How is flexible electronics advancing neuroscience research?

Yihang Chen; Nicholas J Rommelfanger; Ali I Mahdi; Xiang Wu; Scott T Keene; Abdulmalik Obaid; Alberto Salleo; Huiliang Wang; Guosong Hong

doi:10.1016/j.biomaterials.2020.120559

. Author manuscript; available in PMC: 2022 Jan 1.

Published in final edited form as: Biomaterials. 2020 Dec 2;268:120559. doi: 10.1016/j.biomaterials.2020.120559

How is flexible electronics advancing neuroscience research?

Yihang Chen ^a,^c,^†, Nicholas J Rommelfanger ^b,^c,^†, Ali I Mahdi ^a,^c,^†, Xiang Wu ^a,^c,^†, Scott T Keene ^a, Abdulmalik Obaid ^a,^c, Alberto Salleo ^a, Huiliang Wang ^d,^*, Guosong Hong ^a,^c,^*

PMCID: PMC7856293 NIHMSID: NIHMS1651171 PMID: 33310538

Abstract

Innovative neurotechnology must be leveraged to experimentally answer the multitude of pressing questions in modern neuroscience. Driven by the desire to address the existing neuroscience problems with newly engineered tools, we discuss in this review the benefits of flexible electronics for neuroscience studies. We first introduce the concept and define the properties of flexible and stretchable electronics. We then categorize the four dimensions where flexible electronics meets the demands of modern neuroscience: chronic stability, interfacing multiple structures, multi-modal compatibility, and neuron-type-specific recording. Specifically, with the bending stiffness now approaching that of neural tissue, implanted flexible electronic devices produce little shear motion, minimizing chronic immune responses and enabling recording and stimulation for months, and even years. The unique mechanical properties of flexible electronics also allow for intimate conformation to the brain, the spinal cord, peripheral nerves, and the retina. Moreover, flexible electronics enables optogenetic stimulation, microfluidic drug delivery, and neural activity imaging during electrical stimulation and recording. Finally, flexible electronics can enable neuron-type identification through analysis of high-fidelity recorded action potentials facilitated by its seamless integration with the neural circuitry. We argue that flexible electronics will play an increasingly important role in neuroscience studies and neurological therapies via the fabrication of flexible neuromorphic computing elements and the development of enhanced methods of neuronal interpenetration.

Keywords: Brain-machine interfaces, Electrophysiology, Chronic interface, Optogenetics, Neuron-type specificity

1. Introduction

The eminent physicist Freeman Dyson describes the relationship of tool development and scientific discovery in his famous quote: “New directions in science are launched by new tools much more often than by new concepts. The effect of a concept-driven revolution is to explain old things in new ways. The effect of a tool-driven revolution is to discover new things that have to be explained” [1]. This is as much true for neuroscience as it is for physics. One of the earliest examples of a tool-driven biological discovery is the bimetallic arch, which was used by Italian scientist Luigi Galvani in the late 18^th century to stimulate the sciatic nerve of a frog, ushering in the field of bioelectronics and electrophysiology [2]. Several decades later, Ramón y Cajal adopted Golgi’s method for sparsely labeling neurons, leading to the birth of modern neuroscience [3]. More recently, the tungsten microwire electrode developed by Hubel introduced the era of single-neuron recording in live animals, significantly advancing the study of sensory systems by revealing the neural responses to visual stimuli [4]. To further reveal the underlying workings of the neuron, Neher and Sakmann’s patch clamp technique allowed for measurement of the physiological behavior of individual ion channels and intracellular action potentials [5]. To extend neuroscience beyond the capabilities of conventional electrical methods, modern optical stimulation and recording techniques were developed (e.g., optogenetics and calcium/voltage imaging methods [6,7]), opening a new branch of orthogonal approaches for manipulating and monitoring single-neuron activity. Based on this rich history of neuroscience advances, one can reasonably predict that future technological developments, especially those in electrical, optical, and genetic engineering, will bring unprecedented opportunities for neuroscience research.

Akin to the philosophical paradoxes that plagued physics in the first half of the twentieth century, modern neuroscience is advanced by complementary and successive paradigms of increasing complexity and sophistication. These paradigms continue to be validated with improved neuroengineering tools [8]. For example, neural network models have challenged the conventional Cajalian viewpoint of the neuron doctrine, largely owing to the emergence and maturation of multi-neuronal recording methods [9]. Moreover, the Hubelian approach that passively associates external stimuli (e.g., vertical or horizontal gratings on a screen) with internal neural representation (e.g., simple cells in the primary visual cortex) offers an outside-in approach, which arguably produces an incomplete understanding of brain computation. In contrast, an inside-out framework argues for the importance of understanding the brain from within, asking how the brain’s outputs, reflected by the subject’s actions, influence incoming signals [8]. Large-scale neural recording techniques have revealed local and brain-wide neuronal rhythms as pre-existing internal dynamics, supporting the “inside-out” view of the brain [10]. Therefore, emerging neuroscience questions call for new technologies to facilitate the conception and validation of new scientific paradigms for understanding the brain.

Flexible electronics is a research field that takes advantage of advanced structural and functional material designs to minimize mechanical mismatch when interfacing with biological tissues, in particular, soft neural tissue. In light of the history of neuroengineering and existing challenges in neuroscience, flexible electronics offers unique opportunities for neuroscientists. In contrast to its rigid counterpart, flexible electronics uses materials with a lower bending stiffness (thus resulting in greater mechanical compliance), bringing the mechanical properties of these devices closer to those of the interfaced neural tissue [11,12]. These ‘tissue-like’ electronic devices minimally perturb the endogenous environment in the brain, thus enabling both monitoring and stimulation of the brain in its most native state [12,13]. This minimal disturbance to the brain’s intrinsic signaling pathways and biochemical milieu has been independently validated by several groups [14–18]. Motivated by these advantages, we discuss in this review the open question of how flexible electronics continues to address current and future neuroscience challenges (Table 1). We first define the term “flexible electronics” and briefly survey its historical development, in particular, the recent trends of endowing stretchability to these electronic devices. We then discuss how flexible electronics is advantageous for addressing the problems of modern neuroscience in the following four dimensions (Fig. 1):

Chronic stability. Flexible electronics can engage with neural activity at multiple timescales, ranging from single-unit action potentials of millisecond duration to extended periods of months and years to understand circuit evolution in development, learning and memory, and aging.
Interfacing multiple structures. Flexible electronics can conform to multiple structures of the nervous system, providing unique capabilities to access regions of the brain, the spinal cord, peripheral nerves, and the retina that are difficult or impossible to interface with conventional electrical neural probes.
Multi-modal compatibility. Flexible electronics can facilitate multiple modalities of neural interfacing, offering simultaneous optogenetic and chemogenetic/pharmacological neuromodulation, calcium/voltage imaging, and functional magnetic resonance imaging (fMRI) along with electrical recording and stimulation.
Neuron-type-specific recording. Flexible electronics can differentiate between multiple neuron types in single-neuron recording, a capability commonly afforded in calcium/voltage imaging but missing in conventional electrophysiological techniques.

Table 1.

Representative examples of flexible electronics facilitating neuroscience research.

Example	How the example contributes to neuroscience research				Dominant materials	Flexibility (effective bending stiffness/pN*m)	Stretcha bility (strain)	References
Example	chronic recording or stimulation	interfacing structures	modalities	neuron-type-specific recording	Dominant materials	Flexibility (effective bending stiffness/pN*m)	Stretcha bility (strain)	References
Neuron-like electronics (NeuE)	√	brain	electrical	√	SU8	140 ^**		[22]
Mesh electronics	√	brain, retina	electrical		SU8	50–150		[16,23,68,108,109]
Macroporous nanoelectronic 3D FET neural probes		brain	electrical		SU8	91.4 ^**		[15]
Stretchable mesh nanoelectronics	√	organoid	electrical		SU8	90–1900	30%	[80]
Nanoelectronic thread (NET) electrodes	√	brain	electrical		SU8	100–600^*		[17]
Microthread electrodes (MTEs)	√	brain	electrical		carbon fibre	1.22×10⁷ ^*		[18]
Multifunctional fiber	√	brain, spinal cord	electrical, optical, biochemical	√	polycarbonate (PC)	~7×10⁷^*	~100%	[67,159,164,165]
Morphing electronics (MorphE)	√	sciatic nerve	electrical		viscopla stic polymer	5.76×10⁴ (at a strain rate of 50% s⁻¹)^*	>100%	[82]
Soft and elastic hydrogel-based microelectronics	√	sciatic nerve	electrical		PEDOT hydrogel	2.67×10³ ^*	20%	[101]
NeuroRoots	√	brain	electrical		parylene C	776 ^*		[86]
Neurotassels	√	brain	electrical, optical		polyimide	717 ^*		[87]
Polymer electrode array	√	brain	electrical		polyimide	5.83×10⁵ ^*		[88,185,212]
Neuralink	√	brain	electrical		polyimide	not reported		[186]
Climbing-inspired twining electrodes		sciatic nerve	electrical		polyurethane shape memory polymers	1.11×10⁶ ^**	stretchable	[94]
Stretchable low-impedance electrode	√	sympathetic nerve	electrical		PDMS	4.83×10⁴ ^*	40%	[96]
Multi-electrode softening cuffs (MSC)	√	peripheral nerves	electrical		thiol-ene/acrylate shape memory polymer	1.24×10⁶ ^*		[97]
Flexible cuff-like microelectrode	√	vagus nerve	electrical		parylene C	1.18×10⁵ ^*		[98]
NeuroGrid	√	brain	electrical		parylene C	1.47×10⁴ ^*		[10,99,115]
Electronic dura mater (e-dura)	√	spinal cord	electrical, biochemical		PDMS	1.73×10⁵ ^*	20%	[100]
3D-printed soft neural probe	√	brain	electrical		PDMS	not reported		[102]
Wireless, implantable biooptoelectronics system	√	bladder afferent	electrical, optical		PDMS, epoxy, stainless steel, SiC, InGaAs	not reported	25%	[105]
Fluidic-microactuation-delivered carbon nanotube fiber (CNTf) microelectrodes		brain	electrical		CNT fiber	1.92×10⁷ ^**		[110]
Flexible, high-resolution multiplexed electrode array		brain	electrical		polyimide	5.60×10⁶ ^**		[114]
Biohybrid polyimide sieve electrode	√	peripheral nerves	electrical		polyimide	2.13×10⁵ ^*		[124]
Wireless bioresorbable electronic system	√	sciatic nerves, spinal cord	electrical		PLGA	1.73×10⁷ ^*		[126]
Self-unfolding flexible microelectrode array		model of retina	electrical		PDLLA blends	4.84×10⁶ ^*		[129]
soft optoelectronic device		model of retina	electrical		polyimide	572 ^*		[130]
Argus II retinal prosthesis system	√	retina	electrical		polyimide	not reported		[131]
Fully organic retinal prosthesis	√	retina	electrical		silk	not reported		[135]
Organic electrochemical transistor arrays for monitoring neurotransmitters		brain	biochemical		PET	1.33×10⁹ ^*		[140]
Wireless optofluidic neural probe	√	brain	optical, biochemical		PDMS	not reported		[155,157,158]
Wireless opto-electro neural interface (WOENI)	√	brain	electrical, optical		polyimide	not reported		[166]
Transparent graphene microelectrode array		brain	electrical, optical		PET	2.08×10⁷ ^*		[174]
Transparent and flexible low noise graphene electrodes		brain	electrical, optical		polyimide and SU8	6.95×10⁶ ^*		[169]
Graphene-based, carbon-layered electrode array (CLEAR)	√	brain	electrical, optical		parylene C	3.59×10⁶ ^*		[170,171]
Stretchable transparent electrode arrays		brain	electrical, optical		PDMS	4.83×10⁴ ^*	50%	[175]
Transparent nanomesh microelectrodes	√	brain	electrical, optical		parylene C and SU8	6.44×10⁵ ^*		[176,177]
Soft and MRI compatible CNT fiber electrodes	√	brain	electrical, magnetic		CNT fiber	1.58×10⁵		[179]
Flexible nanopipettes		brain	electrical	√	borosilicate	2.51×10⁻² ^* (tip)		[213]
Neuropixels (reference)	√	brain	electrical		Si	1.10×10⁸ ^*		[113]
Optetrode (reference)	√	brain	electrical, optical		silica	2.83×10¹⁰ ^*		[162]
Axon (reference)	N/A	N/A	N/A	N/A	Microtubules	0.6–130^*	65%	[228–230]

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Indicates the effective bending stiffness is calculated by k ∝ Et³;

^**

Indicates the effective bending stiffness is calculated by k ∝ K/w, where w is the width of the device;

Figure 1. — Flexible electronics is advancing neuroscience research in four dimensions: recording neural activity with chronic stability, accessing multiple structures of the nervous system, encompassing different modalities of neural interfacing, and offering the potential to differentiate diverse neuron types.

2. Flexible and stretchable electronics

To define flexible and stretchable electronics, we look at the three key characteristics of the substrates and electronic components of the platforms: soft, bendable, and stretchable [19].

The word ‘soft’ speaks to the low elastic moduli of the materials used in flexible electronics (Fig. 2). The elastic modulus (E), sometimes referred to as Young’s modulus, is an intensive property of a material defined as the ratio of the stress (σ) to the strain (ε):

E = \frac{σ}{ε}

(1)

Therefore, the elastic modulus measures the ability of a particular material to resist the change (increase or decrease) in its length under tensile or compressive force, respectively [20]. Materials with lower elastic moduli are considered ‘softer’, since less force is required to produce the same change in size. A commonly used material in conventional rigid neural probes is silicon, which has an elastic modulus of 150 GPa [11]. In contrast, the elastic modulus of brain tissue is on the order of 100 Pa to 10 kPa, 7 to 9 orders of magnitude softer than silicon. This difference in elastic modulus means that brain tissue will experience much smaller stresses when interfacing with softer materials than with rigid materials under the same amount of induced strain (Fig. 2).

Figure 2. — Dominant materials used in flexible electronics for neuroscience research and their corresponding Young’s moduli.

The degree to which a structure is bendable is represented by the resistance during bending, which is quantified by its bending stiffness (Table 1). Bending stiffness is the extensive measure of the ability of a structure to deform or conform to a curvilinear surface under an applied force, depending on both the elastic modulus of the material and the geometrical features of the structure [21]. The effective bending stiffness (k) can be expressed in terms of the elastic modulus (E) and the thickness (t) of the structure in the direction of bending as follows [20]:

k \propto E t^{3}

(2)

As a reference, a 1–6 μm thick axon has an effective bending stiffness of 0.6 to 130 pN·m (normalized against its width) [22], which is orders of magnitude lower than that of the Michigan-type silicon MEA, which is close to 10⁹ pN·m [21,23]. Since bending stiffness is proportional to the elastic modulus and the third power of material thickness, a lower elastic modulus of the constituent material or a thinner device structure results in more bendable electronics. Benefiting from the scalability and reproducibility of the mature semiconductor industry, a common method for fabricating flexible electronics is to make ultra-thin devices with micro- and nano-fabrication technologies [24]. From a mechanical perspective, flexibility can be imparted to either the electrodes or the entire electronic circuit. On one hand, the electrodes sit at the front end of the neural interface and are directly implanted in the tissue, thereby requiring increased flexibility to improve chronic stability. On the other hand, the rest of the electronic circuit is usually part of the back end and can be placed outside of the brain. However, any portion of the electronic circuit in direct contact with the neural tissue needs to be made sufficiently flexible to afford a chronic, biointegrated interface. In general, decreasing the bending stiffness of the interfacing region induces a lower stress on adjacent neural tissue [25], which has been found to improve adherence and integration of the neural probe with the targeted neural tissue [26]. Specifically, a meta-analysis study has assessed the mechanical properties of multiple neural probes and their corresponding histological outcomes, validating the correlation between bending stiffness and the severity of the immune response: the lower the bending stiffness of the device, the less tissue response it induces [26]. Therefore, flexible electronics with low bending stiffness opens unprecedented opportunities in achieving chronic brain-machine interfaces, as discussed specifically in section “3. Flexible electronics engages with the neural activity at multiple timescales” below.

Flexible electronics can also be made stretchable, maintaining high levels of performance, reliability, and integration of electronic components under elongation (Table 1). Such stretchability can be achieved by two conceptually different strategies: materials innovation and structural design [27]. From a materials perspective, stretchability refers to either reversible, linear elastic responses or plastic deformation without fracture of the material under large strains [27–31]. A variety of elastomeric and ductile materials, such as rubbery conductors, semiconductors, and dielectrics [32] have been adopted in fabricating functional stretchable electronics. From a structural perspective, stretchability can also be achieved with geometrical designs [29]. For example, planar patterns, such as serpentine structures [33–36], fractal designs [37,38], and origami/kirigami assembly [39,40] can effectively distribute global strain via geometrical openings. Another approach for distributing the strain during stretching is to introduce out-of-plane displacements (i.e., buckling [41,42]) by fabricating devices on prestrained substrates. According to the bonding geometry of functional devices, such mechanical designs can be further divided into wavy (with ribbon-like interconnects) [43,44] and island-bridge (with bonded rigid functional units and buckling interconnects) [45]. One area where stretchability is of particular importance is in the context of developing tissues/organs (where plastic deformation without fracture is important) and those in constant motion such as the neuromuscular junction (where elastic deformation with reversibility is important).

Over the past decades, researchers have taken advantage of flexible electronic materials for a wide variety of bio-interfacing devices. Early developments in flexible electronics have emerged from advances in wearable electronics because of the relatively easy access to the skin [19,46]. Well recognized by both academia and industry, wearable electronics focuses on incorporating a variety of functional units including flexible sensors [47,48], logic units [49], circuits [50], displays [51] and actuators [52], to achieve a conformal and noninvasive interface with the skin. This interface has allowed for continuous extraction and analysis of biophysical and biochemical information in real time via biofluids such as sweat [53–56], tears [57], and interstitial fluid [58]. Building on the success of wearable electronics, flexible electronics has been extended to implantable devices interfacing with more complex tissues and harsher environments. Owing to their mechanical resemblance to endogenous tissues during bending, compression, and stretching, flexible and stretchable electronics has enabled in-vivo cardiac electrophysiological mapping on a beating heart via intimate and conformal contact with a curvilinear surface that is constantly changing its shape and size [59]. The conformability of flexible electronics additionally offers a versatile strategy for integration with a variety of organs and surgical tools, such as inflatable balloon catheters, which grant facile and reliable access to targeted tissues via minimally invasive approaches [60]. These applications of flexible electronics, however, have only scratched the surface of what is possible. There remains a wide range of opportunities, in particular for the field of neuroscience, where limitations in current technology can be addressed by implementing flexible electronics. We discuss below how the unique advantages of flexible electronics continue to offer unprecedented opportunities for tackling pressing challenges in modern neuroscience research.

3. Flexible electronics engages with the neural activity at multiple timescales

Understanding the complex dynamic processes and evolution of neural circuits over time requires neural probes with the temporal resolution to measure single-unit action potentials, as well as chronic recording and stimulating ability [21,61]. Recordings of single-neuron action potentials are needed to reconstruct circuit-level connectivity and activity, while chronic recordings of single-neuron activity over weeks, months and even years, are necessary to understand the dynamic evolution of neural plasticity during development, learning, memory formation and aging processes [12,62,63]. Therefore, extending tracking of neural activity to months and years at the single-neuron level (~ms action potentials) will be of great use in longitudinal studies in neuroscience [64,65] and facilitate application in clinical medicine [66]. Regarding neural recordings over multiple timescales, we argue for the importance of adopting a rigorous definition of chronic electrophysiological recording as the continuous tracking of the same neurons over an extended period of time. Chronic in-vivo electrophysiological recording of single-unit action potentials should be verified by various physiological indicators, such as spike waveform, spike amplitude, signal-to-noise ratio (SNR), firing rate, stimulus-evoked firing responses, phase locking to theta oscillations, and pairwise spike train cross-correlations [17,21,67,68]. Many factors may contribute to the degradation of neural signals, such as chronic gliosis induced by the mechanical mismatch between the electrodes and tissue, biofouling and erosion of the electrodes, and delamination of the insulating layers [69]. More specifically, the static and dynamic mechanical mismatches between conventional rigid electronics and soft neural tissues usually lead to various deleterious consequences (Fig. 3A) that significantly erode their functionality over long timescales [70]. In addition, the fouling and erosion of electrodes lead to an impedance change and thus a low quality of detected neural signals over time.

Figure 3. — (A) Flexible and rigid electronics evoke distinct tissue responses over long timescales. (B) Stretchable electronics facilitates chronic integration with the growing neural tissue. (C) Flexible and stretchable electronics affords chronically stable interfacing with organs (such as the heart) that exhibit constant mechanical motions.

Flexible electronics helps alleviate many of the chronic stability issues of rigid neural probes, which are discussed below. First, the huge gap in bending stiffness between neural probes and brain tissue inevitably leads to physical displacement of the probe relative to the interfacing neurons during rotational acceleration of the head [71]. Since the spike waveform and amplitude depend on the distance and the relative position between the recording electrode and the firing neurons [72], such displacement would lead to chronic instability of the extracellularly recorded single-unit action potentials [73]. Furthermore, the relative micromotion resulting from these displacements can impose high stress on the neural tissue [70,74], leading to neuronal death. In addition, the long-term functionality of rigid probes can be impaired by the chronic immune response in the brain tissue surrounding the implant [75], such as astrocytes gathering and proliferating around the electrodes to form a glial scar. Specifically, the glial scar can act as a physical barrier, isolating and insulating the implanted neural probes from the surrounding neural tissues, resulting in increased interface impedance and impaired long-term performance [76]. Moreover, glial cells also actively alter the natural behavior of the local neural tissues near the implants, resulting in impaired neuron excitability, depressed synaptic transmission, suppressed network activity and decreased neuron density as the chronic immune response accumulates [77,78]. Such profound glial modulation of the neuronal environment undoubtedly prevents the electrodes from probing neural activity in its natural state in chronic studies. Second, both the initial probe implantation and the long-term presence of the rigid probe inside the brain give rise to the disruption of the blood-brain barrier (BBB). Consequently, the shortage of blood and oxygen delivery, together with the various biochemical molecules infiltrating through the disrupted BBB, could accelerate the chronic neurodegeneration, neuroinflammatory response and biofouling of the electrodes [70]. Third, the bulky nature and the high rigidity of the conventional neural probes also result in a high level of strain on the electronics upon deformation, which eventually leads to early device failure through structural degradations, thus preventing chronic tracking of neural activities [17]. Finally, in addition to the static mechanical mismatch between conventional probes and soft neural tissue, another mismatch is the dynamic contrast between growing or remodeling neural tissue and the unstretchable probes [79]. Conventional brittle devices, which will break under relatively low strain, are thus not suitable for chronically interfacing growing tissues or organs under constant expansion and contraction [19,37,60,80–82]. Fortunately, flexible electronics can avoid many of these issues due to their favorable mechanical properties.

One emerging strategy to address the bending stiffness mismatch is to develop flexible tissue-like electronics with a cellular level footprint [12], which allows it to behave like and move together with the interfacing neural tissues after implantation (Fig. 3A). The three-dimensional (3D), interconnected topology of the neural network necessitates the design of a mesh structure in the flexible electronics for seamless interpenetration between the electronic and neural networks [83]. Besides the topological mimicry of neural tissue, further improvement on the structural design has led to the recent development of tissue-like mesh electronics with the size of electrodes close to that of a neuron soma (10–20 μm) and bending stiffness similar to that of the brain tissue (100 pN·m) [68]. The tissue-like design and the resulting flexibility enabled chronic tracking of single-neuron activity up to 8 months, evidenced by the minimal variations in intrinsic biophysical properties of the recordings. Immunohistology studies revealed the lack of a chronic immune response and the minimal disruption of neural tissue around flexible mesh electronics up to 1 year post-injection by tracking the endogenous distribution of neurons and astrocytes as a function of time post-implantation [16,68]. Furthermore, the minimal thickness of the tissue-like flexible electronics reduces the strain exerted on the probes upon bending deformation, thus preventing device failure due to structural degradation [17,22]. In addition, some existing strategies used for mitigating the degradation (e.g., oxidation) of rigid neural electrodes, such as using inert electrode materials and reducing the electrochemical potential and current on the electrode [84], can also be employed for improving the long-term functional stability of flexible electronics.

The avoidance of BBB disruption during the implantation of flexible electronics with smaller footprints than their more rigid counterparts also contributes to a stable electronics/tissue interface at multiple timescales. Utilizing a temporary engaging mechanism first developed by the Kipke group [85], the implantation of ultraflexible nanoelectronic thread (NET) electrodes left cellular-sized (ca. 10 μm) surgical damage with little bleeding and minimal local leakage of BBB [17]. Furthermore, the implantation methods based on self-assembly via the capillary force have also been shown to prevent local bleeding [86], and chronic recording has been demonstrated in the implanted flexible electronics [86,87]. Rapid implantation of flexible electronics with high channel count across multiple brain regions while avoiding vascular structures has also been demonstrated [85,88,89], with the implanted flexible devices able to continuously record neural activities in a 24/7 manner [88]. Finally, anti-fouling strategies, which were developed to alleviate the degradation of rigid electrodes due to BBB disruption, may also help flexible electronics to achieve sensitive and accurate detection, as well as efficacious stimulation of neural activity in long-term studies [69,90–93].

Another strategy to reduce chronic immune response and improve long-term interfacing and recording at the organ level is via the incorporation of stretchable and compliant designs that allow electronics to conform to the mechanical distortion of neural tissue under constant motion, which we discuss in greater detail in the “4. Flexible electronics conforms to multiple structures of the nervous system” section below [30,94–100]. Additionally, the stretchability and seamless integration into the surrounding tissues of flexible electronics allow the electronic devices to migrate and evolve together with the growing tissues [80]. In a proof-of-concept work, cyborg organoids have been demonstrated by implanting stretchable mesh nanoelectronics into a human cardiac organoid that grew together during organogenesis [80]. We envision that stretchable electronics holds the promising potential of chronic recording of the neural activities during brain development and neuronal differentiation in neonatal animals (Fig. 3B) with minimal interruption of these natural processes, thus providing new insights about the cellular mechanism for differentiation and development.

Despite the continued efforts in developing flexible and stretchable electronics for chronic neural interface, there remain great opportunities in this field, especially in discovering and designing novel biomaterials with long-term stability and reduced mechanical footprint. Particularly, apart from decreasing the size of neural probes, another strategy to address the bending stiffness mismatch is to reduce the Young’s modulus of the electrode materials. Recently, microelectronics comprising electrically conductive hydrogel-based elastic materials with Young’s modulus values in the kilopascal range has been applied for peripheral nerve stimulation [101]. With a Young’s modulus similar to the surrounding tissue, the soft electrodes based on conductive hydrogels dramatically reduced tissue damage and chronic inflammatory responses at the electrode-tissue interface even under recurrent motion. Furthermore, hydrogel-based neural probes can be programmed and fabricated using 3D printing and have been applied for single-unit recording in vivo [102]. The rapid development of intrinsically flexible and stretchable conductive hydrogels suggests new design principles for the next-generation tissue-like electronics for chronic recordings.

Beyond chronic interfacing with neural tissues, flexible and stretchable electronics with tissue-level bending stiffness values is suitable for chronically interfacing with other organs exhibiting constant contraction and expansion (Fig. 3C), such as the heart, muscles, bladder, etc. These organs are innervated by the peripheral nervous system (PNS) and exhibit continuous changes in volume and shape, thereby making it challenging to achieve a chronically stable interface with these organs. These continuous motions include the shrinking and expansion of the heart and bladder, and the contraction and relaxation of the muscle, thus necessitating the stretchability of the electronics, which allows the devices to follow the mechanical motion dynamically. Specifically, stretchable electrodes have been applied to probe cardiac electrophysiology [59,60,95,103,104] or sense the motion of the bladder [105]. Despite the lack of chronic functional stability as demonstrated in these papers, we believe future work can lead to a chronically stable neural interface with the neuromuscular junctions in the peripheral nervous systems where constant mechanical motions have prohibited chronic study of the control of muscles by motor nerve terminals with electronic tools.

4. Flexible electronics conforms to multiple structures of the nervous system

The unique structural designs and mechanical properties of flexible electronics make it ideal for interfacing with different neural structures ranging from ion channels (a few nanometers), neurons (10 μm), organoids (several millimeters), to various organs and nerves in the nervous system (several to tens of centimeters) (Fig. 4A). The brain consists of a highly interconnected 3D network of neurons and non-neuronal cells, such as astrocytes, oligodendrocytes, and microglia [106,107]. In addition, the spinal cord and the retina both feature unique curvilinear surfaces that should be considered for neural interfacing [100,108]. Therefore, any neural interface design, whether at the surface or deeply implanted, must consider strategies to maximize the interfaced volume of neural tissue, minimize the distance between the electrodes and neurons, and minimize the volume of the neural tissue that is displaced or lost as a result of the implant [21]. To this end, flexible electronics offers great potential for interfacing both the 3D neural tissue of the brain and the curvilinear surface of the brain, the spinal cord, peripheral nerves, and the retina.

Figure 4. — (A) Illustration of the corresponding sizes of flexible electronics and biological structures. Adapted with permission from Ref. [22,80,82,99,100,108,213,227]. (B) Neuron-like electronics (NeuE). The green and red colors correspond to neurons and NeuE, respectively. Adapted with permission from Ref. [22]. (C) Schematic showing the elastocapillary self-assembly of a Neurotassel. Adapted with permission from Ref. [87]. (D) NeuroGrid conforms closely to the surface of the brain, enabling the platform to resolve single-neuron action potentials in an ECoG-like setting (scale bar: 1 mm). Adapted with permission from Ref. [99]. (E) Schematic of e-dura implanted in the spinal subdural region of a rat. The e-dura conforms closely to the dorsal surface of the spinal cord. Adapted with permission from Ref. [100]. (F) Wireless bioresorbable electronic system secured to a sciatic nerve. Adapted with permission from Ref. [126]. (G) Morphing electronics wrapped around a sciatic nerve. Adapted with permission from Ref. [82]. (H) An in-vivo image of mesh electronics implanted in a mouse eye and unfolding conformally to the surface of the retina after intravitreal injection. Adapted with permission from Ref. [108]. (I) Schematic of a hemispherically curved image sensor array (CurvIS array) platform in the back of an eye. Adapted with permission from Ref. [130].

4.1. Flexible electronics for interfacing in deep regions of the brain

Flexible electronics is advantageous in forming an intimate interface with the 3D neural tissue by introducing three unique benefits compared to rigid devices. First, the high mechanical compliance and low space occupancy of flexible electronics open up fundamentally new methods for in-vivo delivery of devices with significantly reduced invasiveness and minimized acute damage than its rigid counterparts [15,17,86,109,110]. Second, flexible electronics allows intimate 3D integration with the endogenous neuronal and glial networks, especially when a macroporous structure is adopted into the flexible electronic network, owing to its tissue-like mechanical properties [12]. Third, the combination of the low bending stiffness, neuron-like feature sizes and axon-mimicking aspect ratio of the individual structural components of flexible electronics makes it more compliant to the remodeling process of the neural tissue such as the promotion of the migration of neural progenitors cells [22].

One system that utilizes flexible electronics with tissue-like mechanical properties to form an intimate 3D interface with neural tissue is mesh electronics. Mesh electronics is designed to have structural features on the sub-micron to micron sizescale (comparable to individual neurons), mechanical flexibility on par with that of the neural tissue and, most importantly, macroporous topology that promotes interpenetration of neurons and glial cells without altering their endogenous distribution while facilitating the diffusion of biomolecules [22,109]. The ultraflexibility of mesh electronics allows it to unfold in an aqueous suspension, and thus can be delivered into the brain via a minimally invasive syringe injection method, akin to pharmaceuticals delivery [109]. After injection, a 3D reconstruction of the interface between neural tissue and neuron-like electronics (NeuE), a special form of mesh electronics, reveals a large number of neurons within close proximity of the recording electrodes to afford extracellular measurements of single-neuron action potentials (Fig. 4B) [22]. In addition, the unique structure and mechanics of NeuE afford a favorable scaffold to promote migration and differentiation of neural progenitor cells into the interfaced neural circuits, thus improving the healing and the restoration processes of the interrogated neural tissue to its native state after acute implantation [109]. Therefore, mesh electronics, especially NeuE, provides a unique tool for neuroscience studies as the multiplexity of neural interrogation can be significantly improved to afford recordings of many neurons simultaneously by increasing the number of recording sites distributed in three dimensions after implantation [23].

Another approach for 3D flexible electronic platforms is to utilize biomimetic multi-channel neural implants that share similar dimensions, mechanical flexibility, and spatial distribution as axon bundles in the brain [86,87]. One such system, NeuroRoots, which is designed with sub-micron features, has a bending stiffness equivalent to a human axon, and offers a unique method of delivery that benefits from its advantageous structural and mechanical properties and limits the invasiveness of the surgical procedure. This highly flexible neural probe was used to measure single-neuron action potentials with a high SNR in the CA1 region of the hippocampus in freely moving animals as a result of the 3D integration of the flexible electronics with the neural tissue [86]. Importantly, NeuroRoots allows the operators to use established infrastructure such as standard connectors for interfacing with recording instrumentation, which makes the platform highly accessible [86].

Like NeuroRoots, the Neurotassels probe consists of flexible microelectrode filaments with a high aspect ratio, which can spontaneously assemble into thin implantable fibers via elastocapillary interactions (Fig. 4C). Neurotassels have been implanted into the medial prefrontal cortex (mPFC) of the mouse brain using a minimally invasive delivery method based on a tissue-dissolvable polymer [87]. Immunohistochemical staining and fluorescence images of brain slices confirmed that neurons are in close proximity with the implanted Neurotassels. This, along with the minimally invasive delivery of Neurotassels, allows for high-quality recording of neural activity [87]. Similar to the mesh electronics and the NeuroRoots, Neurotassels demonstrate a unique ability of flexible electronic platforms – the ability to integrate with the complex 3D network in the brain composed of neurons, astrocytes, and microglia.

Recently developed strategies to couple the rigid complementary metal-oxide semiconductor (CMOS) chips for high-throughput electrical connection of large-scale MEAs [111] could enable highly multiplexed interfaces between neural tissues and flexible electrodes. We envisage that these unique advantages of NeuroRoots and Neurotassels may aid in recording multiple brain regions simultaneously after implantations in different sites of the brain. This multisite recording capability could afford large-scale neural population recordings across the brain for answering key neuroscience questions, such as the spatial distribution of neurons underlying various rodent behaviors, as recently demonstrated by the Neuropixels probe and the massively parallel microwire arrays [111–113].

4.2. Flexible electronics for interfacing on the surface of the brain

Besides integrating with the 3D volume of the neural tissue, flexible electronics can also conform to the curvilinear shape of the brain surface and allow for high-fidelity electrocorticographic (ECoG) recordings. Its flexible nature has enabled these electronic platforms to conformally coat the curved surface of the brain and access rarely explored cortical areas, such as the interior of the sulci [114]. While traditional ECoG arrays usually measure local field potentials (LFPs) on the surface of the brain, it has been a challenge to achieve single-neuron recordings with this platform [63]. Malliaras et al. reported a conformable ECoG platform that utilizes parylene as a flexible substrate, as well as poly(3,4-ethylenedioxythiophene) polystyrene sulfonate (PEDOT:PSS) electrodes to reduce impedance [115]. To achieve single-neuron recordings, the same authors took an alternative approach in a different study. By reducing the electrode size to roughly the size of a single neuron, the authors demonstrated that the NeuroGrid platform is capable of recording both single-neuron action potentials as well as LFPs with high spatial resolution across the cortical surface (Fig. 4D) [99]. In addition to recording superficial cortical neurons alone [99], NeuroGrid was also employed to analyze hippocampal-neocortical communication in conjunction with a silicon probe as the depth electrode [10]. This unique capability to record single-neuron activity in an ECoG array is attributed to the mechanical conformation of the platform to the curved brain surface, which results in an intimate electrical coupling between the neuron-sized recording electrodes and cortical neurons. This close coupling, as achieved by NeuroGrid, is critical for resolving individual neurons due to the fact that the recorded extracellular action potential amplitude is inversely proportional to distance [116]. We anticipate that the conformability enabled by flexible electronics will soon be utilized in clinical settings as well, such as recording signals and synthesizing audible speech by decoding the kinematic and sound representations encoded in human cortical activity [117,118].

4.3. Flexible electronics for interfacing the spinal cord

In addition to applications in the brain, flexible electronics can be used in the spinal cord to improve motor control after injury. Flexible electronics is particularly suitable for interfacing the spinal cord, which has a curvilinear surface and is in constant motion in vivo. Specifically, a pioneering study that demonstrated how flexible electronics can address these challenges is the electronic dura mater (“e-dura”) [100]. E-dura mimics the mechanical properties of the dura mater and consists of thin elastic metal interconnects, electrodes that comprise a platinum-silicon composite and are capable of delivering electrical stimulation and recording electrophysiological signals, and a fluidic microchannel that can deliver drugs locally (Fig. 4E) [100,119–121]. One can envision combining e-dura with the recently demonstrated, targeted spinal cord stimulation neurotechnologies, which restore the ability of walking in humans via timed electrical stimulation [122], for translational applications with superior biointegration properties and lower immune response compared to state-of-the-art implants.

4.4. Flexible electronics for interfacing peripheral nerves

The peripheral nerves, with their small diameters and thus high curvature, also require highly conformal electronic platforms for intimate neural interfacing. A variety of electrodes, such as the transverse intrafascicular multichannel electrode (TIME), longitudinal intrafascicular electrode (LIFE), cuff electrode, and the sieve electrode, have been developed to interface the peripheral nerves, yet with the long-standing trade-off between invasiveness and selectivity [123,124]. Since there is limited space for surgery in the PNS, reducing the steps of surgical procedures is useful for studies involving the peripheral nerves. The Rogers group proposed bioresorbable electronics for potential uses in biomedical applications [125]. Recently, the same group developed a bioresorbable flexible electronics system for improving muscle activation and enhancing neuroregeneration through electrical stimulation, providing a nonpharmacological, bioelectric form of therapy for various tissues and organ systems (Fig. 4F) [126]. Future studies on the peripheral nerves may benefit from bioresorbable electronics as it will allow for fewer invasive surgical procedures.

Another consideration for the peripheral nerves is that they rapidly expand and are in constant motion. The Bao group’s platform, consisting of conductive elastomeric arrays, was able to achieve intimate electrical coupling with electrogenic neural tissue [101]. This intimate coupling allowed the authors to apply ultralow voltages (50 mV) while still yielding effective stimulation of the sciatic nerve [101]. In a more recent work, morphing electronics with tissue-like elastic modulus and negligible stress at a low strain rate demonstrated the self-healing ability that facilitates the formation of a reconfigurable and seamless interface with the sciatic nerve (Fig. 4G) [82]. The biocompatible flexible electronics mentioned above is particularly useful for peripheral nerve interfacing, owing to its ability to conform to their curvilinear surfaces while in motion.

4.5. Flexible electronics for interfacing the retina

Flexible electronics can also function as retinal prostheses by conforming to the curvilinear surface of the retina, which undergoes constant saccadic motion [127]. Mesh electronics is an excellent platform for the retinal interface and has been injected into the vitreous body of the eye, followed by unfolding and coating the curved retina to achieve highly multiplexed recordings of individual retinal ganglion cells (RGCs; Fig. 4H) [108]. The small bending stiffness allows the mesh electronics to unroll in the eye and conformally coat the curved surface, while the high macroporosity allows transmission of the incoming light. In a more recent study, this technology enabled chronic tracking of physiological changes of different RGC types following optic nerve crush, revealing dramatic differences in their resilience to injury [128]. In addition to recording single RGC activity, it is also desirable to electrically stimulate the retina via an intimate electrode/tissue interface. One such platform leverages “smart materials”, which are proposed to precisely control the shape of the electronics through a shape-recovery mechanism, with the aim of achieving stable and reliable electrical stimulation [129]. Based on a shape memory polymer (SMP), this platform introduces a minimally invasive flexible microelectrode array with self-unfolding characteristics that allows for conformal retinal interfacing and stimulation. These “smart materials” may have the capacity to inspire future adaptive stimulation and recording capabilities.

Combining both sensing and stimulation in the retina, another study demonstrated the ability to detect optical signals and apply programmed electrical stimulation to the retina accordingly in live rats [130]. In this study, the Kim group reported a human eye-inspired soft optoelectronic device that incorporates a hemispherically curved array of high-density optical sensors and electrical stimulators (Fig. 4I). This platform showed minimal mechanical disturbance to the eye model and has great potential to be used for epiretinal prostheses. A similar flexible substrate hosting an array of stimulating electrodes has been used in a commercial retinal prosthesis, Argus II of Second Sight, in which the electrical stimulus is programmed based on the processing of camera-captured images [131]. Besides this epiretinal prosthesis, the subretinal prosthesis converts incoming light locally in a silicon-based photovoltaic device array, as has been developed by the Palanker group [132–134]. A fully organic version of the subretinal prosthesis, which comprises a flexible and highly conformable silk substrate covered with photoactive layers of conjugated polymers, has been used to restore vision in a rat model of degenerative blindness [135].

The unique mechanical properties of flexible electronics open up promising opportunities for addressing challenges in several different structures of the nervous system. Flexible electronics can integrate seamlessly with the 3D brain tissue for deep-tissue implantations, conform to the surface of curvilinear surfaces in the nervous system, and achieve intimate electric coupling with structures that are in constant motion.

5. Flexible electronics facilitates multiple modalities of neural interfacing

Multimodal neural interfaces that extend beyond electrical measurement and/or stimulation are preferred for modern neuroscience studies. Although historically interrogation and modulation of the brain were commonly performed with purely electrical methods [84,136], the brain itself is not solely electric in nature. Much of the brain’s communication is achieved via chemical mechanisms, such as the release of neurotransmitters across synapses to communicate with neighboring cells [137] or neuromodulation of populations of neurons via vesicle or hormone secretion [138]. Consequently, the detection and delivery of biochemicals that alter the brain’s natural signaling has become a useful tool in neuroscience research [139,140]. At the very least, flexible and multifunctional neural interfaces combining electrical stimulation and recording plus pharmacological modulation can serve as a powerful tool for dissecting the function of neural circuits and providing therapies for neurological disorders [141]. To improve the specificity of stimulation, optogenetics was developed to achieve optical stimulation of subsets of neurons and/or other cells through labeling with light-sensitive opsins or fluorescent indicators [142]. By transducing cells to produce light-sensitive ion channels (i.e. opsins), optogenetic techniques allow high specificity to cell type/population when compared to electrical and pharmacological methods, while maintaining high temporal precision [143–145]. Similarly, chemogenetics can target specific neuron populations by the genetic introduction of engineered proteins that respond exclusively to exogenous ligands, allowing an additional axis for neuromodulation [146–148]. Finally, to offer feedback during modulation, technologies such as calcium imaging [149,150], voltage imaging [151,152] and fMRI [153,154] have been developed. As optical imaging is orthogonal to electrical recording/stimulation, these modes allow for the detection and stimulation of neural activity across multiple axes, each giving a unique set of information about the neural activity. Thus, a flexible and multifunctional neural interface combining these modalities while minimizing cross-modal interference can leverage the sum of technological innovations in chronic neuromodulation and recording, leading to previously unattainable developments in the field.

5.1. Flexible platforms to integrate pharmaceutical delivery with optoelectronic devices

The targeted delivery of pharmaceuticals to the brain is a powerful modality in neuroscience research, providing insights into the function of brain circuits, and offering opportunities for the treatment of neurodegeneration [155]. As mentioned above, pharmaceuticals delivered into the brain can be one of two cases: pharmacological drugs that alter the brain’s natural chemical signaling and thus the neural activity, and pharmaceuticals that exclusively activate corresponding designer receptors. Flexible electronics reduces or eliminates many of the problems that plagued previous experiments requiring pharmacological delivery, as the biochemical environment in the local neural tissue is sensitive to gliogenic implants. For instance, the metal cannulas typically used to deliver pharmaceuticals into the brain cause chronic immune responses due to their high bending stiffness [156]. To overcome this issue, flexible microfluidic probes have been fabricated from polydimethylsiloxane (PDMS) [155,157,158] or polymer fibers [67,159]. Furthermore, the footprint of drug delivery systems can limit an animal’s mobility and distort its natural behavior [156]. Wireless, lightweight, head-mounted microfluidic devices allow for untethered behavioral experiments, in which stimulation protocols are sent to the device via infrared light [157], radiofrequency fields (Fig. 5A) [158], or Bluetooth technology (Fig. 5B) [155]. Furthermore, validation of the effects of pharmaceuticals on local neural activity is greatly simplified by the use of multimodal probes. Combined pharmacological and optoelectronic probes allow for single-surgery delivery of viral vectors for optogenetic transfection and subsequent optical stimulation and electrical recording to confirm changes in firing behavior in transfected neurons [67,159]. These devices have allowed for electrophysiological measurements of potentials evoked by optical stimulation of ChR2 transfected mice, plus the reduction of such activity upon local delivery of 6-cyano-7-nitroquinoxaline-2,3-dione (CNQX), an α-amino-3-hydroxy-5-methyl-4-isoxazole propionic acid (AMPA) receptor antagonist [159]. Additionally, the effects of D-2-amino-5-phosphonovalerate acid (APV), an N-methyl-D-aspartate (NMDA) receptor antagonist, were confirmed by observing that an increase in locomotion in response to 4 Hz optical stimulation of the dorsal hippocampus subsequently returned to baseline after the release of APV, even though the optical stimulation continued [158]. When pharmaceutical delivery is combined with optoelectronic techniques in a single device, the domain of testable hypotheses in neuroscience dramatically increases.

Figure 5. — (A) A wireless optofluidic device with a flexible microfluidic probe demonstrating simultaneous micro-LED illumination and fluid delivery into a brain tissue phantom. Adapted with permission from Ref. [158]. (B) Schematic demonstrating ‘plug-n-play’ replacement of drug cartridges in a wireless, flexible optofluidic implant, which simplifies the process of refilling the microfluidic reservoirs. Adapted with permission from Ref. [155]. (C) Exploded view of a flexible, modular, optoelectronic device incorporating a Pt recording electrode, a micro-inorganic photodetector (μ-IPD), four micro-inorganic light-emitting diodes (μ-ILEDs), and a temperature microsensor. An epoxy microneedle releases after assisting with implantation, leaving behind a 20 μm thick integrated device (bottom). Adapted with permission from Ref. [163]. (D) Left, thinning of a polymer preform into a flexible optoelectronic and microfluidic fiber probe, accomplished via a thermal drawing process. The completed fiber is shown wrapped around a finger in the inset. Right, cross-sectional images of two multimodal probe designs, each incorporating polycarbonate (PC) optical waveguides, conductive polyethylene (CPE) recording electrodes, and cyclic olefin copolymer (COC) for light confinement in PC. Adapted with permission from Ref. [159]. (E) Bright-field image of an implanted transparent graphene microelectrode array for simultaneous electrical recording and optical stimulation. The flexible microelectrodes are not visible, but gold wires for interfacing with amplifiers are visible (scale bar: 500 μm). Adapted with permission from Ref. [174]. (F) Top, schematic of a transparent bilayer-nanomesh (NM) electrode array for simultaneous electrical recording and optical imaging. Bottom left, bilayer-nanomesh electrode, imaged with an optical microscope. Bottom right, SEM image of a bilayer-nanomesh electrode, zoomed-in on the superimposed green box in the microscope image at left. Adapted with permission from Ref. [177]. (G) Left, SEM image of a CNT fiber used as a flexible, MRI compatible electrode. The twisting angle θ influences the fiber’s electrical and mechanical properties (scale bar: 2 μm). Middle, diagram of a rat’s head showing implantation of a CNT fiber and a PtIr microwire. Right, T2-weighted MRI image (horizontal section) of an implanted CNT fiber (red box) and a PtIr microwire (blue box) of similar diameter. Zoomed-in photographs of the boxes are shown in the insets (inset scale bars: 1.5 mm). Adapted with permission from Ref. [179].

5.2. Optogenetic stimulation and electrical recording enabled by flexible electronics

Flexible electronics allows the simultaneous use of electrical and optical techniques to dissect the complex neural circuitry by optogenetic stimulation and electrical readout of neural activity. Although ‘all-optical electrophysiology’ offers measurements of firing across large spatial scales [6,160], this method suffers from crosstalk between excitation and emission light and is limited by the penetration depth of visible light [161]. The use of flexible, transparent electronics enables recordings of extracellular potential with high temporal resolution and, when inserted into the brain, can eliminate depth limitations. Furthermore, combining optical probes with flexible electronic systems can simplify experiments designed to record the local response to optogenetic stimulation. Although not a flexible electronic design itself, the Optetrode laid the conceptual groundwork for future flexible optoelectronic probes [162]. Consisting of an optical fiber surrounded by four nickel-chromium tetrodes, the Optetrode led to the first electrophysiological recording of the effects of optogenetic inhibition in freely moving mice. In addition to recording an expected decrease in firing rate in most cells, an increase in firing rate for some cells was also measured upon inhibitory illumination, demonstrating the underlying complexity present in such networks. To improve the conformability of optoelectronic probes, the Bruchas group and the Rogers group designed an ultrathin (20 μm) injectable probe comprised of stacked functional layers made via semiconductor fabrication techniques [163]. This highly flexible device integrated four micro-light emitting diodes (LEDs), a single Pt recording electrode, a micro-photodetector, and a temperature sensor (Fig. 5C). Optical stimulation of tyrosine hydroxylase 1 (TH-1) positive dopaminergic neurons transduced to express ChR2 led to conditioned place preference, and the device’s flexibility enabled toleration in vivo for several months. To further reduce the footprint of hybrid optical/electrical implants, Anikeeva et al. developed an electrophysiological recording circuit paired with a waveguide for optogenetic stimulation in an all-polymer fiber formed via a thermal drawing process (Fig. 5D), implanted in both the brain [67,159] and the spinal cord [164,165]. The low bending stiffness of the fiber resulted in a decreased immune response relative to traditional microwire electrodes, which is particularly desirable for chronic optogenetic modulation with electrophysiological feedback [159]. Later, implantable polyimide substrates supporting metal electrodes and four micro-LEDs enabled ECoG recording in response to light [166]. The split design of the flexible, wireless device allowed for bilateral stimulation and recording, and optogenetically evoked potentials were measured in the primary visual cortex (V1) for 21 days after implantation. As discussed, the utilization of flexible electronics for implantable optoelectronic systems has facilitated chronic combined optical and electrical stimulation and recording.

5.3. Transparency and MRI compatibility afforded by reduced materials usage in flexible electronics

The reduced size and the use of transparent and tissue susceptibility-matching materials in flexible electronics imposes less attenuation and distortion of impinging photons and applied magnetic fields than its bulkier and more rigid counterparts, thus leading to greater accommodation of simultaneous electrophysiological recording and optical/magnetic imaging. Performing simultaneous optical stimulation and electrical recording requires transparent devices in order to effectively deliver light (and receive sufficient light in the case of imaging). Although transparent electrodes have previously been fabricated from indium tin oxide [167], the brittleness of this material limits its suitability in vivo [168]. The development of transparent (transmittance ≈ 90% over visible and NIR wavelengths) graphene electrodes on flexible substrates allowed for in vitro [169] and in vivo [170,171] recordings of electrical activity during optical irradiation, albeit with significant photoelectric artifacts [172,173] for the latter device. Later, artifact-free two-photon imaging was achieved in vivo with the graphene electrode array (Fig. 5E) via thorough photoresist removal and graphene surface cleaning [174]. To improve the strain tolerance of transparent electrodes, graphene was replaced with web-like carbon nanotube (CNT) electrodes, which accommodate mechanical deformations via structural reorientation due to maintained contact between neighboring CNTs [175]. This strategy may prove useful for continuous in-vivo neural recordings carried out with electrical and optical means simultaneously during traumatic brain injury studies, where impacts cause rapid deformation of tissue and electrodes [175]. Another flexible, transparent alternative to graphene or carbon nanotube electrodes are bilayer-nanomesh electrodes, typically fabricated by electroplating PEDOT:PSS onto gold nanomeshes (Fig. 5F) [176,177]. Although gold is conducive to photoelectric artifacts and these nanomesh devices are less transparent than graphene electrodes (70% transmittance at 550 nm), the devices offer over 20 times lower impedance than graphene electrodes of the same surface area [176,177]. Despite the lower transparency than graphene electrodes, the PEDOT:PSS-coated gold nanomesh devices afford simultaneous two-photon calcium imaging of single neurons while offering high-fidelity electrical recording in the mouse visual cortex due to their ultra-low impedance [177]. In addition to optical imaging, fMRI has become a powerful tool to measure activity across the brain [153,154], but the difference in magnetic susceptibility between tissue and typical electrode materials (PtIr, Au) causes artifacts that obscure fMRI images near the electrodes [178]. Flexible electrodes fabricated from carbon nanotube fibers (Fig. 5G) [179] demonstrated decreased fMRI artifact size compared to standard PtIr electrodes. The CNT fiber electrodes were ultra-flexible, although this necessitated the use of a shuttle device for implantation, which brings additional acute damage [179]. The low attenuation and distortion of optical and magnetic signals offered by flexible electronics have enabled combined chronic electrical recording and imaging, allowing for simultaneous monitoring of activity across disparate spatial scales in the brain.

5.4. Looking towards multiplexity in flexible multimodal devices

To further benefit neuroscience studies, multimodal flexible electronic devices should aim to reproduce the multiplexity found in existing rigid devices [21]. Multi-shank implants incorporating recording electrodes and micro-LEDs have been demonstrated with rigid devices [180]. Although stiff in nature, optoelectronic devices with integrated optical waveguides offer single-unit electrophysiological recording [181] combined with multicolor [182] or multi-site [183] optogenetic stimulation. Recently, rigid silicon nitride (SiN) waveguide implants have demonstrated precise localization of optical stimulation by using grating emitters to direct up to eight light beams, instead of using micro-LEDs with limited spatial resolution due to incoherent emission [184]. These devices are capable of generating multi-neuron spike patterns with frequencies up to 200 Hz, and neighboring recording electrodes can be included in the fabrication. If combined with recent work in polymer neural probes [88,185,186], multi-site waveguide photonic circuits in flexible electronic platforms should be attainable.

6. Flexible electronics offers the ability to differentiate multiple neuron types

6.1. Electrical recording can be neuron-type-specific

A final unique advantage of flexible electronics for neuroscience studies is its potential for neuron-type-specific electrophysiology, a long-sought goal for neural recording technologies. Dissecting the structure and function of the brain and the complex circuits it comprises requires categorizing and analyzing neurons of different types based on their diverse and distinct molecular, morphological, connectional, and functional properties [187]. Over the past decades, advances in genetic engineering, as well as optical interrogation and modulation, have demonstrated their power to “carve the brain at its joint” by singling out a particular neuron subtype for stimulation or recording [188–190]. For example, optogenetics enables precise deconstruction of the complex neural circuits by genetically targeted expression of the light-sensitive ion channels (e.g., ChR2) and the orthogonality of light to the endogenous signal transduction pathway in the nervous system (see discussion in the section “5. Flexible electronics encompasses multiple modalities of neural interfacing” above). Therefore, unlike non-specific electrical stimulation that activates or suppresses nearby neurons without selectivity, optogenetic stimulation even in a divergent and diffuse manner can achieve neuron-type-specific modulation while sparing the remaining non-transduced neurons without opsin expression [188]. Other than selective optogenetic modulation, selective optical readout of activities from identified neuron types via genetic encoding offers another dimension in dissecting the functionalities of targeted neurons in their encompassing neural circuitry [191–193]. Despite the demonstrated advantages, optical neural manipulation and interrogation technologies have their own limitations [161]. Due to the nature of photon scattering in brain tissue, the penetration depth of light significantly limits the volume of neural tissue that can be accessed by optogenetics and neural activity imaging. Moreover, the slow response kinetics of calcium indicators, including genetically encoded calcium indicators (GECIs), further limits the temporal resolution and prohibits the measurement of single action potentials from each individual neuron [193].

We argue that conventional electrical neural interfacing methods, such as intracellular and extracellular electrophysiological recording techniques [21], can offer new opportunities for cell-type-specific monitoring of neural activity, especially with the help of flexible electronics. As the gold standard for electrophysiology, the patch clamp technique can electrically isolate a single targeted neuron or a single ion channel for in-situ recordings of its electrical behavior, unveiling the cellular or subcellular biophysics of the brain [194,195]. Extracellular recording, given its unique capability for large-scale recordings via multiple channels, offers additional information in reconstructing the interactions between neurons on the circuit level [63,196]. Although traditionally viewed as a technology without neuron-type specificity, in-vivo electrophysiological recording has already started to afford neuron-type-specific information in the recorded data, based on the molecular, morphological, electrophysiological, and connectional perspectives (Fig. 6A) [187,197].

Figure 6. — (A) The four criteria to classify and identify different neuron types. (B) A flexible nanopipette enables in-vivo patch clamp recording and simultaneous visualization of recorded neurons of a known type. The inset represents the recorded signals from the flexible patch clamp. (C) Neuron-like electronics enables multi-channel in-vivo electrophysiological recording and post-mortem two-photon imaging of the electronics/tissue interface for identification of specific neuron types based on triangulation. The inset represents simultaneously recorded signals from the two electrodes, where action potentials produced by the same putative neuron are connected with vertical dashed lines. (D) Multifunctional flexible polymer fibers enable simultaneous optogenetic stimulation (blue shade) and electrophysiological recording of specific neuron types. The left inset shows optical stimuli (blue ticks) and simultaneous electrical readout (black trace). The right inset shows genetically encoded light-gated ion channels. (E) Multifunctional flexible electronics incorporating microfluidic channels is expected to resolve neuron-type information via chemogenetic modulation (red shade) and simultaneous electrophysiological recording. The left inset shows designer drug injection (red line) and simultaneous electrical readout (black trace). The right inset shows the designer receptor exclusively activated by designer drugs (DREADD). (F) “Growing” conducting polymer electrodes (blue filaments) from genetically encoded neurons toward a host electrode is anticipated as another potential approach to realize neuron-type specific in-vivo electrophysiology. The left inset shows the recorded neural signals. The right inset shows electropolymerization of conducting polymers on the surface of genetically encoded neurons driven by an external electrical field. In D-F, ‘extra’ and ‘intra’ indicate the extracellular and intracellular space of the neuron, respectively.

Recent technologies have enabled neuron-type identification and labeling in the brain. First, neurons in the brain can be classified according to their molecular signatures, such as protein and mRNA composition. For example, aspirating the cell content for single-cell RNA-sequencing following whole-cell patch clamping (Patch-seq) offers post-hoc identification of the molecular profile of the very neuron recorded [198–200]. Besides, by genetically expressing “switches” in neurons of specific types via corresponding promoters, optogenetics [201] and chemogenetics [146,202] can selectively modulate particular types of neurons at will and simultaneously record their electrophysiological response in a more causal manner [162,203]. Second, empowered by the morphological characterization of neuron structures by Ramón y Cajal, neurons can be anatomically named and defined based on their location in the nervous system and geometric shape, including dendrite and axon sizes and distributions [187]. This criterion can aid the classification of electrically recorded neurons either by reconstructing the shapes of pre-stained neurons from multiple brain slices or by iontophoretic dye labeling after intracellular or juxtacellular patch clamping [197,204–206]. Third, electrophysiological signals of single-neuron action potentials can serve as the criterion in identifying neurons of specific classification [207]. Given the maturity of spike sorting, feature extraction and clustering, extracellular action potential signals can be clustered into independent spiking units (putative neurons) with distinctive or even iconic spike waveforms and firing patterns [63,116]. For example, extracellular action potential waveforms can be used to sufficiently identify regular spiking pyramidal neurons and parvalbumin-positive fast-spiking basket cells within the brain without visualizing the neurons directly [208,209]. Last, taking advantage of large-scale multi-channel extracellular recordings, identifying neural connections allows extraction of the topological relationship between neurons [210]. Since extracellularly recorded spike amplitude is a function of the distance between the firing neuron and recording electrode, the relative spatial location can be identified by triangulation, which may support the morphological criterion in cellular classification. In addition, since the short latency time in the spike trains between paired neurons implies the putative monosynaptic connection [207,211], the recorded single units from different electrodes can be used to reveal their temporal correlation and underlying cellular interactions with neuron-type information (e.g., excitatory vs. inhibitory neurons), therefore retroactively identifying their neural functions in the circuit.

6.2. Unique strengths of flexible electronics for neuron-type-specific recording

With the four criteria identifying neuron types and supported by recent advances in electrophysiology, we envisage that the unique strengths of flexible electronics facilitate neuron-type-specific electrophysiology. These unique strengths, which have been discussed in previous sections, are elaborated below to justify the use of flexible electronics for in-vivo neuron-type-specific recording.

First, the chronic recording stability of flexible electronics allows neuroscientists to chronically track the activity of the same neurons in the context of their encompassing circuits, as discussed in the section “3. Flexible electronics engages with the neural activity at multiple timescales” above. This unique advantage of flexible electronics facilitates neuron-type-specific recording based on spike waveforms, firing patterns, relative locations of putative neurons and their connectivity patterns verified via reproducible measurements in chronic studies (based on the 3^rd and 4^th criteria in section 6.1 above).

Second, the seamless interface of flexible electronics with different neural tissues enables spatial proximity between recording electrodes and recorded neurons, as discussed in the section “4. Flexible electronics conforms to multiple structures of the nervous system” above. This unique strength leads to a higher SNR, a larger interfaced volume of neural tissue, and less perturbed dynamics of interconnected neural activity than conventional electrical neural probes. As a result, flexible electronics permits more accurate measurement of single-unit firing activity from a larger volumetric neural network, thus facilitating neuron-type-specific recording based on the 4^th criterion in section 6.1.

Third, the multi-modal compatibility of flexible electronics offers versatile platforms for synergistically identifying different neuron types along with optogenetics and chemogenetics (see discussion in the section “5. Flexible electronics encompasses multiple modalities of neural interfacing” above). Genetically expressed “switches” driven by specific promoters can be “phototagged” or “chemotagged”, allowing easy identification of the firing activity of these neurons by electrical recording (based on the 1^st criterion in section 6.1). Similarly, genetically expressed luminescent labels driven by specific promoters allow for imaging the morphology of individual neurons recorded by flexible electronics, thus satisfying the 2^nd criterion in section 6.1.

Besides these unique strengths, flexible electronics can also afford large-scale recording with multiplexity matching or even surpassing its rigid counterparts (e.g., Neuropixels with 384 channels). For example, a 1024-channel flexible neural probe was developed by the Frank group in 2019 by integrating polymer electrodes with a modular stacking headstage design [88]. Moreover, compared to conventional neural probes with only single-sided recording, flexible electrodes can achieve dual-sided recording, which can significantly increase the sampled volume of neural tissue and the number of recorded neurons [212]. According to the 4^th criterion in section 6.1 on neural recording in the context of topological circuit connections, the significantly increased multiplexity of flexible electronics also contributes to neuron-type-specific recording, in addition to the other demonstrated advantages. Below we discuss the latest examples and potential approaches of in-vivo neuron-type-specific electrophysiology via flexible electronics (Fig. 6 and Table 1).

6.3. Examples of flexible electronics for neuron-type-specific recording

Flexible electronics can be combined with real-time or post-mortem fluorescence imaging techniques to offer information on the specific neuron type of each recorded cell. Using fluorescent proteins to specifically label parvalbumin-positive (PV) interneurons, real-time fluorescence imaging guides the access to and intracellular recording of PV interneurons with a fluorescent quantum dots (QDs)-labeled flexible nanopipette (Fig. 6B). Owing to the bending stiffness similar to that of soft atomic force microscope (AFM) tips, flexible nanopipettes could be statically and dynamically adjacent to specific neurons in the brain without damaging them, thus affording in-vivo patch clamp recording of neurons with specific types identified via both molecular and morphological evidence [213]. In addition to real-time imaging of the recorded neurons, post-mortem fluorescence imaging combined with the triangulation of single-unit recording data on multiple electrodes offers another approach to identify neuron types of the recorded signals. A prerequisite of this approach is that the precise 3D locations of the recording electrodes and the recorded neurons are co-registered in the same imaged volume of neural tissue, which is a challenge for conventional rigid neural probes [214]. The tissue-like mechanical properties of flexible electronics enable it to section together with brain tissue without removing the electrodes before tissue fixation, which is technically challenging for rigid electronics [22]. Taking advantage of these unique features, NeuE uses a barcoded electrode design to spatially resolve each recording electrode with respect to surrounding neurons labeled with endogenous fluorescent proteins. Multi-channel electrophysiology of extracellular action potentials in combination with volumetric two-photon imaging enables determination of the spatial coordinates of spiking neurons by triangulation. These coordinates can then be mapped back to the 3D reconstructed neural tissue image to pinpoint the location, morphology and molecular characteristics (via promoter-driven expression of fluorescent labels) of the recorded neurons (Fig. 6C) [22]. Another benefit offered by the “tissue-like” multi-channel flexible electronics is its functional robustness towards potential electrode failure. Even if the signal is missing from one of the electrodes, the neurons can still be localized and tracked according to the other nearby electrodes due to the 3D interpenetration network of flexible electronics and glia-free interface (the single-unit spike is theoretically distinguishable if the recording electrode is located within a range of ca. 100 μm from the soma of the corresponding neuron [116]).

Besides fluorescence imaging of the neurons of interest for electrophysiological study, multifunctional flexible electronics also allow selective activation of neuron subpopulations of specific types via optogenetic stimulation (‘phototagging’) [7], thus differentiating the recorded spikes of opsin-positive neurons from those of opsin-negative ones [215]. The rationale behind this approach is as follows: each recording electrode can detect the extracellular action potentials from multiple neurons [116], yet only those synchronized with the timed light stimuli can be assigned to a particular neuron type, taking advantage of neuron-type specificity of optogenetics [188]. For example, thermally drawn multifunctional flexible polymer fibers can incorporate an optical waveguide for optogenetic stimulation and multiple recording electrodes for simultaneous electrophysiological recordings, the latter of which reveal the action potentials of ChR2-expressing neurons among many other neurons (Fig. 6D) [67]. Although it has not been demonstrated yet, the combination of neuron-type-specific modulation via chemogenetics and chronically stable flexible electronics with microfluidic channels for biologic delivery may be a promising trend for neuroengineering development and neuroscience research in the following years (Fig. 6E). It should also be noted that besides targeting specific types of neurons, projection-specific electrophysiology can also be realized via the combination of flexible electronics and phototagging approaches, taking advantage of the minimal disturbance of tissue-like electronics to the spatial distribution and projections of neurons and neurites [216]. Supported by extensive investigations toward the causality of projection-defined brain dynamics underlying many behaviors and psychiatric disorders, we argue that the combination of projection-specific recording via flexible electronics could become a valuable complementary approach to neuron-type-specific electrophysiology in the ongoing effort to unveil the mysteries of the brain.

6.4. Future outlook of flexible electronics for neuron-type-specific recording

We foresee future opportunities without the need for visualizing or phototagging specific neuron types during recording experiments with flexible electronics. This opportunity is offered by another recent advance in the Deisseroth and Bao labs, which demonstrates neuron-type-specific growth of conducting filaments comprising conjugated polymers [217]. Although completely ‘blind’ neuron-type-specific recordings have yet to be demonstrated, we envisage that the conducting polymers grown out of specific types of neurons could electrically short these neurons with the recording electrodes [218] in the flexible electronic platform (Fig. 6F), thus forming a hybrid bioelectronic system in vivo that exclusively reflects the firing activity of the filament-grafting neurons. In addition, we believe that the development of neuron type-specific recording might be further enriched with longer timescales (see discussion in the section “Flexible electronics engages with the neural activity at multiple timescales” above) utilizing a variety of modalities and accessing different neural structures (see discussion in the sections “Flexible electronics encompasses multiple modalities of neural interfacing” and “Flexible electronics conforms to multiple structures of the nervous system” above) with minimal disturbance of the neural targets.

7. Summary and outlook

As discussed in previous sections, flexible electronics has clearly demonstrated its unique advantages for a plethora of neuroscience studies, owing to the soft mechanical properties on par with the endogenous neural tissue, small feature sizes akin to neurons and neurites, and 3D interconnected macroporous structure similar to that of the neural network (Table 1). These features have offered several benefits, including minimally invasive acute delivery methods for implantation, intimate conformability to various types of neural tissue, chronic stability of device performance, reduced immune response and gliosis, as well as greater compatibility with other neural modulation/interrogation modalities. Therefore, flexible electronics will continue to play an increasingly important role in neuroscience and neurology by encompassing multiple modalities, structures, timescales and neuron-type specificity at the electronics/neural interface (Fig. 7). Furthermore, the low glial response and multifunctionality of flexible electronics are expected to enable entirely new directions for both neuroscience research and clinical applications in neurology. Therefore, fundamentally new studies in neuroscience can be enabled by flexible electronics, such as high-resolution longitudinal studies that track the same neurons over extended periods to investigate long-term brain circuit evolution underlying learning, memory formation and brain aging at the single-neuron spatiotemporal level [12].

Figure 7. — Flexible electronics makes possible a variety of studies that require long-term stability *in vivo*, providing a platform that supports operation across diverse neural structures and incorporates multiple stimulation and recording modalities, all while enabling identification of neuron types via analysis of recorded electrical signals.

Here we highlight two potential directions of flexible electronics for neuroscience. The first is inspired by the need to obtain a minimally invasive, self-accommodating interface that interpenetrates the neural tissue uniformly and monitors neural activity chronically, as required for long-term neuroscience investigations and dependable brain-machine interfaces [219]. Electronics that restructures in changing neural tissue will allow for chronically stable recording and stimulation over previously unattainable timescales. For example, recent advances with morphing electronics in the peripheral nervous system [82] could be applied in the brain. If fabricated in the design of mesh electronics or NeuroRoots, morphing electronics could first interpenetrate the network of neurons and neural progenitor cells and subsequently evolve with growing brain tissue. Such a technology will enable continuous recording throughout the brain’s development, perhaps even in embryos. Further, genetically controlled growth of electronics through neural tissue offers promise for selectively interfacing electrodes with neurons of choice. Genetically targeted growth of conductive polymers has been demonstrated in vitro and in vivo [217], and similar techniques could lead to the controlled growth of conducting polymer networks that interface with recording or stimulation electrodes. The natural production of conductive networks will offer intimate neural interfacing, while also achieving greater neuron-type specificity than has previously been possible with electrical stimulation and recording. Lastly, electronics implanted with a temporary coating that can dissolve the extracellular matrix (ECM) between neurons and glial cells, such as trypsin, will enhance the interpenetration capability of flexible implants through the neuronal network. Ideally, electronics could grow through the newly opened extracellular space before the ECM regenerates around the implant, enabling proximal access to neurons and effectively integrating the implant with native tissue.

Another opportunity for making flexible brain-machine interfaces involves integrating neuromorphic devices. While the current computing paradigm based on conventional von Neumann architecture relies on sequential operations, neurons and synapses rely on parallel, event-driven computation [220]. As traditional hardware architectures are unable to emulate the brain’s ability to process real-world information, neuromorphic devices on flexible substrates have great potential for integrating computation with biological systems to enable new neuroscience studies and clinical applications, most notably for the development of integrated diagnostics on implantable systems [221–223]. In particular, organic transistor-based neuromorphic devices are of great interest for implementing neuromorphic computing in flexible bioelectronics owing to the intrinsically low Young’s modulus of polymers, potential biocompatibility of polymers in vivo, and the ability of simultaneous biosensing and neuromorphic computing in an organic electrochemical transistor (OECT). Recently, electrochemical neuromorphic organic devices were fabricated on a flexible substrate to act as low-voltage artificial synapses [224]. In a different study, a biohybrid synapse with neurotransmitter-mediated synaptic plasticity was constructed by interfacing an organic neuromorphic device with dopaminergic cells [225]. By leveraging the properties of the neuromorphic device, long-term conditioning and recovery of the synaptic weight was demonstrated [225]. In an orthogonal study, a synaptic device was combined with pressure sensors and ring oscillators to construct an artificial afferent nerve and realize a hybrid bioelectronic interface to actuate muscles [226]. By leveraging the unique structural designs and mechanical properties of flexible electronics and the functional properties of neuromorphic devices, the next generation of flexible electronics can emulate both neural structures and functions in an unprecedented way. Whereas the flexible attributes of such device architectures allow the platform to achieve an intimate electrical coupling with neural tissue, the neuromorphic characteristics of such a platform can implement several novel applications towards supplementing, augmenting, or even restoring functionality in the brain.

Acknowledgements

We thank J. R. Sanes for proofreading this paper and giving valuable feedback. This work was supported by a National Institutes of Health (NIH) Pathway to Independence Award (National Institute on Aging 5R00AG056636-04) and Wu Tsai Neurosciences Institute of Stanford University. Some schematics are made in part using BioRender.

Footnotes

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PERMALINK

How is flexible electronics advancing neuroscience research?

Yihang Chen

Nicholas J Rommelfanger

Ali I Mahdi

Xiang Wu

Scott T Keene

Abdulmalik Obaid

Alberto Salleo

Huiliang Wang

Guosong Hong

Abstract

1. Introduction

Table 1.

Figure 1.

2. Flexible and stretchable electronics

Figure 2.

3. Flexible electronics engages with the neural activity at multiple timescales

Figure 3. Flexible electronics engages with the neural activity at multiple timescales.

4. Flexible electronics conforms to multiple structures of the nervous system

Figure 4. Flexible electronics conforms to multiple structures of the nervous system.

4.1. Flexible electronics for interfacing in deep regions of the brain

4.2. Flexible electronics for interfacing on the surface of the brain

4.3. Flexible electronics for interfacing the spinal cord

4.4. Flexible electronics for interfacing peripheral nerves

4.5. Flexible electronics for interfacing the retina

5. Flexible electronics facilitates multiple modalities of neural interfacing

5.1. Flexible platforms to integrate pharmaceutical delivery with optoelectronic devices

Figure 5. Flexible electronics encompasses multiple modalities of neural interfacing.

5.2. Optogenetic stimulation and electrical recording enabled by flexible electronics

5.3. Transparency and MRI compatibility afforded by reduced materials usage in flexible electronics

5.4. Looking towards multiplexity in flexible multimodal devices

6. Flexible electronics offers the ability to differentiate multiple neuron types

6.1. Electrical recording can be neuron-type-specific

Figure 6. Flexible electronics offers the ability to differentiate multiple neuron types.

6.2. Unique strengths of flexible electronics for neuron-type-specific recording

6.3. Examples of flexible electronics for neuron-type-specific recording

6.4. Future outlook of flexible electronics for neuron-type-specific recording

7. Summary and outlook

Figure 7. Opportunities for flexible electronics to advance neuroscience and neurology.

Acknowledgements

Footnotes

References

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