. The glial nature of embryonic and adult neural stem cells. Annu Rev Neurosci. 2009;32(32, 2009):149–84. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR42] 42.Koo B, Lee KH, Ming G, li, Yoon KJ, Song H. Setting the clock of neural progenitor cells during mammalian corticogenesis. Semin Cell Dev Biol. 2023;142:43–53. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR43] 43.Jiang X, Nardelli J. Cellular and molecular introduction to brain development. Neurobiol Dis. 2016;92:3–17. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR44] 44.Molyneaux BJ, Arlotta P, Menezes JRL, Macklis JD. Neuronal subtype specification in the cerebral cortex. Nat Rev Neurosci. 2007;8(6):427–37. [DOI] [PubMed] [Google Scholar]

[CR45] 45.Marín-Padilla M. Cajal-Retzius cells and the development of the neocortex. Trends Neurosci. 1998;21(2):64–71. [DOI] [PubMed] [Google Scholar]

[CR46] 46.Gorski JA, Talley T, Qiu M, Puelles L, Rubenstein JLR, Jones KR. Cortical excitatory neurons and glia, but not GABAergic neurons, are produced in the Emx1-expressing lineage. J Neurosci Off J Soc Neurosci. 2002;22(15):6309–14. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR47] 47.Ueno M, Nakamura Y, Li J, Gu Z, Niehaus J, Maezawa M, et al. Corticospinal circuits from the sensory and motor cortices differentially regulate skilled movements through distinct spinal interneurons. Cell Rep. 2018;23(5):1286–e13007. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR48] 48.Lavdas AA, Grigoriou M, Pachnis V, Parnavelas JG. The medial ganglionic eminence gives rise to a population of early neurons in the developing cerebral cortex. J Neurosci. 1999;19(18):7881–8. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR49] 49.Viollet C, Lepousez G, Loudes C, Videau C, Simon A, Epelbaum J. Somatostatinergic systems in brain: networks and functions. Mol Cell Endocrinol. 2008;286(1):75–87. [DOI] [PubMed] [Google Scholar]

[CR50] 50.Wang WZ, Hoerder-Suabedissen A, Oeschger FM, Bayatti N, Ip BK, Lindsay S, et al. Subplate in the developing cortex of mouse and human. J Anat. 2010;217(4):368–80. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR51] 51.Hoerder-Suabedissen A, Molnár Z. Development, evolution and pathology of neocortical subplate neurons. Nat Rev Neurosci. 2015;16(3):133–46. [DOI] [PubMed] [Google Scholar]

[CR52] 52.Stiles J, Jernigan TL. The basics of brain development. Neuropsychol Rev. 2010;20(4):327–48. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR53] 53.Jiang M, Yu D, Xie B, Huang H, Lu W, Qiu M, et al. WNT signaling suppresses oligodendrogenesis via Ngn2-dependent direct Inhibition of Olig2 expression. Mol Brain. 2020;13:155. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR54] 54.Tabata H, Nakajima K. Multipolar migration: the third mode of radial neuronal migration in the developing cerebral cortex. J Neurosci Off J Soc Neurosci. 2003;23(31):9996–10001. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR55] 55.Accogli A, Addour-Boudrahem N, Srour M. Neurogenesis, neuronal migration, and axon guidance. Handb Clin Neurol. 2020;173:25–42. [DOI] [PubMed] [Google Scholar]

[CR56] 56.Vivi E, Di Benedetto B. Brain stars take the lead during critical periods of early postnatal brain development: relevance of astrocytes in health and mental disorders. Mol Psychiatry. 2024;29(9):2821–33. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR57] 57.Lattke M, Guillemot F. Understanding astrocyte differentiation: clinical relevance, technical challenges, and new opportunities in the omics era. Wires Mech Dis. 2022;14(5):e1557. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR58] 58.Yabut OR, Pleasure SJ. Sonic Hedgehog signaling rises to the surface: emerging roles in neocortical development. Brain Plast. 2018;3(2):119–28. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR59] 59.Bocchi R, Thorwirth M, Simon-Ebert T, Koupourtidou C, Clavreul S, Kolf K, et al. Astrocyte heterogeneity reveals region-specific astrogenesis in the white matter. Nat Neurosci. 2025;28(3):457–69. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR60] 60.Kronman FN, Liwang JK, Betty R, Vanselow DJ, Wu YT, Tustison NJ, et al. Developmental mouse brain common coordinate framework. Nat Commun. 2024;15(1):9072. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR61] 61.Nadarajah B. Radial glia and somal translocation of radial neurons in the developing cerebral cortex. Glia. 2003;43(1):33–6. [DOI] [PubMed] [Google Scholar]

[CR62] 62.Luskin MB. Restricted proliferation and migration of postnatally generated neurons derived from the forebrain subventricular zone. Neuron. 1993;11(1):173–89. [DOI] [PubMed] [Google Scholar]

[CR63] 63.Kim JY, Paredes MF. Implications of extended inhibitory neuron development. Int J Mol Sci. 2021;22(10):5113. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR64] 64.Barber M, Pierani A. Tangential migration of glutamatergic neurons and cortical patterning during development: lessons from Cajal-Retzius cells. Dev Neurobiol. 2016;76(8):847–81. [DOI] [PubMed] [Google Scholar]

[CR65] 65.Foran DR, Peterson AC. Myelin acquisition in the central nervous system of the mouse revealed by an MBP-Lac Z transgene. J Neurosci Off J Soc Neurosci. 1992;12(12):4890–7. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR66] 66.Semple BD, Blomgren K, Gimlin K, Ferriero DM, Noble-Haeusslein LJ. Brain development in rodents and humans: identifying benchmarks of maturation and vulnerability to injury across species. Prog Neurobiol. 2013;0:1–16. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR67] 67.Waites CL, Craig AM, Garner CC. Mechanisms of vertebrate synaptogenesis. Annu Rev Neurosci. 2005;28:251–74. [DOI] [PubMed] [Google Scholar]

[CR68] 68.Li Y, Aimone JB, Xu X, Callaway EM, Gage FH. Development of GABAergic inputs controls the contribution of maturing neurons to the adult hippocampal network. Proc Natl Acad Sci U S A. 2012;109(11):4290–5. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR69] 69.Birnie MT, Baram TZ. Principles of emotional brain circuit maturation. Science. 2022;376(6597):1055–6. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR70] 70.Bond AM, Bhalala OG, Kessler JA. The dynamic role of bone morphogenetic proteins in neural stem cell fate and maturation. Dev Neurobiol. 2012;72(7):1068–84. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR71] 71.Atamian A, Birtele M, Hosseini N, Nguyen T, Seth A, Del Dosso A, et al. Human cerebellar organoids with functional purkinje cells. Cell Stem Cell. 2024;31(1):39–e516. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR72] 72.Xue X, Kim YS, Ponce-Arias AI, O’Laughlin R, Yan RZ, Kobayashi N, et al. A patterned human neural tube model using microfluidic gradients. Nature. 2024;628(8007):391–9. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR73] 73.Zhou Y, Song H, Ming G. li. Genetics of human brain development. Nat Rev Genet. 2024;25(1):26–45. [DOI] [PMC free article] [PubMed]

[CR74] 74.Fietz SA, Kelava I, Vogt J, Wilsch-Bräuninger M, Stenzel D, Fish JL, et al. OSVZ progenitors of human and ferret neocortex are epithelial-like and expand by integrin signaling. Nat Neurosci. 2010;13(6):690–9. [DOI] [PubMed] [Google Scholar]

[CR75] 75.Nowakowski TJ, Pollen AA, Sandoval-Espinosa C, Kriegstein AR. Transformation of the radial glia scaffold demarcates two stages of human cerebral cortex development. Neuron. 2016;91(6):1219–27. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR76] 76.Bilgic M, Wu Q, Suetsugu T, Shitamukai A, Tsunekawa Y, Shimogori T et al. Truncated radial glia as a common precursor in the late corticogenesis of gyrencephalic mammals. eLife 12:RP91406. [DOI] [PMC free article] [PubMed]

[CR77] 77.Yu D, Jain S, Wangzhou A, Zhu B, Shao W, Coley-O’Rourke EJ et al. Microglia regulate GABAergic neurogenesis in prenatal human brain through IGF1. Nature. 2025. [DOI] [PMC free article] [PubMed]

[CR78] 78.Taverna E, Götz M, Huttner WB. The cell biology of neurogenesis: toward an Understanding of the development and evolution of the neocortex. Annu Rev Cell Dev Biol. 2014;30:465–502. [DOI] [PubMed] [Google Scholar]

[CR79] 79.Jakovcevski I, Filipovic R, Mo Z, Rakic S, Zecevic N. Oligodendrocyte development and the onset of myelination in the human fetal brain. Front Neuroanat. [DOI] [PMC free article] [PubMed]

[CR80] 80.Frazel PW, Labib D, Fisher T, Brosh R, Pirjanian N, Marchildon A, et al. Longitudinal scRNA-seq analysis in mouse and human informs optimization of rapid mouse astrocyte differentiation protocols. Nat Neurosci. 2023;26(10):1726–38. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR81] 81.Marín O, Rubenstein JLR. Cell migration in the forebrain. Annu Rev Neurosci. 2003;26(26, 2003):441–83. [DOI] [PubMed] [Google Scholar]

[CR82] 82.Ayala R, Shu T, Tsai LH. Trekking across the brain: the journey of neuronal migration. Cell. 2007;128(1):29–43. [DOI] [PubMed] [Google Scholar]

[CR83] 83.Nadarajah B, Parnavelas JG. Modes of neuronal migration in the developing cerebral cortex. Nat Rev Neurosci. 2002;3(6):423–32. [DOI] [PubMed] [Google Scholar]

[CR84] 84.Taylor KR, Monje M. Neuron–oligodendroglial interactions in health and malignant disease. Nat Rev Neurosci. 2023;24(12):733–46. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR85] 85.McNamara NB, Munro DAD, Bestard-Cuche N, Uyeda A, Bogie JFJ, Hoffmann A, et al. Microglia regulate central nervous system Myelin growth and integrity. Nature. 2023;613(7942):120–9. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR86] 86.Schmidt ERE, Zhao HT, Park JM, Dipoppa M, Monsalve-Mercado MM, Dahan JB, et al. A human-specific modifier of cortical connectivity and circuit function. Nature. 2021;599(7886):640–4. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR87] 87.Azevedo FAC, Carvalho LRB, Grinberg LT, Farfel JM, Ferretti REL, Leite REP, et al. Equal numbers of neuronal and nonneuronal cells make the human brain an isometrically scaled-up primate brain. J Comp Neurol. 2009;513(5):532–41. [DOI] [PubMed] [Google Scholar]

[CR88] 88.Herculano-Houzel S. The remarkable, yet not extraordinary, human brain as a scaled-up primate brain and its associated cost. Proc Natl Acad Sci U S A. 2012;109(Suppl 1):10661–8. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR89] 89.Zarzor MS, Blumcke I, Budday S. Exploring the role of the outer subventricular zone during cortical folding through a physics-based model. eLife. 2023;12:e82925. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR90] 90.Prodromidou K, Matsas R. Evolving features of human cortical development and the emerging roles of non-coding RNAs in neural progenitor cell diversity and function. Cell Mol Life Sci CMLS. 2021;79(1):56. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR91] 91.Jacobson M, Rao MS, editors. Developmental neurobiology. 4th ed. New York: Kluwer Academic/Plenum; 2005. p. 424. [Google Scholar]

[CR92] 92.Fang R, Xia C, Close JL, Zhang M, He J, Huang Z, et al. Conservation and divergence of cortical cell organization in human and mouse revealed by MERFISH. Science. 2022;377(6601):56–62. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR93] 93.Luo X, Liu Y, Dang D, Hu T, Hou Y, Meng X, et al. 3D genome of macaque fetal brain reveals evolutionary innovations during primate corticogenesis. Cell. 2021;184(3):723–e74021. [DOI] [PubMed] [Google Scholar]

[CR94] 94.Zhong S, Wang M, Huang L, Chen Y, Ge Y, Zhang J, et al. Single-cell epigenomics and Spatiotemporal transcriptomics reveal human cerebellar development. Nat Commun. 2023;14(1):7613. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR95] 95.Terauchi A, Yee P, Johnson-Venkatesh EM, Seiglie MP, Kim L, Pitino JC, et al. The projection-specific signals that Establish functionally segregated dopaminergic synapses. Cell. 2023;186(18):3845–e386124. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR96] 96.Freeman MR. Specification and morphogenesis of astrocytes. Science. 2010;330(6005):774–8. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR97] 97.Ruiz-Jiménez JM, Santpere G. The impact of human accelerated regions on neuronal development. Trends Genet TIG. 2025;41(6):459–61. [DOI] [PubMed] [Google Scholar]

[CR98] 98.Eiraku M, Watanabe K, Matsuo-Takasaki M, Kawada M, Yonemura S, Matsumura M, et al. Self-Organized formation of polarized cortical tissues from ESCs and its active manipulation by extrinsic signals. Cell Stem Cell. 2008;3(5):519–32. [DOI] [PubMed] [Google Scholar]

[CR99] 99.Shiraishi A, Muguruma K, Sasai Y. Generation of thalamic neurons from mouse embryonic stem cells. Development. 2017;144(7):1211–20. [DOI] [PubMed] [Google Scholar]

[CR100] 100.Park J, Hsiung HA, Khven I, La Manno G, Lutolf MP. Self-organizing in vitro mouse neural tube organoids mimic embryonic development. Development. 2022;149(20):dev201052. [DOI] [PubMed] [Google Scholar]

[CR101] 101.Ciarpella F, Zamfir RG, Campanelli A, Pedrotti G, Di Chio M, Bottani E, et al. Generation of mouse hippocampal brain organoids from primary embryonic neural stem cells. STAR Protoc. 2023;4(3):102413. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR102] 102.Hodge RD, Bakken TE, Miller JA, Smith KA, Barkan ER, Graybuck LT, et al. Conserved cell types with divergent features in human versus mouse cortex. Nature. 2019;573(7772):61–8. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR103] 103.Lake BB, Ai R, Kaeser GE, Salathia NS, Yung YC, Liu R, et al. Neuronal subtypes and diversity revealed by single-nucleus RNA sequencing of the human brain. Science. 2016;352(6293):1586–90. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR104] 104.van den Heuvel MP, Sporns O. Rich-club organization of the human connectome. J Neurosci Off J Soc Neurosci. 2011;31(44):15775–86. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR105] 105.Miller JA, Ding SL, Sunkin SM, Smith KA, Ng L, Szafer A, et al. Transcriptional landscape of the prenatal human brain. Nature. 2014;508(7495):199–206. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR106] 106.Sousa AMM, Meyer KA, Santpere G, Gulden FO, Sestan N. Evolution of the human nervous system Function, Structure, and development. Cell. 2017;170(2):226–47. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR107] 107.Yu J, Vodyanik MA, Smuga-Otto K, Antosiewicz-Bourget J, Frane JL, Tian S, et al. Induced pluripotent stem cell lines derived from human somatic cells. Science. 2007;318(5858):1917–20. [DOI] [PubMed] [Google Scholar]

[CR108] 108.Stadtfeld M, Hochedlinger K. Induced pluripotency: history, mechanisms, and applications. Genes Dev. 2010;24(20):2239–63. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR109] 109.Reynolds BA, Tetzlaff W, Weiss S. A multipotent EGF-responsive striatal embryonic progenitor cell produces neurons and astrocytes. J Neurosci Off J Soc Neurosci. 1992;12(11):4565–74. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR110] 110.Zhang SC, Wernig M, Duncan ID, Brüstle O, Thomson JA. In vitro differentiation of transplantable neural precursors from human embryonic stem cells. Nat Biotechnol. 2001;19(12):1129–33. [DOI] [PubMed] [Google Scholar]

[CR111] 111.Sasai Y. Next-generation regenerative medicine: organogenesis from stem cells in 3D culture. Cell Stem Cell. 2013;12(5):520–30. [DOI] [PubMed] [Google Scholar]

[CR112] 112.Hu BY, Zhang SC. Directed differentiation of neural-stem cells and subtype-specific neurons from hESCs. Methods Mol Biol Clifton NJ. 2010;636:123–37. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR113] 113.Wu Y, Liu Y, Chesnut JD, Rao MS. Isolation of neural stem and precursor cells from rodent tissue. Methods Mol Biol Clifton NJ. 2008;438:39–53. [DOI] [PubMed] [Google Scholar]

[CR114] 114.Lancaster MA, Knoblich JA. Generation of cerebral organoids from human pluripotent stem cells. Nat Protoc. 2014;9(10):2329–40. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR115] 115.Quadrato G, Nguyen T, Macosko EZ, Sherwood JL, Min Yang S, Berger DR, et al. Cell diversity and network dynamics in photosensitive human brain organoids. Nature. 2017;545(7652):48–53. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR116] 116.Camp JG, Badsha F, Florio M, Kanton S, Gerber T, Wilsch-Bräuninger M, et al. Human cerebral organoids recapitulate gene expression programs of fetal neocortex development. Proc Natl Acad Sci U S A. 2015;112(51):15672–7. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR117] 117.Sun AX, Ng HH, Tan EK. Translational potential of human brain organoids. Ann Clin Transl Neurol. 2018;5(2):226–35. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR118] 118.Rigamonti A, Repetti GG, Sun C, Price FD, Reny DC, Rapino F, et al. Large-Scale production of mature neurons from human pluripotent stem cells in a Three-Dimensional suspension culture system. Stem Cell Rep. 2016;6(6):993–1008. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR119] 119.Sloan SA, Darmanis S, Huber N, Khan TA, Birey F, Caneda C, et al. Human astrocyte maturation captured in 3D cerebral cortical spheroids derived from pluripotent stem cells. Neuron. 2017;95(4):779–e7906. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR120] 120.Schukking M, Miranda HC, Trujillo CA, Negraes PD, Muotri AR. Direct generation of human cortical organoids from primary cells. Stem Cells Dev. 2018;27(22):1549–56. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR121] 121.Trujillo CA, Gao R, Negraes PD, Gu J, Buchanan J, Preissl S, et al. Complex oscillatory waves emerging from cortical organoids model early human brain network development. Cell Stem Cell. 2019;25(4):558–e5697. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR122] 122.Lancaster MA, Corsini NS, Wolfinger S, Gustafson EH, Phillips AW, Burkard TR, et al. Guided self-organization and cortical plate formation in human brain organoids. Nat Biotechnol. 2017;35(7):659–66. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR123] 123.Madhavan M, Nevin ZS, Shick HE, Garrison E, Clarkson-Paredes C, Karl M, et al. Induction of myelinating oligodendrocytes in human cortical spheroids. Nat Methods. 2018;15(9):700–6. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR124] 124.Mansour AA, Gonçalves JT, Bloyd CW, Li H, Fernandes S, Quang D, et al. An in vivo model of functional and vascularized human brain organoids. Nat Biotechnol. 2018;36(5):432–41. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR125] 125.Bagley JA, Reumann D, Bian S, Lévi-Strauss J, Knoblich JA. Fused cerebral organoids model interactions between brain regions. Nat Methods. 2017;14(7):743–51. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR126] 126.Sakaguchi H, Kadoshima T, Soen M, Narii N, Ishida Y, Ohgushi M, et al. Generation of functional hippocampal neurons from self-organizing human embryonic stem cell-derived dorsomedial telencephalic tissue. Nat Commun. 2015;6:8896. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR127] 127.Jo J, Xiao Y, Sun AX, Cukuroglu E, Tran HD, Göke J, et al. Midbrain-like organoids from human pluripotent stem cells contain functional dopaminergic and Neuromelanin-Producing neurons. Cell Stem Cell. 2016;19(2):248–57. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR128] 128.Kwak TH, Kang JH, Hali S, Kim J, Kim KP, Park C, et al. Generation of homogeneous midbrain organoids with in vivo-like cellular composition facilitates neurotoxin-based parkinson’s disease modeling. Stem Cells Dayt Ohio. 2020;38(6):727–40. [DOI] [PubMed] [Google Scholar]

[CR129] 129.Monzel AS, Smits LM, Hemmer K, Hachi S, Moreno EL, van Wuellen T, et al. Derivation of human Midbrain-Specific organoids from neuroepithelial stem cells. Stem Cell Rep. 2017;8(5):1144–54. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR130] 130.Tieng V, Stoppini L, Villy S, Fathi M, Dubois-Dauphin M, Krause KH. Engineering of midbrain organoids containing long-lived dopaminergic neurons. Stem Cells Dev. 2014;23(13):1535–47. [DOI] [PubMed] [Google Scholar]

[CR131] 131.Kim H, Park HJ, Choi H, Chang Y, Park H, Shin J, et al. Modeling G2019S-LRRK2 sporadic parkinson’s disease in 3D midbrain organoids. Stem Cell Rep. 2019;12(3):518–31. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR132] 132.Ozone C, Suga H, Eiraku M, Kadoshima T, Yonemura S, Takata N, et al. Functional anterior pituitary generated in self-organizing culture of human embryonic stem cells. Nat Commun. 2016;7:10351. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR133] 133.Muguruma K, Nishiyama A, Kawakami H, Hashimoto K, Sasai Y. Self-organization of polarized cerebellar tissue in 3D culture of human pluripotent stem cells. Cell Rep. 2015;10(4):537–50. [DOI] [PubMed] [Google Scholar]

[CR134] 134.Ogura T, Sakaguchi H, Miyamoto S, Takahashi J. Three-dimensional induction of dorsal, intermediate and ventral spinal cord tissues from human pluripotent stem cells. Dev Camb Engl. 2018;145(16):dev162214. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR135] 135.Lee JH, Shin H, Shaker MR, Kim HJ, Park SH, Kim JH, et al. Production of human spinal-cord organoids recapitulating neural-tube morphogenesis. Nat Biomed Eng. 2022;6(4):435–48. [DOI] [PubMed] [Google Scholar]

[CR136] 136.Gribaudo S, Robert R, van Sambeek B, Mirdass C, Lyubimova A, Bouhali K, et al. Self-organizing models of human trunk organogenesis recapitulate spinal cord and spine co-morphogenesis. Nat Biotechnol. 2024;42(8):1243–53. [DOI] [PubMed] [Google Scholar]

[CR137] 137.Jacob F, Pather SR, Huang WK, Zhang F, Wong SZH, Zhou H, et al. Human pluripotent stem Cell-Derived neural cells and brain organoids reveal SARS-CoV-2 neurotropism predominates in choroid plexus epithelium. Cell Stem Cell. 2020;27(6):937–e9509. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR138] 138.Miura Y, Li MY, Birey F, Ikeda K, Revah O, Thete MV, et al. Generation of human striatal organoids and cortico-striatal assembloids from human pluripotent stem cells. Nat Biotechnol. 2020;38(12):1421–30. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR139] 139.Huang WK, Wong SZH, Pather SR, Nguyen PTT, Zhang F, Zhang DY, et al. Generation of hypothalamic arcuate organoids from human induced pluripotent stem cells. Cell Stem Cell. 2021;28(9):1657–e167010. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR140] 140.Fligor CM, Langer KB, Sridhar A, Ren Y, Shields PK, Edler MC, et al. Three-Dimensional retinal organoids facilitate the investigation of retinal ganglion cell Development, organization and neurite outgrowth from human pluripotent stem cells. Sci Rep. 2018;8(1):14520. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR141] 141.Kuwahara A, Ozone C, Nakano T, Saito K, Eiraku M, Sasai Y. Generation of a ciliary margin-like stem cell niche from self-organizing human retinal tissue. Nat Commun. 2015;6:6286. [DOI] [PubMed] [Google Scholar]

[CR142] 142.Giandomenico SL, Mierau SB, Gibbons GM, Wenger LMD, Masullo L, Sit T, et al. Cerebral organoids at the air–liquid interface generate diverse nerve tracts with functional output. Nat Neurosci. 2019;22(4):669–79. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR143] 143.Wu W, Liu Y, Liu R, Wang Y, Zhao Y, Li H, et al. Decellularized brain extracellular matrix hydrogel aids the formation of human Spinal-Cord organoids recapitulating the complex Three-Dimensional organization. ACS Biomater Sci Eng. 2024;10(5):3203–17. [DOI] [PubMed] [Google Scholar]

[CR144] 144.Faissner A, Reinhard J. The extracellular matrix compartment of neural stem and glial progenitor cells. Glia. 2015;63(8):1330–49. [DOI] [PubMed] [Google Scholar]

[CR145] 145.Cho AN, Jin Y, An Y, Kim J, Choi YS, Lee JS, et al. Microfluidic device with brain extracellular matrix promotes structural and functional maturation of human brain organoids. Nat Commun. 2021;12(1):4730. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR146] 146.Simsa R, Rothenbücher T, Gürbüz H, Ghosheh N, Emneus J, Jenndahl L, et al. Brain organoid formation on decellularized Porcine brain ECM hydrogels. PLoS ONE. 2021;16(1):e0245685. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR147] 147.Shirahama H, Lee BH, Tan LP, Cho NJ. Precise tuning of facile One-Pot gelatin methacryloyl (GelMA) synthesis. Sci Rep. 2016;6:31036. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR148] 148.Heinrich MA, Bansal R, Lammers T, Zhang YS, Michel Schiffelers R, Prakash J. 3D-Bioprinted Mini-Brain: A glioblastoma model to study cellular interactions and therapeutics. Adv Mater Deerfield Beach Fla. 2019;31(14):e1806590. [DOI] [PubMed] [Google Scholar]

[CR149] 149.Faulkner-Jones A, Fyfe C, Cornelissen DJ, Gardner J, King J, Courtney A, et al. Bioprinting of human pluripotent stem cells and their directed differentiation into hepatocyte-like cells for the generation of mini-livers in 3D. Biofabrication. 2015;7(4):044102. [DOI] [PubMed] [Google Scholar]

[CR150] 150.Zhu Y, Wang L, Yu H, Yin F, Wang Y, Liu H, et al. In situ generation of human brain organoids on a micropillar array. Lab Chip. 2017;17(17):2941–50. [DOI] [PubMed] [Google Scholar]

[CR151] 151.Scuderi S, Kang TY, Jourdon A, Nelson A, Yang L, Wu F, et al. Specification of human brain regions with orthogonal gradients of WNT and SHH in organoids reveals patterning variations across cell lines. Cell Stem Cell. 2025;32(6):970–e98911. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR152] 152.Brownjohn PW, Smith J, Solanki R, Lohmann E, Houlden H, Hardy J, et al. Functional studies of missense TREM2 mutations in human stem Cell-Derived microglia. Stem Cell Rep. 2018;10(4):1294–307. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR153] 153.Xu R, Boreland AJ, Li X, Erickson C, Jin M, Atkins C, et al. Developing human pluripotent stem cell-based cerebral organoids with a controllable microglia ratio for modeling brain development and pathology. Stem Cell Rep. 2021;16(8):1923–37. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR154] 154.Shen Q, Goderie SK, Jin L, Karanth N, Sun Y, Abramova N, et al. Endothelial cells stimulate self-renewal and expand neurogenesis of neural stem cells. Science. 2004;304(5675):1338–40. [DOI] [PubMed] [Google Scholar]

[CR155] 155.Yin X, Mead BE, Safaee H, Langer R, Karp JM, Levy O. Eng Stem Cell Organoids Cell Stem Cell. 2016;18(1):25–38. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR156] 156.Bhatia SN, Ingber DE. Microfluidic organs-on-chips. Nat Biotechnol. 2014;32(8):760–72. [DOI] [PubMed] [Google Scholar]

[CR157] 157.Huh D, Matthews BD, Mammoto A, Montoya-Zavala M, Hsin HY, Ingber DE. Reconstituting organ-level lung functions on a chip. Science. 2010;328(5986):1662–8. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR158] 158.Qian X, Su Y, Adam CD, Deutschmann AU, Pather SR, Goldberg EM, et al. Sliced human cortical organoids for modeling distinct cortical layer formation. Cell Stem Cell. 2020;26(5):766–e7819. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR159] 159.Cakir B, Xiang Y, Tanaka Y, Kural MH, Parent M, Kang YJ, et al. Engineering of human brain organoids with a functional vascular-like system. Nat Methods. 2019;16(11):1169–75. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR160] 160.Wörsdörfer P, Dalda N, Kern A, Krüger S, Wagner N, Kwok CK, et al. Generation of complex human organoid models including vascular networks by incorporation of mesodermal progenitor cells. Sci Rep. 2019;9(1):15663. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR161] 161.Chalkiadaki K, Statoulla E, Zafeiri M, Voudouri G, Amvrosiadis T, Typou A, et al. GABA/Glutamate neuron differentiation imbalance and increased AKT/mTOR signaling in CNTNAP2–/– cerebral organoids. Biol Psychiatry Glob Open Sci. 2025;5(1):100413. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR162] 162.Daviaud N, Friedel RH, Zou H. Vascularization and engraftment of transplanted human cerebral organoids in mouse cortex. eNeuro. 2018;5(6):ENEURO0219–182018. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR163] 163.Revah O, Gore F, Kelley KW, Andersen J, Sakai N, Chen X, et al. Maturation and circuit integration of transplanted human cortical organoids. Nature. 2022;610(7931):319–26. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR164] 164.Wang Z, Wang SN, Xu TY, Hong C, Cheng MH, Zhu PX, et al. Cerebral organoids transplantation improves neurological motor function in rat brain injury. CNS Neurosci Ther. 2020;26(7):682–97. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR165] 165.Xiang Y, Tanaka Y, Patterson B, Kang YJ, Govindaiah G, Roselaar N, et al. Fusion of regionally specified hPSC-Derived organoids models human brain development and interneuron migration. Cell Stem Cell. 2017;21(3):383–e3987. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR166] 166.Andersen J, Revah O, Miura Y, Thom N, Amin ND, Kelley KW, et al. Generation of functional human 3D Cortico-Motor assembloids. Cell. 2020;183(7):1913–e192926. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR167] 167.Kshirsagar A, Mnatsakanyan H, Kulkarni S, Guo J, Cheng K, Ofria LD et al. Multi-Region Brain Organoids Integrating Cerebral, Mid-Hindbrain, and Endothelial Systems. Adv Sci. n/a(n/a):e03768. [DOI] [PMC free article] [PubMed]

[CR168] 168.Sauvageau M, Goff LA, Lodato S, Bonev B, Groff AF, Gerhardinger C, et al. Multiple knockout mouse models reveal LincRNAs are required for life and brain development. eLife. 2013;2:e01749. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR169] 169.Li Q, Cheng Z, Zhou L, Darmanis S, Neff NF, Okamoto J, et al. Developmental heterogeneity of microglia and brain myeloid cells revealed by deep Single-Cell RNA sequencing. Neuron. 2019;101(2):207–e22310. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR170] 170.Anderson DJ, Pauler FM, McKenna A, Shendure J, Hippenmeyer S, Horwitz MS. Simultaneous brain cell type and lineage determined by scRNA-seq reveals stereotyped cortical development. Cell Syst. 2022;13(6):438–e4535. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR171] 171.Bandler RC, Vitali I, Delgado RN, Ho MC, Dvoretskova E, Ibarra Molinas JS, et al. Single-cell delineation of lineage and genetic identity in the mouse brain. Nature. 2022;601(7893):404–9. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR172] 172.Tiklová K, Björklund ÅK, Lahti L, Fiorenzano A, Nolbrant S, Gillberg L, et al. Single-cell RNA sequencing reveals midbrain dopamine neuron diversity emerging during mouse brain development. Nat Commun. 2019;10(1):581. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR173] 173.Saunders A, Macosko EZ, Wysoker A, Goldman M, Krienen FM, de Rivera H, et al. Molecular diversity and specializations among the cells of the adult mouse brain. Cell. 2018;174(4):1015–e103016. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR174] 174.Liu J, Li K, Cai J, Zhang M, Zhang X, Xiong X, et al. Landscape and regulation of m6A and m6Am methylome across human and mouse tissues. Mol Cell. 2020;77(2):426–e4406. [DOI] [PubMed] [Google Scholar]

[CR175] 175.Li YE, Preissl S, Hou X, Zhang Z, Zhang K, Qiu Y, et al. An atlas of gene regulatory elements in adult mouse cerebrum. Nature. 2021;598(7879):129–36. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR176] 176.Zu S, Li YE, Wang K, Armand EJ, Mamde S, Amaral ML, et al. Single-cell analysis of chromatin accessibility in the adult mouse brain. Nature. 2023;624(7991):378–89. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR177] 177.Wang M, Zhang L, Novak SW, Yu J, Gallina IS, Xu LL, et al. Morphological diversification and functional maturation of human astrocytes in glia-enriched cortical organoid transplanted in mouse brain. Nat Biotechnol. 2025;43(1):52–62. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR178] 178.Hasselmann J, Coburn MA, England W, Figueroa Velez DX, Kiani Shabestari S, Tu CH, et al. Development of a chimeric model to study and manipulate human microglia in vivo. Neuron. 2019;103(6):1016–e103310. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR179] 179.Fattorelli N, Martinez-Muriana A, Wolfs L, Geric I, De Strooper B, Mancuso R. Stem-cell-derived human microglia transplanted into mouse brain to study human disease. Nat Protoc. 2021;16(2):1013–33. [DOI] [PubMed] [Google Scholar]

[CR180] 180.Xu R, Brawner AT, Li S, Liu JJ, Kim H, Xue H, et al. OLIG2 drives abnormal neurodevelopmental phenotypes in human iPSC-Based organoid and chimeric mouse models of down syndrome. Cell Stem Cell. 2019;24(6):908–e9268. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR181] 181.Mudge J, Miller NA, Khrebtukova I, Lindquist IE, May GD, Huntley JJ, et al. Genomic convergence analysis of schizophrenia: mRNA sequencing reveals altered synaptic vesicular transport in post-mortem cerebellum. PLoS ONE. 2008;3(11):e3625. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR182] 182.Yeo G, Holste D, Kreiman G, Burge CB. Variation in alternative splicing across human tissues. Genome Biol. 2004;5(10):R74. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR183] 183.Licatalosi DD, Darnell RB. Splicing regulation in neurologic disease. Neuron. 2006;52(1):93–101. [DOI] [PubMed] [Google Scholar]

[CR184] 184.Johnson MB, Kawasawa YI, Mason CE, Krsnik Z, Coppola G, Bogdanović D, et al. Functional and evolutionary insights into human brain development through global transcriptome analysis. Neuron. 2009;62(4):494–509. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR185] 185.Chen G, Yin K, Shi L, Fang Y, Qi Y, Li P, et al. Comparative analysis of human protein-coding and noncoding RNAs between brain and 10 mixed cell lines by RNA-Seq. PLoS ONE. 2011;6(11):e28318. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR186] 186.Patel AP, Tirosh I, Trombetta JJ, Shalek AK, Gillespie SM, Wakimoto H, et al. Single-cell RNA-seq highlights intratumoral heterogeneity in primary glioblastoma. Science. 2014;344(6190):1396–401. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR187] 187.Pollen AA, Nowakowski TJ, Shuga J, Wang X, Leyrat AA, Lui JH, et al. Low-coverage single-cell mRNA sequencing reveals cellular heterogeneity and activated signaling pathways in developing cerebral cortex. Nat Biotechnol. 2014;32(10):1053–8. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR188] 188.Darmanis S, Sloan SA, Zhang Y, Enge M, Caneda C, Shuer LM, et al. A survey of human brain transcriptome diversity at the single cell level. Proc Natl Acad Sci U S A. 2015;112(23):7285–90. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR189] 189.Tasic B, Yao Z, Graybuck LT, Smith KA, Nguyen TN, Bertagnolli D, et al. Shared and distinct transcriptomic cell types across neocortical areas. Nature. 2018;563(7729):72–8. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR190] 190.Raj B, Wagner DE, McKenna A, Pandey S, Klein AM, Shendure J, et al. Simultaneous single-cell profiling of lineages and cell types in the vertebrate brain. Nat Biotechnol. 2018;36(5):442–50. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR191] 191.Zhong S, Zhang S, Fan X, Wu Q, Yan L, Dong J, et al. A single-cell RNA-seq survey of the developmental landscape of the human prefrontal cortex. Nature. 2018;555(7697):524–8. [DOI] [PubMed] [Google Scholar]

[CR192] 192.Zhong S, Ding W, Sun L, Lu Y, Dong H, Fan X, et al. Decoding the development of the human hippocampus. Nature. 2020;577(7791):531–6. [DOI] [PubMed] [Google Scholar]

[CR193] 193.Mathys H, Davila-Velderrain J, Peng Z, Gao F, Mohammadi S, Young JZ, et al. Single-cell transcriptomic analysis of alzheimer’s disease. Nature. 2019;570(7761):332–7. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR194] 194.Grubman A, Chew G, Ouyang JF, Sun G, Choo XY, McLean C, et al. A single-cell atlas of entorhinal cortex from individuals with alzheimer’s disease reveals cell-type-specific gene expression regulation. Nat Neurosci. 2019;22(12):2087–97. [DOI] [PubMed] [Google Scholar]

[CR195] 195.Zimmer B, Piao J, Ramnarine K, Tomishima MJ, Tabar V, Studer L. Derivation of diverse Hormone-Releasing pituitary cells from human pluripotent stem cells. Stem Cell Rep. 2016;6(6):858–72. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR196] 196.Eura N, Matsui TK, Luginbühl J, Matsubayashi M, Nanaura H, Shiota T, et al. Brainstem organoids from human pluripotent stem cells. Front Neurosci. 2020;14:538. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR197] 197.Smits LM, Magni S, Kinugawa K, Grzyb K, Luginbühl J, Sabate-Soler S, et al. Single-cell transcriptomics reveals multiple neuronal cell types in human midbrain-specific organoids. Cell Tissue Res. 2020;382(3):463–76. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR198] 198.Yoon SJ, Elahi LS, Pașca AM, Marton RM, Gordon A, Revah O, et al. Reliability of human cortical organoid generation. Nat Methods. 2019;16(1):75–8. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR199] 199.Tanaka Y, Cakir B, Xiang Y, Sullivan GJ, Park IH. Synthetic analyses of Single-Cell transcriptomes from multiple brain organoids and fetal brain. Cell Rep. 2020;30(6):1682–e16893. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR200] 200.He Z, Dony L, Fleck JS, Szałata A, Li KX, Slišković I, et al. An integrated transcriptomic cell atlas of human neural organoids. Nature. 2024;635(8039):690–8. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR201] 201.Everhard S, Tost J, El Abdalaoui H, Crinière E, Busato F, Marie Y, et al. Identification of regions correlating MGMT promoter methylation and gene expression in glioblastomas. Neuro-Oncol. 2009;11(4):348–56. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR202] 202.Kreth S, Thon N, Eigenbrod S, Lutz J, Ledderose C, Egensperger R, et al. O-methylguanine-DNA methyltransferase (MGMT) mRNA expression predicts outcome in malignant glioma independent of MGMT promoter methylation. PLoS ONE. 2011;6(2):e17156. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR203] 203.Lee DS, Luo C, Zhou J, Chandran S, Rivkin A, Bartlett A, et al. Simultaneous profiling of 3D genome structure and DNA methylation in single human cells. Nat Methods. 2019;16(10):999–1006. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR204] 204.Luo C, Rivkin A, Zhou J, Sandoval JP, Kurihara L, Lucero J, et al. Robust single-cell DNA methylome profiling with snmC-seq2. Nat Commun. 2018;9(1):3824. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR205] 205.Heffel MG, Zhou J, Zhang Y, Lee DS, Hou K, Pastor-Alonso O, et al. Temporally distinct 3D multi-omic dynamics in the developing human brain. Nature. 2024;635(8038):481–9. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR206] 206.Oh G, Ebrahimi S, Wang SC, Cortese R, Kaminsky ZA, Gottesman II, et al. Epigenetic assimilation in the aging human brain. Genome Biol. 2016;17:76. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR207] 207.Tian W, Zhou J, Bartlett A, Zeng Q, Liu H, Castanon RG, et al. Single-cell DNA methylation and 3D genome architecture in the human brain. Science. 2023;382(6667):eadf5357. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR208] 208.Treble-Barna A, Heinsberg LW, Stec Z, Breazeale S, Davis TS, Kesbhat AA, et al. Brain-derived neurotrophic factor (BDNF) epigenomic modifications and brain-related phenotypes in humans: A systematic review. Neurosci Biobehav Rev. 2023;147:105078. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR209] 209.Fullard JF, Giambartolomei C, Hauberg ME, Xu K, Voloudakis G, Shao Z, et al. Open chromatin profiling of human postmortem brain infers functional roles for non-coding schizophrenia loci. Hum Mol Genet. 2017;26(10):1942–51. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR210] 210.Fullard JF, Hauberg ME, Bendl J, Egervari G, Cirnaru MD, Reach SM, et al. An atlas of chromatin accessibility in the adult human brain. Genome Res. 2018;28(8):1243–52. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR211] 211.Herring CA, Simmons RK, Freytag S, Poppe D, Moffet JJD, Pflueger J, et al. Human prefrontal cortex gene regulatory dynamics from gestation to adulthood at single-cell resolution. Cell. 2022;185(23):4428–e444728. [DOI] [PubMed] [Google Scholar]

[CR212] 212.Morabito S, Miyoshi E, Michael N, Shahin S, Martini AC, Head E, et al. Single-nucleus chromatin accessibility and transcriptomic characterization of alzheimer’s disease. Nat Genet. 2021;53(8):1143–55. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR213] 213.Li YE, Preissl S, Miller M, Johnson ND, Wang Z, Jiao H, et al. A comparative atlas of single-cell chromatin accessibility in the human brain. Science. 2023;382(6667):eadf7044. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR214] 214.Dong P, Song L, Bendl J, Misir R, Shao Z, Edelstien J, et al. A multi-regional human brain atlas of chromatin accessibility and gene expression facilitates promoter-isoform resolution genetic fine-mapping. Nat Commun. 2024;15(1):10113. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR215] 215.Zhu K, Bendl J, Rahman S, Vicari JM, Coleman C, Clarence T, et al. Multi-omic profiling of the developing human cerebral cortex at the single-cell level. Sci Adv. 2023;9(41):eadg3754. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR216] 216.Bryois J, Garrett ME, Song L, Safi A, Giusti-Rodriguez P, Johnson GD, et al. Evaluation of chromatin accessibility in prefrontal cortex of individuals with schizophrenia. Nat Commun. 2018;9(1):3121. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR217] 217.Trevino AE, Sinnott-Armstrong N, Andersen J, Yoon SJ, Huber N, Pritchard JK, et al. Chromatin accessibility dynamics in a model of human forebrain development. Science. 2020;367(6476):eaay1645. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR218] 218.Ziffra RS, Kim CN, Ross JM, Wilfert A, Turner TN, Haeussler M, et al. Single-cell epigenomics reveals mechanisms of human cortical development. Nature. 2021;598(7879):205–13. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR219] 219.Lewis EMA, Kaushik K, Sandoval LA, Antony I, Dietmann S, Kroll KL. Epigenetic regulation during human cortical development: Seq-ing answers from the brain to the organoid. Neurochem Int. 2021;147:105039. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR220] 220.Shang Z, Chen D, Wang Q, Wang S, Deng Q, Wu L, et al. Single-cell RNA-seq reveals dynamic transcriptome profiling in human early neural differentiation. GigaScience. 2018;7(11):giy117. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR221] 221.Uzquiano A, Kedaigle AJ, Pigoni M, Paulsen B, Adiconis X, Kim K, et al. Proper acquisition of cell class identity in organoids allows definition of fate specification programs of the human cerebral cortex. Cell. 2022;185(20):3770–e378827. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR222] 222.Fleck JS, Jansen SMJ, Wollny D, Zenk F, Seimiya M, Jain A, et al. Inferring and perturbing cell fate regulomes in human brain organoids. Nature. 2023;621(7978):365–72. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR223] 223.Barral A, Déjardin J. The chromatin signatures of enhancers and their dynamic regulation. Nucl Austin Tex. 2023;14(1):2160551. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR224] 224.Koshi-Mano K, Mano T, Morishima M, Murayama S, Tamaoka A, Tsuji S, et al. Neuron-specific analysis of histone modifications with post-mortem brains. Sci Rep. 2020;10(1):3767. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR225] 225.Ziller MJ, Edri R, Yaffe Y, Donaghey J, Pop R, Mallard W, et al. Dissecting neural differentiation regulatory networks through epigenetic footprinting. Nature. 2015;518(7539):355–9. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR226] 226.Amiri A, Coppola G, Scuderi S, Wu F, Roychowdhury T, Liu F, et al. Transcriptome and epigenome landscape of human cortical development modeled in organoids. Science. 2018;362(6420):eaat6720. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR227] 227.Inoue F, Kreimer A, Ashuach T, Ahituv N, Yosef N. Identification and massively parallel characterization of regulatory elements driving neural induction. Cell Stem Cell. 2019;25(5):713–e72710. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR228] 228.Zenk F, Fleck JS, Jansen SMJ, Kashanian B, Eisinger B, Santel M, et al. Single-cell epigenomic reconstruction of developmental trajectories from pluripotency in human neural organoid systems. Nat Neurosci. 2024;27(7):1376–86. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR229] 229.Hess ME, Hess S, Meyer KD, Verhagen LAW, Koch L, Brönneke HS, et al. The fat mass and obesity associated gene (Fto) regulates activity of the dopaminergic midbrain circuitry. Nat Neurosci. 2013;16(8):1042–8. [DOI] [PubMed] [Google Scholar]

[CR230] 230.Li L, Zang L, Zhang F, Chen J, Shen H, Shu L, et al. Fat mass and obesity-associated (FTO) protein regulates adult neurogenesis. Hum Mol Genet. 2017;26(13):2398–411. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR231] 231.Walters BJ, Mercaldo V, Gillon CJ, Yip M, Neve RL, Boyce FM, et al. The role of the RNA demethylase FTO (Fat mass and Obesity-Associated) and mRNA methylation in hippocampal memory formation. Neuropsychopharmacol Off Publ Am Coll Neuropsychopharmacol. 2017;42(7):1502–10. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR232] 232.Du B, Zhang Y, Liang M, Du Z, Li H, Fan C, et al. N6-methyladenosine (m6A) modification and its clinical relevance in cognitive dysfunctions. Aging. 2021;13(16):20716–37. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR233] 233.Castro-Hernández R, Berulava T, Metelova M, Epple R, Peña Centeno T, Richter J, et al. Conserved reduction of m6A RNA modifications during aging and neurodegeneration is linked to changes in synaptic transcripts. Proc Natl Acad Sci U S A. 2023;120(9):e2204933120. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR234] 234.Edgar PF, Schonberger SJ, Dean B, Faull RL, Kydd R, Cooper GJ. A comparative proteome analysis of hippocampal tissue from schizophrenic and alzheimer’s disease individuals. Mol Psychiatry. 1999;4(2):173–8. [DOI] [PubMed] [Google Scholar]

[CR235] 235.Johnson ECB, Dammer EB, Duong DM, Ping L, Zhou M, Yin L, et al. Large-scale proteomic analysis of alzheimer’s disease brain and cerebrospinal fluid reveals early changes in energy metabolism associated with microglia and astrocyte activation. Nat Med. 2020;26(5):769–80. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR236] 236.Johnson ECB, Carter EK, Dammer EB, Duong DM, Gerasimov ES, Liu Y, et al. Large-scale deep multi-layer analysis of alzheimer’s disease brain reveals strong proteomic disease-related changes not observed at the RNA level. Nat Neurosci. 2022;25(2):213–25. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR237] 237.Graham SF, Chevallier OP, Roberts D, Hölscher C, Elliott CT, Green BD. Investigation of the human brain metabolome to identify potential markers for early diagnosis and therapeutic targets of alzheimer’s disease. Anal Chem. 2013;85(3):1803–11. [DOI] [PubMed] [Google Scholar]

[CR238] 238.Wang Y, Zhou L, Wang N, Qiu B, Yao D, Yu J, et al. Comprehensive characterization of metabolic consumption and production by the human brain. Neuron. 2025;113(11):1708–e17225. [DOI] [PubMed] [Google Scholar]

[CR239] 239.Dezonne RS, Sartore RC, Nascimento JM, Saia-Cereda VM, Romão LF, Alves-Leon SV, et al. Derivation of functional human astrocytes from cerebral organoids. Sci Rep. 2017;7:45091. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR240] 240.Karlinski Zur M, Bhattacharya B, Solomonov I, Ben Dror S, Savidor A, Levin Y, et al. Altered extracellular matrix structure and elevated stiffness in a brain organoid model for disease. Nat Commun. 2025;16(1):4094. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR241] 241.Chen C, Lee S, Zyner KG, Fernando M, Nemeruck V, Wong E, et al. Trans-omic profiling uncovers molecular controls of early human cerebral organoid formation. Cell Rep. 2024;43(5):114219. [DOI] [PubMed] [Google Scholar]

[CR242] 242.Pamies D, Block K, Lau P, Gribaldo L, Pardo CA, Barreras P, et al. Rotenone exerts developmental neurotoxicity in a human brain spheroid model. Toxicol Appl Pharmacol. 2018;354:101–14. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR243] 243.Guy B, Zhang JS, Duncan LH, Johnston RJ. Human neural organoids: models for developmental neurobiology and disease. Dev Biol. 2021;478:102–21. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR244] 244.Qian X, Nguyen HN, Jacob F, Song H, Ming GL. Using brain organoids to understand Zika virus-induced microcephaly. Dev Camb Engl. 2017;144(6):952–7. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR245] 245.Smits LM, Reinhardt L, Reinhardt P, Glatza M, Monzel AS, Stanslowsky N, et al. Modeling parkinson’s disease in midbrain-like organoids. NPJ Park Dis. 2019;5:5. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR246] 246.Ramani A, Pasquini G, Gerkau NJ, Jadhav V, Vinchure OS, Altinisik N, et al. Reliability of high-quantity human brain organoids for modeling microcephaly, glioma invasion and drug screening. Nat Commun. 2024;15(1):10703. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR247] 247.Struzyna LA, Watt ML. The emerging role of neuronal organoid models in drug discovery: potential applications and hurdles to implementation. Mol Pharmacol. 2021;99(4):256–65. [DOI] [PubMed] [Google Scholar]

[CR248] 248.McMahon AP, Bradley A. The Wnt-1 (int-1) proto-oncogene is required for development of a large region of the mouse brain. Cell. 1990;62(6):1073–85. [DOI] [PubMed] [Google Scholar]

[CR249] 249.Chiaradia I, Lancaster MA. Brain organoids for the study of human neurobiology at the interface of in vitro and in vivo. Nat Neurosci. 2020;23(12):1496–508. [DOI] [PubMed] [Google Scholar]

[CR250] 250.Onesto MM, Kim JI, Pasca SP. Assembloid models of cell-cell interaction to study tissue and disease biology. Cell Stem Cell. 2024;31(11):1563–73. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR251] 251.Nityanandam A, Patton MH, Bayazitov IT, Newman KD, Thomas KT, Zakharenko SS. Protocol for generating human assembloids to investigate thalamocortical and corticothalamic synaptic transmission and plasticity. STAR Protoc. 2025;6(1):103630. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR252] 252.Martins-Costa C, Wiegers A, Pham VA, Sidhaye J, Doleschall B, Novatchkova M, et al. ARID1B controls transcriptional programs of axon projection in an organoid model of the human corpus callosum. Cell Stem Cell. 2024;31(6):866–e88514. [DOI] [PubMed] [Google Scholar]

[CR253] 253.Marton RM, Miura Y, Sloan SA, Li Q, Revah O, Levy RJ, et al. Differentiation and maturation of oligodendrocytes in human three-dimensional neural cultures. Nat Neurosci. 2019;22(3):484–91. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR254] 254.Nambot S, Faivre L, Mirzaa G, Thevenon J, Bruel AL, Mosca-Boidron AL, et al. De Novo TBR1 variants cause a neurocognitive phenotype with ID and autistic traits: report of 25 new individuals and review of the literature. Eur J Hum Genet EJHG. 2020;28(6):770–82. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR255] 255.Dhaliwal N, Choi WWY, Muffat J, Li Y. Modeling PTEN overexpression-induced microcephaly in human brain organoids. Mol Brain. 2021;14(1):131. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR256] 256.Pigoni M, Uzquiano A, Paulsen B, Kedaigle AJ, Yang SM, Symvoulidis P, et al. Cell-type specific defects in PTEN-mutant cortical organoids converge on abnormal circuit activity. Hum Mol Genet. 2023;32(18):2773–86. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR257] 257.Cederlund M. Microcephaly in preschool children with autism spectrum disorder. Res Autism Spectr Disord. 2021;88:101845. [Google Scholar]

[CR258] 258.Paulsen B, Velasco S, Kedaigle AJ, Pigoni M, Quadrato G, Deo AJ, et al. Autism genes converge on asynchronous development of shared neuron classes. Nature. 2022;602(7896):268–73. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR259] 259.Villa CE, Cheroni C, Dotter CP, López-Tóbon A, Oliveira B, Sacco R, et al. CHD8 haploinsufficiency links autism to transient alterations in excitatory and inhibitory trajectories. Cell Rep. 2022;39(1):110615. [DOI] [PubMed] [Google Scholar]

[CR260] 260.Gomes AR, Fernandes TG, Vaz SH, Silva TP, Bekman EP, Xapelli S, et al. Modeling Rett syndrome with human Patient-Specific forebrain organoids. Front Cell Dev Biol. 2020;8:610427. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR261] 261.Zhang BZ, Chu H, Han S, Shuai H, Deng J, Hu Y et al. fan,. SARS-CoV-2 infects human neural progenitor cells and brain organoids. Cell Res. 2020;30(10):928–31. [DOI] [PMC free article] [PubMed]

[CR262] 262.Ramani A, Müller L, Ostermann PN, Gabriel E, Abida-Islam P, Müller‐Schiffmann A, et al. SARS ‐CoV‐2 targets neurons of 3D human brain organoids. EMBO J. 2020;39(20):e106230. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR263] 263.Samarasinghe RA, Miranda OA, Buth JE, Mitchell S, Ferando I, Watanabe M, et al. Identification of neural oscillations and epileptiform changes in human brain organoids. Nat Neurosci. 2021;24(10):1488–500. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR264] 264.Marchetto MC, Belinson H, Tian Y, Freitas BC, Fu C, Vadodaria K, et al. Altered proliferation and networks in neural cells derived from idiopathic autistic individuals. Mol Psychiatry. 2017;22(6):820–35. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR265] 265.Pagliaro A, Artegiani B, Hendriks D. Emerging approaches to enhance human brain organoid physiology. Trends Cell Biol. 2025;35(6):483–99. [DOI] [PubMed] [Google Scholar]

[CR266] 266.Kang SC, Sarn NB, Venegas J, Tan Z, Hitomi M, Eng C. Germline PTEN genotype-dependent phenotypic divergence during the early neural developmental process of forebrain organoids. Mol Psychiatry. 2024;29(6):1767–81. [DOI] [PubMed] [Google Scholar]

[CR267] 267.Dhaliwal NK, Weng OY, Dong X, Bhattacharya A, Ahmed M, Nishimura H, et al. Synergistic hyperactivation of both mTORC1 and mTORC2 underlies the neural abnormalities of PTEN-deficient human neurons and cortical organoids. Cell Rep. 2024;43(5):114173. [DOI] [PubMed] [Google Scholar]

[CR268] 268.Xu YJ, Liu PP, Yan ZZ, Mi TW, Wang YY, Li Q, et al. KW-2449 and VPA exert therapeutic effects on human neurons and cerebral organoids derived from MECP2-null hESCs. Stem Cell Res Ther. 2022;13(1):534. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR269] 269.Lin YT, Seo J, Gao F, Feldman HM, Wen HL, Penney J, et al. APOE4 causes widespread molecular and cellular alterations associated with alzheimer’s disease phenotypes in human iPSC-Derived brain cell types. Neuron. 2018;98(6):1141–e11547. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR270] 270.Raj N, McEachin ZT, Harousseau W, Zhou Y, Zhang F, Merritt-Garza ME, et al. Cell-type-specific profiling of human cellular models of fragile X syndrome reveal PI3K-dependent defects in translation and neurogenesis. Cell Rep. 2021;35(2):108991. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR271] 271.Dang J, Tiwari SK, Lichinchi G, Qin Y, Patil VS, Eroshkin AM, et al. Zika virus depletes neural progenitors in human cerebral organoids through activation of the innate immune receptor TLR3. Cell Stem Cell. 2016;19(2):258–65. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR272] 272.Sison SL, O’Brien BS, Johnson AJ, Seminary ER, Terhune SS, Ebert AD. Human cytomegalovirus disruption of calcium signaling in neural progenitor cells and organoids. J Virol. 2019;93(17):e00954–19. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR273] 273.Sun G, Chiuppesi F, Chen X, Wang C, Tian E, Nguyen J, et al. Modeling human Cytomegalovirus-Induced microcephaly in human iPSC-Derived brain organoids. Cell Rep Med. 2020;1(1):100002. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR274] 274.Zheng Y, Zhang F, Xu S, Wu L. Advances in neural organoid systems and their application in neurotoxicity testing of environmental chemicals. Genes Environ Off J Jpn Environ Mutagen Soc. 2021;43(1):39. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR275] 275.Park JC, Jang SY, Lee D, Lee J, Kang U, Chang H, et al. A logical network-based drug-screening platform for alzheimer’s disease representing pathological features of human brain organoids. Nat Commun. 2021;12(1):280. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR276] 276.Eze UC, Bhaduri A, Haeussler M, Nowakowski TJ, Kriegstein AR. Single-cell atlas of early human brain development highlights heterogeneity of human neuroepithelial cells and early radial glia. Nat Neurosci. 2021;24(4):584–94. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR277] 277.Brandenberg N, Hoehnel S, Kuttler F, Homicsko K, Ceroni C, Ringel T, et al. High-throughput automated organoid culture via stem-cell aggregation in microcavity arrays. Nat Biomed Eng. 2020;4(9):863–74. [DOI] [PubMed] [Google Scholar]

[CR278] 278.Hofer M, Lutolf MP. Engineering organoids. Nat Rev Mater. 2021;6(5):402–20. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR279] 279.Renner H, Grabos M, Becker KJ, Kagermeier TE, Wu J, Otto M, et al. A fully automated high-throughput workflow for 3D-based chemical screening in human midbrain organoids. eLife. 2020;9:e52904. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR280] 280.Zivko C, Sagar R, Xydia A, Lopez-Montes A, Mintzer J, Rosenberg PB, et al. iPSC-derived hindbrain organoids to evaluate Escitalopram oxalate treatment responses targeting neuropsychiatric symptoms in alzheimer’s disease. Mol Psychiatry. 2024;29(11):3644–52. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR281] 281.Gomez-Giro G, Frangenberg D, Vega D, Zagare A, Barmpa K, Antony PMA, et al. α‐Synuclein pathology spreads in a Midbrain–Hindbrain assembloid model. Adv Sci. 2025;12(20):2409040. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR282] 282.Kshirsagar A, Mnatsakanyan H, Kulkarni S, Guo J, Cheng K, Ofria LD, et al. Multi-Region brain organoids integrating Cerebral, Mid‐Hindbrain, and endothelial systems. Adv Sci. 2025;12(33):e03768. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR283] 283.Yuan F, Fang KH, Hong Y, Xu SB, Xu M, Pan Y, et al. LHX6 is essential for the migration of human pluripotent stem cell-derived GABAergic interneurons. Protein Cell. 2020;11(4):286–91. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR284] 284.Bertucci T, Bowles KR, Lotz S, Qi L, Stevens K, Goderie SK et al. Improved protocol for reproducible human cortical organoids reveals early alterations in metabolism with MAPT mutations. BioRxiv Prepr Serv Biol. 2023;2023.07.11.548571.

[CR285] 285.Srikanth P, Lagomarsino VN, Muratore CR, Ryu SC, He A, Taylor WM, et al. Shared effects of DISC1 disruption and elevated WNT signaling in human cerebral organoids. Transl Psychiatry. 2018;8(1):77. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR286] 286.Wang Y, Chiola S, Yang G, Russell C, Armstrong CJ, Wu Y, et al. Modeling human telencephalic development and autism-associated SHANK3 deficiency using organoids generated from single neural rosettes. Nat Commun. 2022;13(1):5688. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR287] 287.Szu J, Wojcinski A, Jiang P, Kesari S. Impact of the Olig family on neurodevelopmental disorders. Front Neurosci. 2021;15:659601. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR288] 288.Vasan L, Chinchalongporn V, Saleh F, Zinyk D, Ke C, Suresh H, et al. Examining the NEUROG2 lineage and associated gene expression in human cortical organoids. Dev Camb Engl. 2025;152(2):dev202703. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR289] 289.van Essen MJ, Apsley EJ, Riepsaame J, Xu R, Northcott PA, Cowley SA, et al. PTCH1-mutant human cerebellar organoids exhibit altered neural development and recapitulate early Medulloblastoma tumorigenesis. Dis Model Mech. 2024;17(2):dmm050323. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR290] 290.Fischer J, Fernández Ortuño E, Marsoner F, Artioli A, Peters J, Namba T, et al. Human-specific ARHGAP11B ensures human-like basal progenitor levels in hominid cerebral organoids. EMBO Rep. 2022;23(11):e54728. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR291] 291.Fiddes IT, Lodewijk GA, Mooring M, Bosworth CM, Ewing AD, Mantalas GL, et al. Human-Specific NOTCH2NL genes affect Notch signaling and cortical neurogenesis. Cell. 2018;173(6):1356–e136922. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR292] 292.López-Tobón A, Villa CE, Cheroni C, Trattaro S, Caporale N, Conforti P, et al. Human cortical organoids expose a differential function of GSK3 on cortical neurogenesis. Stem Cell Rep. 2019;13(5):847–61. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR293] 293.Seeler S, Andersen MS, Sztanka-Toth T, Rybiczka-Tešulov M, van den Munkhof MH, Chang CC, et al. A circular RNA expressed from the FAT3 locus regulates neural development. Mol Neurobiol. 2023;60(6):3239–60. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR294] 294.Liu J, Mosti F, Zhao HT, Lollis D, Sotelo-Fonseca JE, Escobar-Tomlienovich CF, et al. A human-specific enhancer fine-tunes radial glia potency and corticogenesis. Nature. 2025;643(8074):1321–32. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR295] 295.Kang Y, Zhou Y, Li Y, Han Y, Xu J, Niu W, et al. A human forebrain organoid model of fragile X syndrome exhibits altered neurogenesis and highlights new treatment strategies. Nat Neurosci. 2021;24(10):1377–91. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR296] 296.Urresti J, Zhang P, Moran-Losada P, Yu NK, Negraes PD, Trujillo CA, et al. Cortical organoids model early brain development disrupted by 16p11.2 copy number variants in autism. Mol Psychiatry. 2021;26(12):7560–80. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR297] 297.Jourdon A, Wu F, Mariani J, Capauto D, Norton S, Tomasini L, et al. Modeling idiopathic autism in forebrain organoids reveals an imbalance of excitatory cortical neuron subtypes during early neurogenesis. Nat Neurosci. 2023;26(9):1505–15. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR298] 298.de Jong JO, Llapashtica C, Genestine M, Strauss K, Provenzano F, Sun Y, et al. Cortical overgrowth in a preclinical forebrain organoid model of CNTNAP2-associated autism spectrum disorder. Nat Commun. 2021;12(1):4087. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR299] 299.Li C, Fleck JS, Martins-Costa C, Burkard TR, Themann J, Stuempflen M, et al. Single-cell brain organoid screening identifies developmental defects in autism. Nature. 2023;621(7978):373–80. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR300] 300.Birtele M, Del Dosso A, Xu T, Nguyen T, Wilkinson B, Hosseini N, et al. Non-synaptic function of the autism spectrum disorder-associated gene SYNGAP1 in cortical neurogenesis. Nat Neurosci. 2023;26(12):2090–103. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR301] 301.Discovery of. A non-canonical function of SYNGAP1 at early stages of human cortical neurogenesis. Nat Neurosci. 2023;26(12):2050–1. [DOI] [PubMed] [Google Scholar]

[CR302] 302.Zhang W, Yang SL, Yang M, Herrlinger S, Shao Q, Collar JL, et al. Modeling microcephaly with cerebral organoids reveals a WDR62-CEP170-KIF2A pathway promoting cilium disassembly in neural progenitors. Nat Commun. 2019;10(1):2612. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR303] 303.Omer Javed A, Li Y, Muffat J, Su KC, Cohen MA, Lungjangwa T, et al. Microcephaly modeling of kinetochore mutation reveals a Brain-Specific phenotype. Cell Rep. 2018;25(2):368–e3825. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR304] 304.Fair SR, Schwind W, Julian DL, Biel A, Guo G, Rutherford R, et al. Cerebral organoids containing an AUTS2 missense variant model microcephaly. Brain J Neurol. 2023;146(1):387–404. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR305] 305.Li R, Sun L, Fang A, Li P, Wu Q, Wang X. Recapitulating cortical development with organoid culture in vitro and modeling abnormal spindle-like (ASPM related primary) microcephaly disease. Protein Cell. 2017;8(11):823–33. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR306] 306.Wang L, Li Z, Sievert D, Smith DEC, Mendes MI, Chen DY, et al. Loss of NARS1 impairs progenitor proliferation in cortical brain organoids and leads to microcephaly. Nat Commun. 2020;11(1):4038. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR307] 307.Esk C, Lindenhofer D, Haendeler S, Wester RA, Pflug F, Schroeder B, et al. A human tissue screen identifies a regulator of ER secretion as a brain-size determinant. Science. 2020;370(6519):935–41. [DOI] [PubMed] [Google Scholar]

[CR308] 308.Dang LT, Vaid S, Lin G, Swaminathan P, Safran J, Loughman A, et al. STRADA-mutant human cortical organoids model megalencephaly and exhibit delayed neuronal differentiation. Dev Neurobiol. 2021;81(5):696–709. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR309] 309.Zhang W, Ma L, Yang M, Shao Q, Xu J, Lu Z, et al. Cerebral organoid and mouse models reveal a RAB39b-PI3K-mTOR pathway-dependent dysregulation of cortical development leading to macrocephaly/autism phenotypes. Genes Dev. 2020;34(7–8):580–97. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR310] 310.Xu J, Kong Y, Wang N, Li H, Li Y, Liu Z, et al. Personalized human Astrocyte-Derived Region-Specific forebrain organoids recapitulate endogenous pathological features of focal cortical dysplasia. Adv Sci Weinh Baden-Wurtt Ger. 2025;12(8):e2409774. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR311] 311.Birey F, Li MY, Gordon A, Thete MV, Valencia AM, Revah O, et al. Dissecting the molecular basis of human interneuron migration in forebrain assembloids from timothy syndrome. Cell Stem Cell. 2022;29(2):248–e2647. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR312] 312.Trujillo CA, Adams JW, Negraes PD, Carromeu C, Tejwani L, Acab A, et al. Pharmacological reversal of synaptic and network pathology in human MECP2-KO neurons and cortical organoids. EMBO Mol Med. 2021;13(1):e12523. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR313] 313.Xiang Y, Tanaka Y, Patterson B, Hwang SM, Hysolli E, Cakir B, et al. Dysregulation of BRD4 function underlies the functional abnormalities of MeCP2 mutant neurons. Mol Cell. 2020;79(1):84–e989. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR314] 314.Yildirim M, Delepine C, Feldman D, Pham VA, Chou S, Ip J, et al. Label-free three-photon imaging of intact human cerebral organoids for tracking early events in brain development and deficits in Rett syndrome. eLife. 2022;11:e78079. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR315] 315.Mellios N, Feldman DA, Sheridan SD, Ip JPK, Kwok S, Amoah SK, et al. MeCP2-regulated MiRNAs control early human neurogenesis through differential effects on ERK and AKT signaling. Mol Psychiatry. 2018;23(4):1051–65. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR316] 316.Gonzalez C, Armijo E, Bravo-Alegria J, Becerra-Calixto A, Mays CE, Soto C. Modeling amyloid beta and Tau pathology in human cerebral organoids. Mol Psychiatry. 2018;23(12):2363–74. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR317] 317.Tang XY, Xu L, Wang J, Hong Y, Wang Y, Zhu Q, et al. DSCAM/PAK1 pathway suppression reverses neurogenesis deficits in iPSC-derived cerebral organoids from patients with down syndrome. J Clin Invest. 2021;131(12):e135763. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR318] 318.Zhang W, Zhang M, Xu Z, Yan H, Wang H, Jiang J, et al. Human forebrain organoid-based multi-omics analyses of PCCB as a schizophrenia associated gene linked to GABAergic pathways. Nat Commun. 2023;14(1):5176. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR319] 319.Notaras M, Lodhi A, Dündar F, Collier P, Sayles NM, Tilgner H, et al. Schizophrenia is defined by cell-specific neuropathology and multiple neurodevelopmental mechanisms in patient-derived cerebral organoids. Mol Psychiatry. 2022;27(3):1416–34. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR320] 320.Ye F, Kang E, Yu C, Qian X, Jacob F, Yu C, et al. DISC1 regulates neurogenesis via modulating kinetochore attachment of Ndel1/Nde1 during mitosis. Neuron. 2017;96(5):1041–e10545. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR321] 321.Kathuria A, Lopez-Lengowski K, Vater M, McPhie D, Cohen BM, Karmacharya R. Transcriptome analysis and functional characterization of cerebral organoids in bipolar disorder. Genome Med. 2020;12(1):34. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR322] 322.Yang G, Ullah HMA, Parker E, Gorsi B, Libowitz M, Maguire C, et al. Neurite outgrowth deficits caused by rare PLXNB1 mutation in pediatric bipolar disorder. Mol Psychiatry. 2023;28(6):2525–39. [DOI] [PubMed] [Google Scholar]

[CR323] 323.Osete JR, Akkouh IA, Ievglevskyi O, Vandenberghe M, de Assis DR, Ueland T, et al. Transcriptional and functional effects of lithium in bipolar disorder iPSC-derived cortical spheroids. Mol Psychiatry. 2023;28(7):3033–43. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR324] 324.Chen J, Hadi F, Wen X, Zhao W, Xu M, Xue S, et al. Transcriptional regulation by PHGDH drives amyloid pathology in alzheimer’s disease. Cell. 2025;188(13):3513–e352926. [DOI] [PMC free article] [PubMed] [Google Scholar]

PERMALINK

Pluripotent stem cells-based neural organoids for modelling human brain development and diseases

Lingling Tong

Peiqi Tian

Ruoxi Wang

Shiyun Niu

Ruoming Wang

Yaxuan Ye

Yuxin Wu

Wenjing Zhang

Yueqi Wang

Angelica Foggetti

Di Chen

Abstract

Introduction

Neural development in mouse

Embryonic development of neuroectoderm

Fig. 1.

Fig. 2.

Neurogenesis

Neuronal migration

Fig. 3.

Neural network maturation

Neural development in human

Embryonic development of neuroectoderm

Neurogenesis

Neuronal migration

Neural network maturation

Comparison of mouse and human neural development

Brain organoids in mice

Fig. 4.

Table 1.

Brain organoids in humans

Table 2.

Optimization of the culture conditions

Co-culture system and vascularized organoids

Assembloids system

Application of genomics in neural organoids

Fig. 5.

Omics in mouse brains, mouse brain organoids and chimeric models

Omics in human brain and brain organoids

The applications of brain organoids

Fig. 6.

Cellular process

Gene function

Table 3.

Disease modeling

Table 4.

Drug screen

Conclusion and perspectives

Acknowledgements

Author contributions

Funding

Data availability

Declarations

Ethics approval and consent to participate

Consent for publication

Competing interests

Footnotes

Contributor Information

References

Associated Data

Data Availability Statement

ACTIONS

PERMALINK

RESOURCES

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