Emergent functional properties of neuronal networks with controlled topology

Engineered modular neuronal networks-on-chip represent structure-function relationship

Brain function is substantially linked to the highly organized modular structure of neuronal networks. However, the structure of in vitro assembled neuronal circuits often exhibits variability, complicating the consistent recording of network functional output and its correlation to network structure. Therefore, engineering neuronal structures with predefined geometry and reproducible functional features is essential to precisely model in vivo neuronal circuits. Here, we engineered microchannel devices to assemble 2D and 3D modular networks. The microchannel devices were coupled with a multi-electrode array (MEA) electrophysiology system to enable recordings from circuits. Each network consisted of 64 modules connected to their adjacent modules by micron-sized channels. Modular circuits within microchannel devices showed enhanced activity and functional connectivity traits. This includes metrics such as connection weights, clustering coefficient, global efficiency, and the number of hub neurons with higher betweenness centrality. In addition, modular networks demonstrated an increased functional modularity score compared to the randomly formed circuits. Neurons within individual modules displayed uniform network characteristics and predominantly participated in their respective functional communities within the same or neighboring physical modules. These observations highlight that the modular network structure promotes the development of segregated functional connectivity traits while simultaneously enhancing the efficiency of overall network connectivity. Our findings emphasize the significant impact of physical constraints on the activity patterns and functional organization within engineered modular networks. These circuits, characterized by stable modular architecture and intricate functional dynamics-key features of the brain networks-offer a robust in vitro model for advancing neuroscience research.

Connectivity and network burst properties of in-vitro neuronal networks induced by a clustered structure with alginate hydrogel patterning

Modularity is one of the important structural properties that affect information processing and other functionalities of neuronal networks. Researchers have developed in-vitro clustered network models for reproducing the modularity, but it is still challenging to control the segregation and integration of several sub-populations of them. We cultured clustered networks with alginate patterning and collected the electrophysiological signals to investigate the changes in functional properties during the development. We built inter-connected neuronal clusters using alginate micro-patterning with a circular shape on the surface of the micro-electrode array. The neuronal clusters were enabled to be connected at 3 or 10 days-in-vitro (DIV) by removing the barrier. The neuronal signals from different types of networks were collected from 16 to 34 DIV, and functional characteristics were examined. Connectivity and burst motif analysis were carried out to find out the relation between the structure and function of the networks. Neuronal networks with clustered structure showed different activity properties from the random networks along the development. The clustered networks had more short-range connections compared to the random networks. In the network burst motif analysis, the clustered networks showed more various patterns and a slower propagation of the activation patterns. In this study, we successfully cultured neuronal networks with clustered structure, and the structure affected the functional properties. The network model suggested in this study will be a good solution for observing the effect of structure on function during their development.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13534-023-00289-5.

Multiple neuron clusters on Micro-Electrode Arrays as an in vitro model of brain network

Understanding the brain functioning is essential for governing brain processes with the aim of managing pathological network dysfunctions. Due to the morphological and biochemical complexity of the central nervous system, the development of general models with predictive power must start from in vitro brain network engineering. In the present work, we realized a micro-electrode array (MEA)-based in vitro brain network and studied its emerging dynamical properties. We obtained four-neuron-clusters (4N) assemblies by plating rat embryo cortical neurons on 60-electrode MEA with cross-shaped polymeric masks and compared the emerging dynamics with those of sister single networks (1N). Both 1N and 4N assemblies exhibited spontaneous electrical activity characterized by spiking and bursting signals up to global activation by means of network bursts. Data revealed distinct patterns of network activity with differences between 1 and 4N. Rhythmic network bursts and dominant initiator clusters suggested pacemaker activities in both assembly types, but the propagation of activation sequences was statistically influenced by the assembly topology. We proved that this rhythmic activity was ivabradine sensitive, suggesting the involvement of hyperpolarization-activated cyclic nucleotide-gated (HCN) channels, and propagated across the real clusters of 4N, or corresponding virtual clusters of 1N, with dominant initiator clusters, and nonrandom cluster activation sequences. The occurrence of nonrandom series of identical activation sequences in 4N revealed processes possibly ascribable to neuroplasticity. Hence, our multi-network dissociated cortical assemblies suggest the relevance of pacemaker neurons as essential elements for generating brain network electrophysiological patterns; indeed, such evidence should be considered in the development of computational models for envisaging network behavior both in physiological and pathological conditions.

Portrait of intense communications within microfluidic neural networks

In vitro model networks could provide cellular models of physiological relevance to reproduce and investigate the basic function of neural circuits on a chip in the laboratory. Several tools and methods have been developed since the past decade to build neural networks on a chip; among them, microfluidic circuits appear to be a highly promising approach. One of the numerous advantages of this approach is that it preserves stable somatic and axonal compartments over time due to physical barriers that prevent the soma from exploring undesired areas and guide neurites along defined pathways. As a result, neuron compartments can be identified and isolated, and their interconnectivity can be modulated to build a topological neural network (NN). Here, we have assessed the extent to which the confinement imposed by the microfluidic environment can impact cell development and shape NN activity. Toward that aim, microelectrode arrays have enabled the monitoring of the short- and mid-term evolution of neuron activation over the culture period at specific locations in organized (microfluidic) and random (control) networks. In particular, we have assessed the spike and burst rate, as well as the correlations between the extracted spike trains over the first stages of maturation. This study enabled us to observe intense neurite communications that would have been weaker and more delayed within random networks; the spiking rate, burst and correlations being reinforced over time in terms of number and amplitude, exceeding the electrophysiological features of standard cultures. Beyond the enhanced detection efficiency that was expected from the microfluidic channels, the confinement of cells seems to reinforce neural communications and cell development throughout the network.

Microenvironments Matter: Advances in Brain-on-Chip

To highlight the particular needs with respect to modeling the unique and complex organization of the human brain structure, we reviewed the state-of-the-art in devising brain models with engineered instructive microenvironments. To acquire a better perspective on the brain's working mechanisms, we first summarize the importance of regional stiffness gradients in brain tissue, varying per layer and the cellular diversities of the layers. Through this, one can acquire an understanding of the essential parameters in emulating the brain in vitro. In addition to the brain's organizational architecture, we addressed also how the mechanical properties have an impact on neuronal cell responses. In this respect, advanced in vitro platforms emerged and profoundly changed the methods of brain modeling efforts from the past, mainly focusing on animal or cell line research. The main challenges in imitating features of the brain in a dish are with regard to composition and functionality. In neurobiological research, there are now methods that aim to cope with such challenges by the self-assembly of human-derived pluripotent stem cells (hPSCs), i.e., brainoids. Alternatively, these brainoids can be used stand-alone or in conjunction with Brain-on-Chip (BoC) platform technology, 3D-printed gels, and other types of engineered guidance features. Currently, advanced in vitro methods have made a giant leap forward regarding cost-effectiveness, ease-of-use, and availability. We bring these recent developments together into one review. We believe our conclusions will give a novel perspective towards advancing instructive microenvironments for BoCs and the understanding of the brain's cellular functions either in modeling healthy or diseased states of the brain.

Rich dynamics and functional organization on topographically designed neuronal networks in vitro

Neuronal cultures are a prominent experimental tool to understand complex functional organization in neuronal assemblies. However, neurons grown on flat surfaces exhibit a strongly coherent bursting behavior with limited functionality. To approach the functional richness of naturally formed neuronal circuits, here we studied neuronal networks grown on polydimethylsiloxane (PDMS) topographical patterns shaped as either parallel tracks or square valleys. We followed the evolution of spontaneous activity in these cultures along 20 days in vitro using fluorescence calcium imaging. The networks were characterized by rich spatiotemporal activity patterns that comprised from small regions of the culture to its whole extent. Effective connectivity analysis revealed the emergence of spatially compact functional modules that were associated with both the underpinned topographical features and predominant spatiotemporal activity fronts. Our results show the capacity of spatial constraints to mold activity and functional organization, bringing new opportunities to comprehend the structure-function relationship in living neuronal circuits.

Comparison of fractal and grid electrodes for studying the effects of spatial confinement on dissociated retinal neuronal and glial behavior

Understanding the impact of the geometry and material composition of electrodes on the survival and behavior of retinal cells is of importance for both fundamental cell studies and neuromodulation applications. We investigate how dissociated retinal cells from C57BL/6J mice interact with electrodes made of vertically-aligned carbon nanotubes grown on silicon dioxide substrates. We compare electrodes with different degrees of spatial confinement, specifically fractal and grid electrodes featuring connected and disconnected gaps between the electrodes, respectively. For both electrodes, we find that neuron processes predominantly accumulate on the electrode rather than the gap surfaces and that this behavior is strongest for the grid electrodes. However, the 'closed' character of the grid electrode gaps inhibits glia from covering the gap surfaces. This lack of glial coverage for the grids is expected to have long-term detrimental effects on neuronal survival and electrical activity. In contrast, the interconnected gaps within the fractal electrodes promote glial coverage. We describe the differing cell responses to the two electrodes and hypothesize that there is an optimal geometry that maximizes the positive response of both neurons and glia when interacting with electrodes.

Long-term morphological and functional dynamics of human stem cell-derived neuronal networks on high-density micro-electrode arrays

Comprehensive electrophysiological characterizations of human induced pluripotent stem cell (hiPSC)-derived neuronal networks are essential to determine to what extent these in vitro models recapitulate the functional features of in vivo neuronal circuits. High-density micro-electrode arrays (HD-MEAs) offer non-invasive recording with the best spatial and temporal resolution possible to date. For 3 months, we tracked the morphology and activity features of developing networks derived from a transgenic hiPSC line in which neurogenesis is inducible by neurogenic transcription factor overexpression. Our morphological data revealed large-scale structural changes from homogeneously distributed neurons in the first month to the formation of neuronal clusters over time. This led to a constant shift in position of neuronal cells and clusters on HD-MEAs and corresponding changes in spatial distribution of the network activity maps. Network activity appeared as scarce action potentials (APs), evolved as local bursts with longer duration and changed to network-wide synchronized bursts with higher frequencies but shorter duration over time, resembling the emerging burst features found in the developing human brain. Instantaneous firing rate data indicated that the fraction of fast spiking neurons (150–600 Hz) increases sharply after 63 days post induction (dpi). Inhibition of glutamatergic synapses erased burst features from network activity profiles and confirmed the presence of mature excitatory neurotransmission. The application of GABAergic receptor antagonists profoundly changed the bursting profile of the network at 120 dpi. This indicated a GABAergic switch from excitatory to inhibitory neurotransmission during circuit development and maturation. Our results suggested that an emerging GABAergic system at older culture ages is involved in regulating spontaneous network bursts. In conclusion, our data showed that long-term and continuous microscopy and electrophysiology readouts are crucial for a meaningful characterization of morphological and functional maturation in stem cell-derived human networks. Most importantly, assessing the level and duration of functional maturation is key to subject these human neuronal circuits on HD-MEAs for basic and biomedical applications.

Stimulus-Evoked Activity Modulation of In Vitro Engineered Cortical and Hippocampal Networks

The delivery of electrical stimuli is crucial to shape the electrophysiological activity of neuronal populations and to appreciate the response of the different brain circuits involved. In the present work, we used dissociated cortical and hippocampal networks coupled to Micro-Electrode Arrays (MEAs) to investigate the features of their evoked response when a low-frequency (0.2 Hz) electrical stimulation protocol is delivered. In particular, cortical and hippocampal neurons were topologically organized to recreate interconnected sub-populations with a polydimethylsiloxane (PDMS) mask, which guaranteed the segregation of the cell bodies and the connections among the sub-regions through microchannels. We found that cortical assemblies were more reactive than hippocampal ones. Despite both configurations exhibiting a fast (<35 ms) response, this did not uniformly distribute over the MEA in the hippocampal networks. Moreover, the propagation of the stimuli-evoked activity within the networks showed a late (35−500 ms) response only in the cortical assemblies. The achieved results suggest the importance of the neuronal target when electrical stimulation experiments are performed. Not all neuronal types display the same response, and in light of transferring stimulation protocols to in vivo applications, it becomes fundamental to design realistic in vitro brain-on-a-chip devices to investigate the dynamical properties of complex neuronal circuits.

Topologically controlled circuits of human iPSC-derived neurons for electrophysiology recordings

Bottom-up neuroscience, which consists of building and studying controlled networks of neurons in vitro, is a promising method to investigate information processing at the neuronal level. However, in vitro studies tend to use cells of animal origin rather than human neurons, leading to conclusions that might not be generalizable to humans and limiting the possibilities for relevant studies on neurological disorders. Here we present a method to build arrays of topologically controlled circuits of human induced pluripotent stem cell (iPSC)-derived neurons. The circuits consist of 4 to 50 neurons with well-defined connections, confined by microfabricated polydimethylsiloxane (PDMS) membranes. Such circuits were characterized using optical imaging and microelectrode arrays (MEAs), suggesting the formation of functional connections between the neurons of a circuit. Electrophysiology recordings were performed on circuits of human iPSC-derived neurons for at least 4.5 months. We believe that the capacity to build small and controlled circuits of human iPSC-derived neurons holds great promise to better understand the fundamental principles of information processing and storing in the brain.

Neurons-on-a-Chip: In Vitro NeuroTools

Neurons-on-a-Chip technology has been developed to provide diverse in vitro neuro-tools to study neuritogenesis, synaptogensis, axon guidance, and network dynamics. The two core enabling technologies are soft-lithography and microelectrode array technology. Soft lithography technology made it possible to fabricate microstamps and microfluidic channel devices with a simple replica molding method in a biological laboratory and innovatively reduced the turn-around time from assay design to chip fabrication, facilitating various experimental designs. To control nerve cell behaviors at the single cell level via chemical cues, surface biofunctionalization methods and micropatterning techniques were developed. Microelectrode chip technology, which provides a functional readout by measuring the electrophysiological signals from individual neurons, has become a popular platform to investigate neural information processing in networks. Due to these key advances, it is possible to study the relationship between the network structure and functions, and they have opened a new era of neurobiology and will become standard tools in the near future.

Interpreting the Entire Connectivity of Individual Neurons in Micropatterned Neural Culture With an Integrated Connectome Analyzer of a Neuronal Network (iCANN)

The function of a neural circuit can be determined by the following: (1) characteristics of individual neurons composing the circuit, (2) their distinct connection structure, and (3) their neural circuit activity. However, prior research on correlations between these three factors revealed many limitations. In particular, profiling and modeling of the connectivity of complex neural circuits at the cellular level are highly challenging. To reduce the burden of the analysis, we suggest a new approach with simplification of the neural connection in an array of honeycomb patterns on 2D, using a microcontact printing technique. Through a series of guided neuronal growths in defined honeycomb patterns, a simplified neuronal circuit was achieved. Our approach allowed us to obtain the whole network connectivity at cellular resolution using a combination of stochastic multicolor labeling via viral transfection. Therefore, we were able to identify several types of hub neurons with distinct connectivity features. We also compared the structural differences between different circuits using three-node motif analysis. This new model system, iCANN, is the first experimental model of neural computation at the cellular level, providing neuronal circuit structures for the study of the relationship between anatomical structure and function of the neuronal network.

Development of the micro-patterned 3D neuronal-hydrogel model using soft-lithography for study a 3D neural network on a microelectrode array. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2021;2021:1234-1237. [PMID: 34891510 DOI: 10.1109/embc46164.2021.9629822]

In vitro patterned neuronal models have been studied as one of the strategies to investigate the relationship between structural connectivity and functional activity of neural network. Despite the importance of three-dimensional (3D) cell models, most of these studies have been performed on two-dimensional models. In this study, we present a technique to construct the micro-pattern to 3D neuronal-hydrogel model using a micromolding in capillaries (MIMIC) technique on microelectrode array (MEA). Our technique was suitable to prevent the deformation of micro-patterned collagen model against the neuronal contracted tension during the network formation. The relationship between the growth directions of glial cells and micro-pattern direction was investigated. Lastly, we confirmed that our 3D model had synchronized activity among neurons in 3D. This model is expected to be used as a tool to study the relationship between structural connectivity and functional activity in the 3D environment.

Spontaneous and Perturbational Complexity in Cortical Cultures

Dissociated cortical neurons in vitro display spontaneously synchronized, low-frequency firing patterns, which can resemble the slow wave oscillations characterizing sleep in vivo. Experiments in humans, rodents, and cortical slices have shown that awakening or the administration of activating neuromodulators decrease slow waves, while increasing the spatio-temporal complexity of responses to perturbations. In this study, we attempted to replicate those findings using in vitro cortical cultures coupled with micro-electrode arrays and chemically treated with carbachol (CCh), to modulate sleep-like activity and suppress slow oscillations. We adapted metrics such as neural complexity (NC) and the perturbational complexity index (PCI), typically employed in animal and human brain studies, to quantify complexity in simplified, unstructured networks, both during resting state and in response to electrical stimulation. After CCh administration, we found a decrease in the amplitude of the initial response and a marked enhancement of the complexity during spontaneous activity. Crucially, unlike in cortical slices and intact brains, PCI in cortical cultures displayed only a moderate increase. This dissociation suggests that PCI, a measure of the complexity of causal interactions, requires more than activating neuromodulation and that additional factors, such as an appropriate circuit architecture, may be necessary. Exploring more structured in vitro networks, characterized by the presence of strong lateral connections, recurrent excitation, and feedback loops, may thus help to identify the features that are more relevant to support causal complexity.

On the road to the brain-on-a-chip: a review on strategies, methods, and applications

The brain is the most complex organ of our body. Such a complexity spans from the single-cell morphology up to the intricate connections that hundreds of thousands of neurons establish to create dense neuronal networks. All these components are involved in the genesis of the rich patterns of electrophysiological activity that characterize the brain. Over the years, researchers coming from different disciplines developedin vitrosimplified experimental models to investigate in a more controllable and observable way how neuronal ensembles generate peculiar firing rhythms, code external stimulations, or respond to chemical drugs. Nowadays, suchin vitromodels are namedbrain-on-a-chippointing out the relevance of the technological counterpart as artificial tool to interact with the brain: multi-electrode arrays are well-used devices to record and stimulate large-scale developing neuronal networks originated from dissociated cultures, brain slices, up to brain organoids. In this review, we will discuss the state of the art of the brain-on-a-chip, highlighting which structural and biological features a realisticin vitrobrain should embed (and how to achieve them). In particular, we identified two topological features, namely modular and three-dimensional connectivity, and a biological one (heterogeneity) that takes into account the huge number of neuronal types existing in the brain. At the end of this travel, we will show how 'far' we are from the goal and how interconnected-brain-regions-on-a-chip is the most appropriate wording to indicate the current state of the art.

Collective dynamics of neuronal activities in various modular networks

Modularity is a key feature of structural and functional brain networks. However, the association between the structure and function of modular brain networks has not been revealed. We constructed three types of modular cortical networks in vitro and investigated their neuronal activities. The modular networks comprising 4, 3, or 2 modules were constructed using polydimethylsiloxane (PDMS) microstructures fabricated directly on a multi-electrode array (MEA) without transfer. The 4-module network had the strongest modular connectivity, followed by the 3-module and 2-module networks. To investigate how neuronal activities were affected by the modular network structure, spontaneous neuronal activities were recorded on different days in vitro and analyzed based on spike amplitudes, network bursts, and the propagation properties of individual spikes. Different characteristics were observed depending on the network topology and modular connectivity. Moreover, when an electrode was stimulated by biphasic voltage pulses, bursts were elicited for the 4-module network, whereas spikes were elicited for the 3-module and 2-module networks. Direct fabrication of the PDMS microstructures on the MEA without transfer allows microscale construction of modular networks and high-density functional recording; therefore, the technique utilizing the PDMS microstructures can be applied to the systematic study of the dynamics of modular neuronal networks in vitro.

Electrophysiology Read-Out Tools for Brain-on-Chip Biotechnology

Brain-on-Chip (BoC) biotechnology is emerging as a promising tool for biomedical and pharmaceutical research applied to the neurosciences. At the convergence between lab-on-chip and cell biology, BoC couples in vitro three-dimensional brain-like systems to an engineered microfluidics platform designed to provide an in vivo-like extrinsic microenvironment with the aim of replicating tissue- or organ-level physiological functions. BoC therefore offers the advantage of an in vitro reproduction of brain structures that is more faithful to the native correlate than what is obtained with conventional cell culture techniques. As brain function ultimately results in the generation of electrical signals, electrophysiology techniques are paramount for studying brain activity in health and disease. However, as BoC is still in its infancy, the availability of combined BoC-electrophysiology platforms is still limited. Here, we summarize the available biological substrates for BoC, starting with a historical perspective. We then describe the available tools enabling BoC electrophysiology studies, detailing their fabrication process and technical features, along with their advantages and limitations. We discuss the current and future applications of BoC electrophysiology, also expanding to complementary approaches. We conclude with an evaluation of the potential translational applications and prospective technology developments.

Micropatterning of Substrates for the Culture of Cell Networks by Stencil-Assisted Additive Nanofabrication

The fabrication of in vitro neuronal cell networks where cells are chemically or electrically connected to form functional circuits with useful properties is of great interest. Standard cell culture substrates provide ensembles of cells that scarcely reproduce physiological structures since their spatial organization and connectivity cannot be controlled. Supersonic Cluster Beam Deposition (SCBD) has been used as an effective additive method for the large-scale fabrication of interfaces with extracellular matrix-mimicking surface nanotopography and reproducible morphological properties for cell culture. Due to the high collimation of SCBD, it is possible to exploit stencil masks for the fabrication of patterned films and reproduce features as small as tens of micrometers. Here, we present a protocol to fabricate micropatterned cell culture substrates based on the deposition of nanostructured cluster-assembled zirconia films by stencil-assisted SCBD. The effectiveness of this approach is demonstrated by the fabrication of micrometric patterns able to confine primary astrocytes. Calcium waves propagating in the astrocyte networks are shown.

Large-scale acoustic-driven neuronal patterning and directed outgrowth

Acoustic manipulation is an emerging non-invasive method enabling precise spatial control of cells in their native environment. Applying this method for organizing neurons is invaluable for neural tissue engineering applications. Here, we used surface and bulk standing acoustic waves for large-scale patterning of Dorsal Root Ganglia neurons and PC12 cells forming neuronal cluster networks, organized biomimetically. We showed that by changing parameters such as voltage intensity or cell concentration we were able to affect cluster properties. We examined the effects of acoustic arrangement on cells atop 3D hydrogels for up to 6 days and showed that assembled cells spontaneously grew branches in a directed manner towards adjacent clusters, infiltrating the matrix. These findings have great relevance for tissue engineering applications as well as for mimicking architectures and properties of native tissues.

Hybrid Interfaces Made of Nanotubes and Backbone-Altered Dipeptides Tune Neuronal Network Architecture

Peptides constituted of backbone homologated α-amino acids combined with carbon materials offer interesting possibilities in the modulation of cellular functions. In this work, we have prepared diphenylalanine β- and γ-peptides and conjugated them to carbon nanotubes (CNTs). These hybrids were able to self-assemble into fibrillar dendritic structures enabling the growth of primary hippocampal cells and the modulation of their neuronal functions. In particular, following the deposition of the different nanomaterials on glass substrates, we have evaluated their effects on circuit function and geometry. The geometrical restrictions due to CNT nucleated nodes allowed growth of neuronal networks with control over network geometry, and exploring its functional impact. In diverse applications from basic neuroscience, the presence of CNT nodes may be exploited in brain interfaces able to convey highly localized electrical stimuli.

Multi-Electrode Array with a Planar Surface for Cell Patterning by Microprinting

Multielectrode arrays (MEAs) are devices for non-invasive electrophysiological measurements of cell populations. This paper describes a novel fabrication method of MEAs with a fully planar surface. The surface of the insulation layer and the surface of the electrodes were on one plane; we named this device the planar MEA (pMEA). The main advantage of the pMEA is that it allows uniform contact between the pMEA surface and a substrate for positioning of microfluidic channels or microprinting of a cell adhesive layer. The fabrication of the pMEA is based on a low adhesive Au sacrificial peel-off layer. In divergence from conventional MEAs with recessed electrodes, the electrodes of the pMEA lead across the sloped edge of the insulation layer. To make this, the profile of the edge of the insulation layer was measured and the impedance of the planar electrodes was characterized. The impedance of the pMEA was comparable with the impedance of conventional MEA electrodes. The pMEA was tested for patterning HL-1 cells with a combination of imprinting fibronectin and coating by antifouling poly (l-lysine)-graft-poly(ethylene glycol) (PLL-g-PEG). The HL-1 cells remained patterned even at full confluency and presented spontaneous and synchronous beating activity.

Instrumented Microphysiological Systems for Real-Time Measurement and Manipulation of Cellular Electrochemical Processes

Recent advancements in electronic materials and subsequent surface modifications have facilitated real-time measurements of cellular processes far beyond traditional passive recordings of neurons and muscle cells. Specifically, the functionalization of conductive materials with ligand-binding aptamers has permitted the utilization of traditional electronic materials for bioelectronic sensing. Further, microfabrication techniques have better allowed microfluidic devices to recapitulate the physiological and pathological conditions of complex tissues and organs in vitro or microphysiological systems (MPS). The convergence of these models with advances in biological/biomedical microelectromechanical systems (BioMEMS) instrumentation has rapidly bolstered a wide array of bioelectronic platforms for real-time cellular analytics. In this review, we provide an overview of the sensing techniques that are relevant to MPS development and highlight the different organ systems to integrate instrumentation for measurement and manipulation of cellular function. Special attention is given to how instrumented MPS can disrupt the drug development and fundamental mechanistic discovery processes.

Chemically Cross-Linked Carbon Nanotube Films Engineered to Control Neuronal Signaling

In recent years, the use of free-standing carbon nanotube (CNT) films for neural tissue engineering has attracted tremendous attention. CNT films show large surface area and high electrical conductivity that combined with flexibility and biocompatibility may promote neuron growth and differentiation while stimulating neural activity. In addition, adhesion, survival, and growth of neurons can be modulated through chemical modification of CNTs. Axonal and synaptic signaling can also be positively tuned by these materials. Here we describe the ability of free-standing CNT films to influence neuronal activity. We demonstrate that the degree of cross-linking between the CNTs has a strong impact on the electrical conductivity of the substrate, which, in turn, regulates neural circuit outputs.

Tissue-specific extracellular matrix accelerates the formation of neural networks and communities in a neuron-glia co-culture on a multi-electrode array

The brain’s extracellular matrix (ECM) is a macromolecular network composed of glycosaminoglycans, proteoglycans, glycoproteins, and fibrous proteins. In vitro studies often use purified ECM proteins for cell culture coatings, however these may not represent the molecular complexity and heterogeneity of the brain’s ECM. To address this, we compared neural network activity (over 30 days in vitro) from primary neurons co-cultured with glia grown on ECM coatings from decellularized brain tissue (bECM) or MaxGel, a non-tissue-specific ECM. Cells were grown on a multi-electrode array (MEA) to enable noninvasive long-term interrogation of neuronal networks. In general, the presence of ECM accelerated the formation of networks without affecting the inherent network properties. However, specific features of network activity were dependent on the type of ECM: bECM enhanced network activity over a greater region of the MEA whereas MaxGel increased network burst rate associated with robust synaptophysin expression. These differences in network activity were not attributable to cellular composition, glial proliferation, or astrocyte phenotypes, which remained constant across experimental conditions. Collectively, the addition of ECM to neuronal cultures represents a reliable method to accelerate the development of mature neuronal networks, providing a means to enhance throughput for routine evaluation of neurotoxins and novel therapeutics.

A Versatile Protein and Cell Patterning Method Suitable for Long-Term Neural Cultures

Herein, we present an easy-to-use protein and cell patterning method relying solely on pipetting, rinsing steps and illumination with a desktop lamp, which does not require any expensive laboratory equipment, custom-built hardware or delicate chemistry. This method is based on the adhesion promoter poly(allylamine)-grafted perfluorophenyl azide, which allows UV-induced cross-linking with proteins and the antifouling molecule poly(vinylpyrrolidone). Versatility is demonstrated by creating patterns with two different proteins and a polysaccharide directly on plastic well plates and on glass slides, and by subsequently seeding primary neurons and C2C12 myoblasts on the patterns to form islands and mini-networks. Patterning characterization is done via immunohistochemistry, Congo red staining, ellipsometry, and infrared spectroscopy. Using a pragmatic setup, patterning contrasts down to 5 μm and statistically significant long-term stability superior to the gold standard poly(l-lysine)-grafted poly(ethylene glycol) could be obtained. This simple method can be used in any laboratory or even in classrooms and its outstanding stability is especially interesting for long-term cell experiments, e.g., for bottom-up neuroscience, where well-defined microislands and microcircuits of primary neurons are studied over weeks.

Analog control with two Artificial Axons

The artificial axon is a recently introduced synthetic assembly of supported lipid bilayers and voltage gated ion channels, displaying the basic electrophysiology of nerve cells. Here we demonstrate the use of two artificial axons as control elements to achieve a simple task. Namely, we steer a remote control car towards a light source, using the sensory input dependent firing rate of the axons as the control signal for turning left or right. We present the result in the form of the analysis of a movie of the car approaching the light source. In general terms, with this work we pursue a constructivist approach to exploring the nexus between machine language at the nerve cell level and behavior.

Nanowire based bioprobes for electrical monitoring of electrogenic cells

The continuous miniaturization of electronic components and the emergence of nano-biotechnology has opened new perspectives to monitor electrical activities at the single cell level. Here, we describe the creation of very high surface-to-volume ratio passive devices (vertical nanowire probes) using large-scale fabrication process, allowing to follow the electrical activity of mammalian neurons. Based on conventional silicon processing, the silicon nanowires were silicided in platinum in order to improve their electrochemical performances and to guarantee their biocompatibility. Very high signal to noise ratio was achieved (up to 2000) when measuring spontaneous action potentials. Moreover, this bio-platform was used to record the impact of various bio-chemical and electrical stimulations on neuronal activity. To conclude, this study proposes a thorough comparison of the characteristics and performances of these new nanowire-based nanoprobes with the main alternative systems published up to now.

Slow-Wave Recordings From Micro-Sized Neural Clusters Using Multiwell Type Microelectrode Arrays

OBJECTIVE

The use of microelectrode array (MEA) recordings is a very effective neurophysiological method because it is able to continuously and noninvasively obtain the spatiotemporal information of electrical activity from many neurons constituting a neural network. Very recently, studies have been published that used MEAs for the measurement of a low-frequency component of electrical activity as an indicator of diverse activity of cultured neurons. The occurrence of low-frequency activities has electrophysiological information that does not include the information from fast spikes. However, there is no in vitro experimental model suitable for measuring the low-frequency activities (slow-waves) for further study.

METHODS

Neural clusters consisting of dozens of neurons were placed directly onto each electrode of an MEA from which fast spikes and slow-waves were measured.

RESULTS

We obtained sufficient data on the early development patterns of the slow-waves and the spikes measured from many independent neural clusters confirming that the slow-waves occurred first before the emergence of the spikes in the neural clusters. We also showed that changes in the occurrence frequency of the slow-waves for synaptic blockers were measured from a large number of independent cultures.

CONCLUSION

Microsized neural cluster arrays, which can be combined with conventional MEAs, are suitable for multiple simultaneous recordings of slow-waves.

SIGNIFICANCE

Our technology provides a simple but useful method to study the generation of a low-frequency component of the electrical activity in cultured neural networks that are not yet well known as well as to expand the use of conventional MEAs.

Self-Aligned Functionalization Approach to Order Neuronal Networks at the Single-Cell Level

Despite significant progress, our knowledge of the functioning of the central nervous system still remains scarce to date. A better understanding of its behavior, in either normal or diseased conditions, goes through an increased knowledge of basic mechanisms involved in neuronal function, including at the single-cell level. This has motivated significant efforts for the development of miniaturized sensing devices to monitor neuronal activity with high spatial and signal resolution. One of the main challenges remaining to be addressed in this domain is, however, the ability to create in vitro spatially ordered neuronal networks at low density with a precise control of the cell location to ensure proper monitoring of the activity of a defined set of neurons. Here, we present a novel self-aligned chemical functionalization method, based on a repellant surface with patterned attractive areas, which permits the elaboration of low-density neuronal network down to individual cells with a high control of the soma location and axonal growth. This approach is compatible with complementary metal-oxide-semiconductor line technology at a wafer scale and allows performing the cell culture on packaged chip outside microelectronics facilities. Rat cortical neurons were cultured on such patterned surfaces for over one month and displayed a very high degree of organization in large networks. Indeed, more than 90% of the network nodes were settled by a soma and 100% of the connecting lines were occupied by a neurite, with a very good selectivity (low parasitic cell connections). After optimization, networks composed of 75% of unicellular nodes were obtained, together with a control at the micron scale of the location of the somas. Finally, we demonstrated that the dendritic neuronal growth was guided by the surface functionalization, even when micrometer scale topologies were encountered and we succeeded to control the extension growth along one-dimensional-aligned nanostructures with sub-micrometrical scale precision. This novel approach now opens the way for precise monitoring of neuronal network activity at the single-cell level.

Biofunctionalized 3D Nanopillar Arrays Fostering Cell Guidance and Promoting Synapse Stability and Neuronal Activity in Networks

A controlled geometry of in vitro neuronal networks allows investigation of the cellular mechanisms that underlie neuron-to-neuron and neuron-extracellular matrix interactions, which are essential to biomedical research. Herein, we report a selective guidance of primary hippocampal neurons by using arrays of three-dimensional vertical nanopillars (NPs) functionalized with a specific adhesion-promoting molecule-poly-dl-ornithine (PDLO). We show that 90% of neuronal cells are guided exclusively on the combinatorial PDLO/NP substrate. Moreover, we demonstrate the influence of the interplay between nanostructures and neurons on synapse formation and maturation, resulting in increased expression of postsynaptic density-95 protein and enhanced network cellular activity conferred by the endogenous c-fos expression. Successful guidance to foster synapse stability and cellular activity on multilevel cues of surface topography and chemical functionalization suggests the potential to devise technologies to control neuronal growth on nanostructures for tissue engineering, neuroprostheses, and drug development.

Technical feasibility study for production of tailored multielectrode arrays and patterning of arranged neuronal networks

In this manuscript, we first reveal a simple ultra violet laser lithographic method to design and produce plain tailored multielectrode arrays. Secondly, we use the same lithographic setup for surface patterning to enable controlled attachment of primary neuronal cells and help neurite guidance. For multielectrode array production, we used flat borosilicate glass directly structured with the laser lithography system. The multi layered electrode system consists of a layer of titanium coated with a layer of di-titanium nitride. Finally, these electrodes are covered with silicon nitride for insulation. The quality of the custom made multielectrode arrays was investigated by light microscopy, electron microscopy and X-ray diffraction. The performance was verified by the detection of action potentials of primary neurons. The electrical noise of the custom-made MEA was equal to commercially available multielectrode arrays. Additionally, we demonstrated that structured coating with poly lysine, obtained with the aid of the same lithographic system, could be used to attach and guide neurons to designed structures. The process of neuron attachment and neurite guidance was investigated by light microscopy and charged particle microscopy. Importantly, the utilization of the same lithographic system for MEA fabrication and poly lysine structuring will make it easy to align the architecture of the neuronal network to the arrangement of the MEA electrode.. In future studies, this will lead to multielectrode arrays, which are able to specifically attach neuronal cell bodies to their chemically defined electrodes and guide their neurites, gaining a controlled connectivity in the neuronal network. This type of multielectrode array would be able to precisely assign a signal to a certain neuron resulting in an efficient way for analyzing the maturation of the neuronal connectivity in small neuronal networks.

Recent advances in microfluidic technologies for cell-to-cell interaction studies

Microfluidic cell cultures are ideally positioned to become the next generation of in vitro diagnostic tools for biomedical research, where key biological processes such as cell signalling and dynamic cell-to-cell interactions can be reliably analysed under reproducible physiological cell culture conditions. In the last decade, a large number of microfluidic cell analysis systems have been developed for a variety of applications including drug target optimization, drug screening and toxicological testing. More recently, advanced in vitro microfluidic cell culture systems have emerged that are capable of replicating the complex three-dimensional architectures of tissues and organs and thus represent valid biological models for investigating the mechanism and function of human tissue structures, as well as studying the onset and progression of diseases such as cancer. In this review, we present the most important developments in single-cell, 2D and 3D microfluidic cell culture systems for studying cell-to-cell interactions published over the last 6 years, with a focus on cancer research and immunotherapy, vascular models and neuroscience. In addition, the current technological development of microdevices with more advanced physiological cell microenvironments that integrate multiple organ models, namely, the so-called body-, human- and multi-organ-on-a-chip, is reviewed.

Easy to Apply Polyoxazoline-Based Coating for Precise and Long-Term Control of Neural Patterns

Arranging cultured cells in patterns via surface modification is a tool used by biologists to answer questions in a specific and controlled manner. In the past decade, bottom-up neuroscience emerged as a new application, which aims to get a better understanding of the brain via reverse engineering and analyzing elementary circuitry in vitro. Building well-defined neural networks is the ultimate goal. Antifouling coatings are often used to control neurite outgrowth. Because erroneous connectivity alters the entire topology and functionality of minicircuits, the requirements are demanding. Current state-of-the-art coating solutions such as widely used poly(l-lysine)-g-poly(ethylene glycol) (PLL-g-PEG) fail to prevent primary neurons from making undesired connections in long-term cultures. In this study, a new copolymer with greatly enhanced antifouling properties is developed, characterized, and evaluated for its reliability, stability, and versatility. To this end, the following components are grafted to a poly(acrylamide) (PAcrAm) backbone: hexaneamine, to support spontaneous electrostatic adsorption in buffered aqueous solutions, and propyldimethylethoxysilane, to increase the durability via covalent bonding to hydroxylated culture surfaces and antifouling polymer poly(2-methyl-2-oxazoline) (PMOXA). In an assay for neural connectivity control, the new copolymer's ability to effectively prevent unwanted neurite outgrowth is compared to the gold standard, PLL-g-PEG. Additionally, its versatility is evaluated on polystyrene, glass, and poly(dimethylsiloxane) using primary hippocampal and cortical rat neurons as well as C2C12 myoblasts, and human fibroblasts. PAcrAm-g-(PMOXA, NH₂, Si) consistently outperforms PLL-g-PEG with all tested culture surfaces and cell types, and it is the first surface coating which reliably prevents arranged nodes of primary neurons from forming undesired connections over the long term. Whereas the presented work focuses on the proof of concept for the new antifouling coating to successfully and sustainably prevent unwanted connectivity, it is an important milestone for in vitro neuroscience, enabling follow-up studies to engineer neurologically relevant networks. Furthermore, because PAcrAm-g-(PMOXA, NH₂, Si) can be quickly applied and used with various surfaces and cell types, it is an attractive extension to the toolbox for in vitro biology and biomedical engineering.

Selective Targeting of Neurons with Inorganic Nanoparticles: Revealing the Crucial Role of Nanoparticle Surface Charge

Nanoparticles (NPs) are increasingly used in biomedical applications, but the factors that influence their interactions with living cells need to be elucidated. Here, we reveal the role of NP surface charge in determining their neuronal interactions and electrical responses. We discovered that negatively charged NPs administered at low concentration (10 nM) interact with the neuronal membrane and at the synaptic cleft, whereas positively and neutrally charged NPs never localize on neurons. This effect is shape and material independent. The presence of negatively charged NPs on neuronal cell membranes influences the excitability of neurons by causing an increase in the amplitude and frequency of spontaneous postsynaptic currents at the single cell level and an increase of both the spiking activity and synchronous firing at neural network level. The negatively charged NPs exclusively bind to excitable neuronal cells, and never to nonexcitable glial cells. This specific interaction was also confirmed by manipulating the electrophysiological activity of neuronal cells. Indeed, the interaction of negatively charged NPs with neurons is either promoted or hindered by pharmacological suppression or enhancement of the neuronal activity with tetrodotoxin or bicuculline, respectively. We further support our main experimental conclusions by using numerical simulations. This study demonstrates that negatively charged NPs modulate the excitability of neurons, revealing the potential use of NPs for controlling neuron activity.

High-density MEA recordings unveil the dynamics of bursting events in Cell Cultures

High density multielectrode arrays (MEAs) based on CMOS technology (CMOS-MEAs) can simultaneously record extracellular spiking activity in neuronal cultures from 4096 closely spaced microelectrodes. This allows for a finer investigation of neuronal network activity compared to conventional MEAs with a few tens of electrodes. However, the sensing properties of these devices differ. To highlight this aspect, here we investigate and discuss the differences observed when quantifying spontaneous synchronized bursting events (SBEs) in datasets acquired with conventional MEAs and high-density MEAs from comparable hippocampal cultures. We found that datasets acquired with high-density MEAs exhibit collective dynamics similar to conventional arrays, but are characterized by a higher percentage of random spikes, i.e. spikes that are not part of a burst, most probably resulting from the larger recording capability. Additionally, the percentage of electrodes that record a burst is remarkably small on high-density MEAs compared to what can be observed on conventional MEAs and SBEs appear to be propagating in time across the electrode array, by involving shorter sequences of spikes per electrode. Overall, these results highlight a lower level of network synchronization involved in SBEs compared to what has been debated for several decades based on conventional MEA recordings from cell cultures.

Neural Circuits on a Chip

Neural circuits are responsible for the brain's ability to process and store information. Reductionist approaches to understanding the brain include isolation of individual neurons for detailed characterization. When maintained in vitro for several days or weeks, dissociated neurons self-assemble into randomly connected networks that produce synchronized activity and are capable of learning. This review focuses on efforts to control neuronal connectivity in vitro and construct living neural circuits of increasing complexity and precision. Microfabrication-based methods have been developed to guide network self-assembly, accomplishing control over in vitro circuit size and connectivity. The ability to control neural connectivity and synchronized activity led to the implementation of logic functions using living neurons. Techniques to construct and control three-dimensional circuits have also been established. Advances in multiple electrode arrays as well as genetically encoded, optical activity sensors and transducers enabled highly specific interfaces to circuits composed of thousands of neurons. Further advances in on-chip neural circuits may lead to better understanding of the brain.

Unidirectional signal propagation in primary neurons micropatterned at a single-cell resolution

The structure and connectivity of cultured neuronal networks can be controlled by using micropatterned surfaces. Here, we demonstrate that the direction of signal propagation can be precisely controlled at a single-cell resolution by growing primary neurons on micropatterns. To achieve this, we first examined the process by which axons develop and how synapses form in micropatterned primary neurons using immunocytochemistry. By aligning asymmetric micropatterns with a marginal gap, it was possible to pattern primary neurons with a directed polarization axis at the single-cell level. We then examined how synapses develop on micropatterned hippocampal neurons. Three types of micropatterns with different numbers of short paths for dendrite growth were compared. A normal development in synapse density was observed when micropatterns with three or more short paths were used. Finally, we performed double patch clamp recordings on micropatterned neurons to confirm that these synapses are indeed functional, and that the neuronal signal is transmitted unidirectionally in the intended orientation. This work provides a practical guideline for patterning single neurons to design functional neuronal networks in vitro with the direction of signal propagation being controlled.

In-mold patterning and actionable axo-somatic compartmentalization for on-chip neuron culture

Oriented neuronal networks with controlled connectivity are required for many applications ranging from studies of neurodegeneration to neuronal computation. To build such networks in vitro, an efficient, directed and long lasting guidance of axons toward their target is a pre-requisite. The best guidance achieved so far, however, relies on confining axons in enclosed microchannels, making them poorly accessible for further investigation. Here we describe a method providing accessible and highly regular arrays of axons, emanating from somas positioned in distinct compartments. This method combines the use of a novel removable partition, allowing soma positioning outside of the axon guidance patterns, and in-mold patterning (iMP), a hybrid method combining chemical and mechanical cell positioning clues applied here for the first time to neurons. The axon guidance efficiency of iMP is compared to that of conventional patterning methods, e.g. micro-contact printing (chemical constraints by a poly-l-lysine motif) and micro-grooves (physical constraints by homogeneously coated microstructures), using guiding tracks of different widths and spacing. We show that iMP provides a gain of 10 to 100 in axon confinement efficiency on the tracks, yielding mm-long, highly regular, and fully accessible on-chip axon arrays. iMP also allows well-defined axon guidance from small populations of several neurons confined at predefined positions in μm-sized wells. iMP will thus open new routes for the construction of complex and accurately controlled neuronal networks.

Controlled single-cell deposition and patterning by highly flexible hollow cantilevers

Single-cell patterning represents a key approach to decouple and better understand the role and mechanisms of individual cells of a given population. In particular, the bottom-up approach of engineering neuronal circuits with a controlled topology holds immense promises to perceive the relationships between connectivity and function. In order to accommodate these efforts, highly flexible SU-8 cantilevers with integrated microchannels have been fabricated for both additive and subtractive patterning. By directly squeezing out single cells onto adhesive surfaces, controlled deposition with a spatial accuracy of 5 μm could be achieved, while subtractive patterning has been realized by selective removal of targeted single cells. Complex cell patterns were created on substrates pre-patterned with cell-adhesive and repulsive areas, preserving the original pattern geometry for long-term studies. For example, a circular loop with a diameter of 530 μm has been realized using primary hippocampal neurons, which were fully connected to their respective neighbors along the loop. Using the same cantilevers, the versatility of the technique has also been demonstrated via in situ modification of already mature neuronal cultures by both detaching individual cells of the population and adding fresh ones, incorporating them into the culture.

Insinuating electronics in the brain

There is an expanding interface between electronic engineering and neurosurgery. Rapid advances in microelectronics and materials science, driven largely by consumer demand, are inspiring and accelerating development of a new generation of diagnostic, therapeutic, and prosthetic devices for implantation in the nervous system. This paper reviews some of the basic science underpinning their development and outlines some opportunities and challenges for their use in neurosurgery.

Structure, Function, and Propagation of Information across Living Two, Four, and Eight Node Degree Topologies

In this study, we created four network topologies composed of living cortical neurons and compared resultant structural-functional dynamics including the nature and quality of information transmission. Each living network was composed of living cortical neurons and were created using microstamping of adhesion promoting molecules and each was "designed" with different levels of convergence embedded within each structure. Networks were cultured over a grid of electrodes that permitted detailed measurements of neural activity at each node in the network. Of the topologies we tested, the "Random" networks in which neurons connect based on their own intrinsic properties transmitted information embedded within their spike trains with higher fidelity relative to any other topology we tested. Within our patterned topologies in which we explicitly manipulated structure, the effect of convergence on fidelity was dependent on both topology and time-scale (rate vs. temporal coding). A more detailed examination using tools from network analysis revealed that these changes in fidelity were also associated with a number of other structural properties including a node's degree, degree-degree correlations, path length, and clustering coefficients. Whereas information transmission was apparent among nodes with few connections, the greatest transmission fidelity was achieved among the few nodes possessing the highest number of connections (high degree nodes or putative hubs). These results provide a unique view into the relationship between structure and its affect on transmission fidelity, at least within these small neural populations with defined network topology. They also highlight the potential role of tools such as microstamp printing and microelectrode array recordings to construct and record from arbitrary network topologies to provide a new direction in which to advance the study of structure-function relationships.