The emergence of electrical activity in human brain organoids

Summary

Human brain organoids, generated from pluripotent stem cells, recapitulate fundamental features of human brain development, including neuronal diversity, regional architecture, and functional network activity. Integrated multimodal and transcriptomic analyses reveal a molecular repertoire of ionotropic receptors supporting action potentials, synaptic transmission, and oscillatory dynamics resembling early brain activity. This review synthesizes current knowledge on the molecular and electrophysiological determinants of neuronal maturation and network computations, from synaptic integration to large-scale dynamics. Ongoing refinements in organoid generation are improving developmental timing and structural fidelity, establishing these models as powerful platforms for investigating brain differentiation, circuit formation, disease mechanisms, and biomedical applications.

This work provides a comprehensive overview of how human brain organoids recapitulate key features of neural network development, with a focus on the emergence of electrical activity. The review synthesizes advances in electrophysiological, imaging, and computational approaches used to study intrinsic excitability, synaptic function, and oscillatory dynamics in brain organoids. It also highlights how these functional readouts enable modeling of neurodevelopmental and epileptic disorders, offering new opportunities for therapeutic discovery.

Introduction

The evolution of 3D brain organoids: From pluripotent stem cells to complex cortical circuits

Human brain organoids are three-dimensional (3D) self-organizing structures derived from pluripotent stem cells (PSCs), designed to recapitulate key aspects of human brain development in vitro. Unlike traditional two-dimensional (2D) cultures, brain organoids exhibit structural and functional properties that more closely resemble human brain tissue, including the presence of diverse neuronal subtypes and rudimentary brain regional architecture (Figure 1A).

Figure 1.

Electrical activity in human brain organoids

(A) Schematic of cortical organoid structure and presence of 4-month-old cortical layer organization.

(B) UMAP plot colored by cell types (Tarhan et al., 2023; Uzquiano et al., 2022). Abbreviations are as follows: CFuPN, corticofugal projection neuron; PN, projection neuron; immature IN, immature interneuron; CPN, callosal projection neuron; oRG, outer radial glia; aRG, apical radial glia; IP, intermediate progenitor.

(C) Feature plot showing the expression of KCN1B gene coding Kv2.1 channel and representative input/output (I/O) line plot showing sodium (INa) and potassium (Ik) currents.

(D) Feature plot showing the expression of SCN2A gene coding Nav1.2 channel and representative firing trace.

(E) Feature plots showing the expression of GABRB1 (GABA(A) receptor subunit beta-1) and GRIA1 (GluA1) and representative traces.

(F) Average GCaMP fluorescence image of cortical organoids and representative calcium traces under basal condition and upon TTX administration.

Different protocols have been developed to generate these models from induced pluripotent stem cells (iPSCs), each tailored to achieve specific structural and functional characteristics. One prominent approach is the generation of whole brain organoids, which are produced using unpatterned protocols that allow for the spontaneous self-organization of diverse brain regions (Lancaster et al., 2013; Quadrato et al., 2017). While this approach successfully recapitulates multiple brain areas allowing for higher cellular diversity, the stochastic nature of self-organization can lead to variability in the representation and arrangement of these regions across different organoids.

To achieve region-specific models, patterned protocols have been developed, employing exogenous signaling factors to guide differentiation toward defined brain areas (Birtele et al., 2024; Tambalo and Lodato, 2020; Wu and Nowakowski, 2025). For instance, protocols have been established to generate organoids representing the cellular diversity of cortical (Sloan et al., 2018; Velasco et al., 2019) (Figure 1B), thalamic (Xiang et al., 2020), spinal cord (Andersen et al., 2020; Faravelli et al., 2025; Lee et al., 2022), striatal (Miura et al., 2020), midbrain (Fiorenzano et al., 2021; Nickels et al., 2020), and cerebellar regions (Atamian et al., 2024; Muguruma et al., 2015). These guided protocols enhance reproducibility, regional specificity, and cellular heterogeneity of the resulting organoids, facilitating targeted in vitro studies of distinct brain areas and supporting disease modeling.

To further refine iPSC differentiation into specific neural subtypes, systematic morphogen screening approaches have been employed. A recent study used a multiplexed screen of morphogens in human neural organoids, leveraging the combinatorial modulation of signaling pathways to enhance both regional and cellular diversity (Amin et al., 2024). Single-cell RNA sequencing (scRNA-seq) data deconvolution uncovered principles of brain region specification, including critical time windows and morphogen combinations that yield highly specialized neuronal subtypes, i.e., tachykinin precursor 3 (TAC3)-expressing striatal neurons (Amin et al., 2024).

Intriguingly, growth factor signaling influences the competency of human iPSCs to differentiate into cerebral organoids (Bertucci et al., 2023; Ideno et al., 2022; Watanabe et al., 2022). Studies indicate that feeder-free iPSCs, especially those derived from patients, may exhibit poor differentiation into cerebral organoids, possibly due to specific epigenetic statuses (Nishizawa et al., 2016; Ortmann and Vallier, 2017; de Souza, 2017). This issue can be mitigated by controlling fibroblast growth factor (FGF) and transforming growth factor β signaling activation at the undifferentiated stage, contributing to a more reliable generation of cerebral organoids (Bertucci et al., 2023).

Beyond individual regions, the development of assembloids represents a significant advancement in recapitulating regional complexity and connectivity. Assembloids, created by fusing region-specific organoids such as dorsal and ventral forebrain spheroids (Xiang et al., 2017), represent a major advancement in modeling brain regional complexity and connectivity, enabling the study of GABAergic neuron migration and excitatory-inhibitory balance in 3D models of neurodevelopmental disorders (Birey et al., 2022; Gomes et al., 2020). In addition, brain assembloids have also been employed to explore long-range connectivity in advanced systems including cortico-motor (Andersen et al., 2020), cortico-thalamic (Patton et al., 2024), cortico-striatal (Miura et al., 2020), midbrain-striatum-cortical (Reumann et al., 2023), cortico-striatal-thalamic-cortical (Miura et al., 2024), and cortico-diencephalic-spinal-sensory (ascending neural sensory pathway) (Kim et al., 2025) assembloids.

Expanding beyond the spatial fusion of organoids, the introduction of connettoids—organoids reciprocally connected via axonal projections—has opened new avenues for modeling bidirectional long-range communication (Kirihara et al., 2019). This concept has been further advanced through the establishment of robust, functional inter-organoid connectivity using engineered microdevices, enabling controlled studies of complex circuit dynamics and inter-organ communication (Osaki et al., 2024).

Beyond regional diversity, novel models of chimeric organoids derived from different donors (Antón-Bolaños et al., 2024; Caporale et al., 2025; Galimberti et al., 2024), namely chimeroids, provide invaluable systems to investigate the interindividual variability in response to shared environmental cues. The advantage of using chimeroids potentially extends beyond the personalized approach, capturing the complexity of biological systems at a large population scale.

Despite the impressive cell-type diversity and accurate regional patterning, brain organoids continue to face the limitation of remaining immature compared to the adult human brain. Seminal 2D approaches have helped uncover molecular and environmental factors that drive neuronal maturation, which are now being applied to 3D systems. For instance, the use of glial co-culture significantly improves structural and functional synapse formation (Christopherson et al., 2005). Additionally, the use of a physiologically optimized culture medium (Bardy et al., 2015), and the combinatorial treatment with neurotrophic factors and small molecules (Hergenreder et al., 2024) accelerate the maturation across multiple parameters in hPSC-derived neurons. Building on these findings, similar strategies have been extended to 3D cultures. In line with 2D data, the incorporation of additional cell types in 3D organoids (Cakir et al., 2019) or transplantation into rodent brains (Mansour et al., 2018; Revah et al., 2022) significantly improve their maturation. Together, these advances mark important steps toward overcoming the developmental arrest typically seen in brain organoid models.

These diverse methodologies underscore the versatility of iPSC-derived organoid technologies in recapitulating the complexity of human brain development and function, offering valuable platforms for studying both health and disease states.

The importance of studying electrical properties and network activity in organoids

Neuronal function depends on generating and propagating electrical signals, which underlie synaptic transmission and network function. Investigating electrical activity in brain organoids involves multiple levels of analysis, from intrinsic neuronal excitability, synaptic plasticity, and network oscillations. These properties serve as biomarkers for neuronal health and as read-outs of how well organoids model in vivo neural networks. Furthermore, evaluating electrical activity is critical for disease modeling, as many neurodevelopmental disorders are associated with altered neuronal excitability (Smith and Walsh, 2020), impaired synaptic function (Bariselli et al., 2016; 2018), or network dysregulation (Del Pino et al., 2018).

While organoid research has primarily focused on decoding the cellular and molecular features of these human models, functional readouts are becoming a timely aspect of organoid characterization. In fact, adult electrophysiological features are tightly linked to molecular profiles (Mancinelli and Lodato, 2018) and ion channel repertoire (Figures 1C–1F), as indicated by neuronal Patch-seq multimodal profiling (Cadwell et al., 2017).

Electrophysiological and imaging techniques offer complementary approaches to studying neuronal activity in brain organoids. Patch-clamp recordings allow for high-resolution measurements in individual neurons enabling researchers to assess intrinsic excitability, action potential firing, and synaptic transmission. In parallel, multi-electrode array (MEA) recordings provide a means to monitor extracellular electrical signals at population scale and are particularly well suited for capturing spontaneous and evoked activity patterns across neural networks. Meanwhile, calcium imaging, typically using genetically encoded calcium indicators, enables the visualization of intracellular Ca²⁺ transients as a proxy for neuronal activity. Calcium imaging can be applied at both the single-cell and population level, allowing researchers to track activity dynamics across multiple neurons over time and to map spatiotemporal patterns of network activation.

This review aims to provide a comprehensive overview of the current understanding of electrical properties and network activity in human brain organoids, highlighting both experimental findings and methodological advances. Here, we will discuss recent evidence on electrical properties, spanning intrinsic properties, synaptic transmission, connectivity, and network oscillations in brain organoids (Table 1). In addition to investigating neuronal properties, we will discuss the most recent evidence highlighting the possibility of studying synaptic plasticity, the molecular signature of learning, in human neural networks. These studies open the exciting possibility of studying pathophysiological network alterations in human models, not limited to neurodevelopmental but also neurodegenerative and neuropsychiatric diseases (Levy and Paşca, 2023).

Table 1.

Electrophysiological signatures of brain organoids and their maturation insights

Organoid type/protocol	Generation/methodology	Key electrophysiological properties	Temporal dynamics	Time point/stage	Advantages/challenges	Ref.
Whole brain organoids	derived from human pluripotent stem cells	measurable sodium and potassium currents at 60 DIV; action potential firing; neurons respond to both glutamate and GABA application	not described	60 DIV	offers insights into human-specific neuronal maturation; variability in intrinsic property data	Lancaster et al. (2013); Quadrato et al. (2017); Logan et al. (2020); Foliaki et al. (2021); Sharf et al., (2022)
Forebrain organoids	derived from human pluripotent stem cells	neurons show reduced membrane resistance and increased capacitance over time; measurable sodium and potassium currents; action potential firing	notable changes between 90 and 120 days in vitro (DIV)	60-80-100–120 DIV	offers insights into functional properties of human-specific neurons	Qian et al., 2016; Watanabe et al. (2017)
Forebrain organoids	derived from human pluripotent stem cells	reduced resting membrane potential over time and increased sag ratio in subsurface neurons compared to superficial	notable changes between 90 and 120 days in vitro (DIV)	90–120 DIV	offers insights into neuronal-specific intrinsic property	Landry et al. (2023)
Hippocampal organoids	3D culture from pluripotent cells; mouse model	progressive membrane hyperpolarization; increased capacitance; higher membrane resistance; TTX-sensitive action potentials	progressive maturation over culture period	11-19-34 DIV	demonstrates clear intrinsic properties; serves as a benchmark for maturation	Ciarpella et al., 2021
Cortical organoids	region-specific protocols for cerebral cortex differentiation	ability to fire action potentials; larger conductances similar to fetal tissue; emergence of network oscillations with AMPAR and GABAR activity	from 2 months (sparse activity) to 6 months (rhythmic 2–3 Hz oscillations)	2–6 months	demonstrates evolving network activity; variability and incomplete intrinsic data can limit interpretation	Trujillo et al. (2019); Paulsen et al. (2022); Park et al. (2024)
Striatal organoids	region-specific protocols for striatal differentiation	inward rectification; hyperpolarized resting potential; delayed firing at high-current injections (SPN features)	observed during neuronal maturation	110/120–160/170 DIV	reproduces key features of striatal neurons	Miura et al. (2020)
Midbrain organoids	region-specific differentiation targeting DA neurons	increased sodium and potassium conductance; emergence of bursting patterns; HCN-like currents; quinpirole sensitivity	maturation phase not explicitly defined	DIV33–50 and 65–84	accurately recapitulates dopaminergic neuron features	Jo et al. (2016); Fiorenzano et al., 2021
Cerebellar organoids	protocols tailored to generate cerebellar structures	development of Purkinje cell-like properties; HCN-mediated currents; complex waveform firing in current-clamp	maturation phase not explicitly defined	108–113 DIV	mimics specific electrophysiological signatures of cerebellar neurons; narrow developmental window	Muguruma et al., 2015; Atamian et al., (2024)
Assembloids (fused organoids)	fusion of region-specific organoids (e.g., cortical, thalamic, and midbrain) to mimic interregional connectivity	evoked EPSCs via electrical or optogenetic stimulation; evidence of synaptic plasticity (LTP/LTD); coordinated network activity across regions	advanced network integration stages; not explicitly time-defined	observed at various integration stages	offers a platform to study interregional neural circuits and plasticity; assembly complexity and integration variability remain challenges	Paşca et al., 2015; Andersen et al. (2020); Miura et al. (2020); Samarasinghe et al. (2021); Patton et al. (2024); Osaki et al. (2024)

Intrinsic membrane properties as maturing features of human brain organoids

A fundamental property of neurons is their ability to rapidly invert membrane voltage polarity and fire action potentials (APs) (Hodgkin and Huxley, 1990) to transmit information across neuronal networks (Buzsáki, 2010). In electrophysiological assessments of brain organoids (Zourray et al., 2022), the first level of analysis focuses on passive membrane properties (Table S1). They are termed passive because they do not involve active conductance mechanisms and include the resting membrane potential (RMP); input resistance (Rin), which reflects the voltage response to steady-state current injections; and membrane capacitance (Cm), which reflects the transient charge movement across the membrane in response to voltage steps (Cheng et al., 2020) (Table S1).

In hippocampal mouse organoids, maturation leads to progressive membrane hyperpolarization, increased Cm, and higher membrane resistance (Rm), which are linked to enhanced K⁺ and Na⁺ currents (Ciarpella et al., 2021). Interestingly, this pattern does not align with the intrinsic postnatal maturation of hippocampal neurons, typically characterized by a progressive decrease in Rin, a gradual loss of hyperpolarization-activated cyclic nucleotide-gated channels (HCN)-mediated currents, and a reduction in overall excitability (Dougherty, 2020; Jones et al., 2024). These discrepancies suggest that brain organoids may model prenatal hippocampal development, complementing postnatal rodent studies. Alternatively, they may reflect regional maturation differences not yet captured by current 3D models (Dougherty, 2020).

A similar phenomenon has been described in human forebrain organoids (Qian et al., 2016), where the maturation of intrinsic neuronal properties follows defined spatial and temporal patterns. In the elegant work published by (Landry et al., 2023), subsurface neurons (deep layer-like) (rather than surface neurons, upper layer-like) show a time-dependent reduction and increase in RMP and Rm, respectively, typical of maturing neurons. This effect likely reflects the developmental sequence of corticogenesis, where deep-layer neurons are born and mature earlier than upper-layer neurons. As in hippocampal organoids, the observed changes in RMP and Rm in cortical organoids are linked to enhanced AP firing (Landry et al., 2023) and Na⁺ and K⁺ conductances (Logan et al., 2020). However, it remains unclear whether these differences persist when considering the inherently asynchronous development of early born deep- and late born upper-layer neurons. Additionally, the prolonged developmental timeline of human neurons compared to other species (Kanton et al., 2019)—that is neoteny—may not be uniformly recapitulated across all neuronal subtypes, limiting the interpretation of such properties across distinct classes of cortical neurons. Future studies employing human-mouse chimeric models may help determine whether these features are intrinsically encoded or modulated by the environment.

Midbrain organoids also exhibit similar maturation of intrinsic properties, with dopamine (DA) neurons showing increased Na⁺ and K⁺ conductances, enhanced Cm, and reduced Rm as they mature (Jo et al., 2016). Notably, the authors observed the emergence of bursting patterns of AP firing, HCN-mediated currents, and heightened sensitivity to quinpirole (a selective DA type-2 receptor agonist), which are typical features of midbrain DA neurons (Mercuri et al., 1995). In addition to displaying typical DA neuron properties, silk-microfiber engineered ventral midbrain organoids are also capable of DA release, indicating the acquisition of mature dopaminergic identity (Fiorenzano et al., 2021).

The first evidence of cerebellar Purkinje-like electrophysiological properties derived from human stem cells demonstrated HCN-mediated currents and the ability to generate APs (Muguruma et al., 2015). These recordings were performed on dissociated cells in 2D culture, which, despite confirming key features, did not reveal spontaneous firing, highlighting the challenge of capturing full maturation outside a 3D environment. Advanced protocols now allow direct recording from Purkinje cells in 3D tissue. By 4–7 months in vitro, PCP2/L7⁺ neurons exhibit hallmark properties—hyperpolarized RMP, spontaneous and evoked firing, HCN-mediated currents, and repetitive activity—indicating functional maturation in a self-organized context (Atamian et al., 2024).

Along the same lines, striatal organoids (Miura et al., 2020) contain neurons with features of mature spiny projection neurons (SPNs) (Kasanetz and Manzoni, 2009), such as hyperpolarized RMP, inward rectification (Table S1), and delayed firing at high-current depolarizing injections (Miura et al., 2020).

The electrophysiological properties of cortical neurons were first evaluated in 3D human cortical spheroids (Paşca et al., 2015). Using an established forebrain differentiation protocol (Kadoshima et al., 2013), Watanabe et al. found that neurons with higher conductance fired APs more reliably, linking the maturation of intrinsic membrane properties to enhanced functional output. Further supporting this, modulation of K⁺ currents enhance Ca²⁺ transient frequency in cortical organoids (Park et al., 2024), reflecting increased neuronal activity.

Developmental changes in intrinsic properties, such as RMP, Cm, Rm, and AP firing, consistently reflect neuronal maturation across brain organoid protocols (Figures 1C–1E). These shifts indicate progressive acquisition of functional traits and mark the transition from immature progenitors (Vitali et al., 2018) to mature neurons capable of network activity, providing a robust readout of in vitro neuronal differentiation.

Acquisition of ionotropic receptor currents regulates neuronal function in organoids

Extra-synaptic and synaptic receptors

Pharmacological manipulation of ionotropic receptors—such as AMPARs, NMDARs, and GABARs (Table S1) —provides a reliable approach to indirectly assess synaptic connections and extra-synaptic receptor function (Figure 1F). Voltage-clamp studies demonstrate that two-month-old human whole brain organoids respond to both glutamate and GABA application with measurable currents, the latter enhanced by propofol, a positive modulator of GABAARs (Logan et al., 2020). These types of experiments provide the proof-of-principle that the expression of ionotropic channel subunits—which can be depicted at single-cell resolution—corresponds to their functional assembly and membrane localization.

In addition to changing membrane potential, modulating ionotropic currents can affect whole-network activity; for instance, application of compounds such as kainate, AMPA, NMDA, and GABA alters bursting event patterns in MEA recordings (Foliaki et al., 2021). Calcium imaging experiments also revealed that glutamate increases the frequency of Ca²⁺ transients in whole brain organoids (Lancaster et al., 2013), while diazepam (a potentiator of GABAARs) decreases single-unit spiking (Sharf et al., 2022). Similarly, bioelectronic delivery of GABA decreases Ca²⁺ transient frequency in cortical organoids (Park et al., 2024). Novel protocols for 3D cerebellar organoids—supplemented with CXCL12, critical to instruct cerebellar foliation via the CXCL12-CXCR4 pathway (Demenego et al., 2025; Huang et al., 2014)—display bursting Ca²⁺ transients, modulated by NMDA and picrotoxin (PTX, a blocker of GABAAR) further suggesting the insertion of GABAARs and NMDARs in the neuronal network (Atamian et al., 2024).

These findings indicate that brain organoids can integrate ionotropic receptors into developing circuits, reinforcing their relevance as models of network function. Monitoring network responses to ionotropic receptor modulation over time offers a practical approach to track network maturation. This has been elegantly demonstrated in 3D cerebellar organoids, where calcium bursts become more pronounced and show increased sensitivity to NMDA and PTX over time (Atamian et al., 2024), reflecting the emergence of maturing electrical properties.

Excitatory and inhibitory synaptic transmission

Recent studies utilized patch-clamp recordings to isolate excitatory postsynaptic currents (EPSCs) to demonstrate the existence of AMPAR- and NMDAR-mediated transmission within cortical (Paşca et al., 2015; Trujillo et al., 2019), midbrain (Jo et al., 2016), and cerebellar (Muguruma et al., 2015) organoids. Additional experiments involving the stimulation of pre-synaptic compartments provided evidence of synaptic patterning. For example, electrical stimulation of cortical or thalamic areas evoked AMPAR- and NMDAR-mediated EPSCs in cortico-thalamic assembloids (Patton et al., 2024). Other optogenetic studies showed that Chrimson induces TTX-sensitive excitatory post-synaptic depolarization in cortico-spinal-muscle assembloids. This indicates that neurotransmitter release relies on pre-synaptic depolarizations following opsin-induced APs (Andersen et al., 2020). A similar optogenetic approach applied to cortico-striatal assembloids demonstrated that 30% of cells in the striatal compartment responded to optogenetic stimulation of cortical regions (Miura et al., 2020). These findings show that different protocols of brain organoids express extra-synaptic and synaptic glutamatergic receptors, highlighting their utility as models for studying excitatory synaptic function and network activity in the developing brain.

In addition to glutamatergic transmission, neurons within dorsal spheroids exhibit spontaneous and evoked inhibitory post-synaptic potentials only when assembled with ventrally derived spheroids (Birey et al., 2017). In the midbrain (Jo et al., 2016) and cerebellar organoids (Muguruma et al., 2015), where GABAergic populations naturally emerge, spontaneous synaptic events can only be abolished upon PTX application, highlighting a GABAergic contribution. These data indicate that specific differentiation or assembly protocols—accounting for presynaptic GABAergic compartments—give rise to local inhibitory microcircuits. However, whether these human models reproduce the vast array of connectivity patterns of inhibitory neuron subtypes (Lim et al., 2018) and their terminal circuit maturation remains to be explored.

While pharmacological manipulations with exogenous ionotropic modulators described previously enable to test—in an unspecific and acute manner—the expression of receptors in the probed system, only the spontaneous synaptic events can reveal functional pre- and post-synaptic coupling. It is envisionable to assess the integration and subunit composition of ionotropic receptors at organoid synapses across multiple time points, tracking whether they recapitulate features of synaptic maturation. In multiple circuits, including VTA dopamine neurons (Bellone et al., 2011), hippocampal glutamatergic synapses (Bellone and Nicoll, 2007), and cortical interneurons (Matta et al., 2013), synaptic maturation is marked by a progressive shift in ionotropic receptor composition. Similar transitions in organoids would provide key evidence of functional synaptic maturation within human-derived models.

Decoding complex network activity in 3D brain organoids

The emergence of population-level activity and oscillations

Electrical activity during prenatal and early postnatal stages is critical for the maturation of different brain regions (Yuste et al., 2024). Brain slices or in vivo two-photon recordings revealed that specific patterns of spontaneous neuronal firing serve as functional indicators of neuronal network development in mice (Luhmann and Khazipov, 2018). In the developing cerebral cortex and hippocampus, sparse, intrinsic Ca²⁺ activity in a small number of cells during embryonic periods evolves into more synchronized, gap junction-mediated activity around birth (Luhmann and Khazipov, 2018). Early Ca²⁺-sensor-based studies revealed the presence of single-neuron activity in organoids (Figure 1G). TTX and glutamate receptor antagonists blocked these transients, demonstrating their entrainment in functional neuronal networks (Lancaster et al., 2013). Since then, population activity has been studied in various settings, including correlated single-unit activity in grafted organoids (Mansour et al., 2018), and coordinated single-cell GCaMP-mediated fluorescence transients in cortical organoids (Watanabe et al., 2017).

High-density microelectrode recordings at different time points captured the concerted activity of neuronal populations in vitro, revealing bursting oscillatory patterns sensitive to NBQX, further suggesting the involvement of AMPAR transmission (Quadrato et al., 2017). Extracellular MEA recordings indicate that cortical organoids develop functional excitatory neurons and exhibit progressively increasing activity over time, as evidenced by enhanced firing rates, burst frequencies, and synchrony (Trujillo et al., 2019). Cortical organoids, but not neural spheroids, display robust network activity that develops over time from rare bursts every 20 s at 2 months, to short 300–500 ms bursts at 4 months, and finally to steady rhythmic activity at 2–3 Hz by 6 months (Trujillo et al., 2019). Although these oscillations resemble immature networks of preterm neonates, they are sensitive to AMPAR and GABAAR blockers, highlighting the functional expression of excitatory and inhibitory receptors in vitro (Trujillo et al., 2019). Building on these findings, cortical organoids generate temporally organized single-unit firing sequences, or protosequences, in the absence of sensory input (van der Molen et al., 2025). These activity patterns reflect a preconfigured temporal structure of AP firing that mirrors early developmental processes in vivo, further establishing organoids as a model to investigate the ontogeny of network-level computations and circuit assembly.

These intrinsic oscillatory dynamics can be further modulated by long-range interactions, as shown in assembloids. For example, when dorsal and ventral forebrain compartments are interconnected, the resulting network displays enhanced gamma oscillations and structured bursting activity, not observable in isolated organoids (Hernandez et al., 2025). This indicates that synaptic integration across regions contributes to the emergence and refinement of cortical-like oscillatory dynamics. Accordingly, studies in murine assembloids have recently shown that fusing region-specific spheroids can reshape network activity and promote the emergence of more complex, synchronized dynamics (Iannello et al., 2025). Notably, hippocampal spheroids that show little organized activity on their own develop robust, theta-range oscillations and reproducible burst motifs only when connected to entorhinal-like regions (Iannello et al., 2025). This enhanced synchrony, reminiscent of in vivo circuits, highlights how inter-regional connectivity can drive functional maturation and memory-relevant activity patterns even in vitro.

As highlighted previously, integrating glutamatergic and GABAergic neurons favors inhibitory and excitatory synapse formation, which might contribute to higher order network oscillations (Samarasinghe et al., 2021). The emergence of different types of oscillatory activities reflects fundamental aspects of circuit maturation and function. Low-frequency oscillations, such as those in the delta and theta ranges, are typically indicative of high network synchronicity, where neurons fire in a coordinated manner. This is characteristic of early developmental stages or of networks with limited inhibitory modulation (Luhmann and Khazipov, 2018). In contrast, the appearance of higher frequency oscillations, such as beta and gamma bands, signifies a more complex and mature network state. These oscillations require precise temporal coordination and are facilitated by the activity of GABAergic interneurons, which exert inhibitory control to sculpt and desynchronize network activity. Notably, such fast oscillations are absent in organoids that predominantly contain excitatory neurons (Paulsen et al., 2022; Revah et al., 2022; Schröter et al., 2022; Trujillo et al., 2019), highlighting the critical role of inhibitory interneurons in generating these dynamic patterns. This can be further demonstrated pharmacologically by applying bicuculline, a GABAAR antagonist (Samarasinghe et al., 2021). As expected, removal of inhibitory drive enhances network synchronicity, leading to the emergence of hypersynchronous bursts. Therefore, the observation of both low- and high-frequency oscillations within organoid networks not only indicates the presence of diverse neuronal subtypes but also reflects the establishment of balanced excitatory-inhibitory interactions that underpin complex information processing in the developing and mature brain (Buzsáki, 2010).

Together, these findings support the notion that functional connectivity across and within brain regions is a critical driver of oscillatory complexity and maturation in organoid models, offering a powerful framework to dissect the principles of circuit assembly and emergent dynamics in human neural development.

Computational approaches to unravel functional complexity

Decoding the intricate electrical activity of brain organoids requires advanced computational tools to manage and interpret the large, complex datasets generated by electrophysiological recordings. To address this challenge, recent studies have introduced novel machine learning-based techniques that can identify and quantify more complex patterns of neuronal interactions and activity. One such approach is CEBRA (computational embedding of brain activity) (Schneider et al., 2023), which uses unsupervised machine learning to extract simpler representations of complex neural activity, referred to as activity embeddings. These embeddings allow researchers to detect significant changes in activity over time, simplifying the analysis and making it easier to identify trends such as maturation and network dynamics.

In addition to CEBRA, MOPED (modeling organoid population electrophysiology dynamics) methods (Roos et al., 2025) have been recently developed to enable automated, unbiased analysis of activity embeddings within the neural organoids. This approach significantly enhances the interpretability and comparability of organoid data, allowing the assessment of how neural populations interact dynamically, how neuronal responses evolve before and after stimulation, and how bursts of activity are organized across time. Using these computational tools, recent findings suggest that organoids exhibit a developmental pattern of activity, mirroring that of brain maturation (Roos et al., 2025). Notably, organoid activity increases with age, and their bursting behavior shows age-dependent differences (Roos et al., 2025). Moreover, when organoids are subjected to pharmacological or electrical stimulation, their activity embeddings undergo significant changes, offering new insights into how organoid networks respond to external perturbations (Roos et al., 2025).

These advanced computational approaches are poised to revolutionize our ability to model human brain activity, improving drug testing, neurotoxicity screening, and disease modeling by providing more accurate, reproducible, and interpretable data from brain organoids.

Advanced organoid models exhibit synaptic and network plasticity signatures

Synaptic plasticity, first identified in the rabbit hippocampus, reflects long-term changes in synaptic strength that enable neuronal adaptations (Citri and Malenka, 2008). While it has been extensively studied in rodent models, it remains difficult to translate to humans due to limited tissue access (Mansvelder et al., 2019). Thus, recent observations of synaptic plasticity in human brain organoids represent a unique opportunity to challenge and refine preclinical findings in human neural networks.

In cortico-thalamic assembloids, both pre/postsynaptic stimulation pairing (spike-timing dependent plasticity) and low-frequency stimulation (LFS) can induce long-term potentiation (LTP) or long-term depression (LTD) of thalamocortical and corticothalamic projections (Patton et al., 2024). These forms of plasticity depend on mGluRs, NMDARs, and postsynaptic calcium signaling. Notably, an exception is LTP at thalamocortical synapses, which occurs independently of NMDARs, suggesting mechanistic divergence across input pathways within these assembloids (Patton et al., 2024). In rodents, by contrast, thalamocortical plasticity requires NMDARs, particularly during critical periods of development (Schlaggar et al., 1993). A similar divergence exists for corticothalamic plasticity: in human assembloids, corticothalamic LTP is blocked by NMDAR and mGluR-I antagonists and abolished by postsynaptic calcium buffering, indicating a postsynaptic, NMDAR-dependent mechanism. In rodents, however, this form of plasticity has a presynaptic locus and is insensitive to both NMDAR and mGluR blockade (Castro-Alamancos and Calcagnotto, 1999). While these discrepancies may reflect developmental stage mismatches, incomplete arealization, or species-specific differences in intracellular signaling, the ability of brain organoids to express enduring synaptic plasticity likely reflects a degree of functional maturation. However, whether this plasticity fully recapitulates the properties of maturing human circuits remains an open question, especially given the prolonged developmental trajectory of human brain networks.

In addition to whole-cell recordings, other authors investigated long-term circuit plasticity by measuring network bursting activity in response to optogenetic stimulation of axon bundles across cerebral organoids. They observed long-lasting entrainment of bursting upon LFS that rapidly subsided, suggesting short-term plasticity (Osaki et al., 2024). Other authors instead obtained long-lasting changes in circuit function upon HFS in bioengineered cerebral organoids. These models containing a mixture of glutamatergic, GABAergic, and glial cells, expressed HFS-induced long- and short-term depression and potentiation of field excitatory postsynaptic potentials (fEPSPs) (Zafeiriou et al., 2020). These observations suggest that enduring plasticity in brain organoids requires complex neuronal integration across different neuronal subtypes or glial cells. They also imply that these 3D models can express various types of plasticity upon specific stimulation patterns, depending on circuit architecture and cell identity of the neuronal and non-neuronal components.

Studying synaptic plasticity in neural organoid networks stands at the forefront of neuroscience research, offering an unprecedented opportunity to investigate the mechanisms of synaptic modifications in human neural circuits. These models not only provide a window into species-specific plasticity but also pave the way for deeper insights into the functional maturation of human synapses, ultimately bridging the gap between preclinical findings and human neurophysiology.

Unraveling circuit dysfunction in neurodevelopmental disorders using brain organoids

One of the most significant contributions of brain organoids to neurodevelopmental disorders (NDDs) research is their use as patient-specific models to uncover cellular and electrophysiological dysfunctions underlying disease phenotypes. A comprehensive and elegant review of neurodevelopmental disorder modeling using brain organoids was recently published by Birtele and colleagues (Birtele et al., 2024), providing an extensive overview of disease-specific approaches and findings in the field. In this context, we highlight only a few representative examples in which functional readouts—particularly electrophysiological phenotypes—played a central role in both characterizing disease states and evaluating potential therapeutic strategies. These cases underscore the utility of brain organoids not only for modeling disease mechanisms but also as robust platforms for drug discovery.

In several NDDs, hyperexcitability has been used as a quantifiable and disease-relevant phenotype in high-throughput screening assays, enabling the identification of compounds capable of pharmacologically rescuing neuronal dysfunction. For example, organoids derived from patients with CDKL5 deficiency disorder (CDD), a severe early-onset epileptic encephalopathy, consistently exhibit increased intrinsic neuronal excitability compared to controls (Negraes et al., 2021; Wu et al., 2022). This hyperexcitability is characterized by a higher frequency of APs with increased amplitude and shorter duration due to faster depolarization and repolarization rates (Wu et al., 2022). These changes reflect underlying dysfunctions in voltage-gated Na⁺ and K⁺ channels, with CDD neurons (and not astrocytes) showing increased current densities and an earlier activation of Na⁺ channels (Wu et al., 2022). Morphological abnormalities in CDD neurons, both in culture or even post transplantation in vivo, further indicate impaired neuronal maturation and connectivity for CDK5 condition (Negraes et al., 2021).

Similar insights have been gained in models of Rett syndrome (RTT), another neurodevelopmental disorder characterized by severe cognitive and motor deficits (Wu et al., 2022). Organoids derived from patients with RTT also display increased neuronal excitability, mirroring many electrophysiological alterations observed in CDD, including enhanced Na⁺/K⁺ current densities and a negative shift in Na⁺ channel activation. While these data might suggest a common molecular mechanism underlying the pathophysiology of early seizures, in contrast to CDD, synaptic function in RTT organoids appears to be largely unaffected (Wu et al., 2022). Electrophysiological similarities across these distinct neurodevelopmental disorders point to shared molecular roots of early seizure susceptibility, while their differences reveal disorder-specific circuit alterations and divergent developmental adaptations.

Brain organoids have been pivotal in modeling Timothy syndrome type 1 (Birey et al., 2022), revealing how a CACNA1C exon 8A gain-of-function mutation disrupts calcium channel inactivation. Importantly, this study enabled the development of antisense oligonucleotides (ASOs) therapies that restored channel function and improved dendritic morphology, demonstrating the promise of targeted molecular interventions (Chen et al., 2024).

These findings further highlight the importance of a comprehensive characterization of both active and passive neuronal properties, as well as network-level functional features. Such an integrative approach is essential for uncovering the molecular underpinnings of each disorder and for identifying effective, targeted therapies. In addition, the transplantation of human cortical organoids into rodent brains enabled in vivo studies of neuronal maturation and circuit integration, providing a critical bridge between in vitro findings and physiological relevance.

Challenges and future directions of brain organoid biology

The rapidly evolving field of brain organoid electrophysiology presents a compelling narrative of progress and promise. As demonstrated, organoids exhibit a remarkable progression in neuronal maturation compared to 2D models—from intrinsic membrane properties and synaptic activity to complex network oscillations and plasticity. These milestones validate organoids as physiologically relevant models of early human brain development and offer novel platforms to investigate disease mechanisms and therapeutic strategies. Acting as a time machine, they enable dynamic tracking of neurodevelopmental processes, helping distinguish causative from adaptive changes in disorders such as infantile epilepsy, autism spectrum disorder, and attention deficit hyperactivity disorder.

Despite challenges such as variability and incomplete maturation, the integration of advanced electrophysiological tools with computational modeling is refining our ability to decode complex neuronal activity and access principle of human brain function, otherwise unattainable. A key innovation is the development of assembloids, created by fusing region-specific organoids (e.g., cortex, thalamus, and midbrain), to reconstruct complex neural circuits that mimic in vivo connectivity. These models facilitate the study of inter-regional interactions and are proving invaluable in modeling disorders linked to dysregulated connectivity, such as amyotrophic lateral sclerosis (ALS) (van der Geest et al., 2024), Parkinson’s disease (PD) (Smits et al., 2019), and spinal muscle atrophy (SMA) (Faravelli et al., 2025).

A complementary strategy, connectoids, establishes long-range axonal connections between spatially separated brain region-specific organoids, providing a platform to study directional inter-regional communication in vitro. While promising, current connectoid systems require further refinement to better mimic axonal biology. Moreover, the physical separation between organoids limits the replication of continuous spatial organization, morphogen gradients, and localized cell-cell interactions essential for in vivo brain development. Enhancing spatial-temporal integration will be key to increasing their physiological relevance.

Given the rapid and transformative progress in brain organoid research over the past decade, it is now conceivable that significant advances will soon emerge not only in modeling complex structures and inter-organ interactions (brain-body assembloids), but also in deepening our understanding of the mechanisms underlying neurological and neurodevelopmental disorders. By integrating brain organoids with other organoid systems that mimic distinct regions of the body (i.e., intestine, thymus, liver, and heart), researchers can gain deeper insights into how organs communicate under both physiological and pathological conditions. Recent innovations, such as the transplantation of assembloids—multi-region or multi-lineage organoid constructs—into in vivo systems, are expanding the scope of functional studies, allowing for the exploration of long-range connectivity, circuit integration, and systemic influences on brain development. In parallel, emerging 3D bioprinting technologies offer unprecedented control over spatial organization and cell-type distribution, enabling the engineering of more physiologically relevant and reproducible organoid systems.

Acknowledgments

This work was supported by ERC Starting Grant IMPACT 101043003 to S.L. and PNRR - CN00000041 to S.L. and S.B.

Author contributions

S.L., S.M., and S.B. conceived and wrote the manuscript. S.B. and S.M. contributed equally to the manuscript. All authors approve the final version of the manuscript.

Declaration of interests

The authors declare no competing interests.