An in vitro method to manipulate the direction and functional strength between neural populations

Nanomagnetic Guidance Shapes the Structure-Function Relationship of Developing Cortical Networks

In this study, we implement large-scale nanomagnetic guidance on cortical neurons to guide dissociated neuronal networks during development. Cortical networks cultured over microelectrode arrays were exposed to functionalized magnetic nanoparticles, followed by magnetic field exposure to guide neurites over 14 days in vitro. Immunofluorescence of the axonal protein Tau revealed a greater number of neurites that were longer and aligned with the nanomagnetic force relative to nonguided networks. This was further confirmed through brightfield imaging on the microelectrode arrays during development. Spontaneous electrophysiological recordings revealed that the guided networks exhibited increased firing rates and frequency in force-aligned connectivity identified through Granger Causality. Applying this methodology across networks with nonuniform force directions increased local activity in target regions, identified as regions in the direction of the nanomagnetic force. Altogether, these results demonstrate that nanomagnetic forces guide the structure and function of dissociated cortical neuron networks at the millimeter scale.

Reverse engineering of feedforward cortical-Hippocampal microcircuits for modelling neural network function and dysfunction

Engineered biological neural networks are indispensable models for investigation of neural function and dysfunction from the subcellular to the network level. Notably, advanced neuroengineering approaches are of significant interest for their potential to replicate the topological and functional organization of brain networks. In this study, we reverse engineered feedforward neural networks of primary cortical and hippocampal neurons, using a custom-designed multinodal microfluidic device with Tesla valve inspired microtunnels. By interfacing this device with nanoporous microelectrodes, we show that the reverse engineered multinodal neural networks exhibit capacity for both segregated and integrated functional activity, mimicking brain network dynamics. To advocate the broader applicability of our model system, we induced localized perturbations with amyloid beta to study the impact of pathology on network functionality. Additionally, we demonstrate long-term culturing of subregion- and layer specific neurons extracted from the entorhinal cortex and hippocampus of adult Alzheimer's-model mice and rats. Our results thus highlight the potential of our approach for reverse engineering of anatomically relevant multinodal neural networks to study dynamic structure-function relationships in both healthy and pathological conditions.

Engineering an in vitro retinothalamic nerve model

Understanding the retinogeniculate pathway in vitro can offer insights into its development and potential for future therapeutic applications. This study presents a Polydimethylsiloxane-based two-chamber system with axon guidance channels, designed to replicate unidirectional retinogeniculate signal transmission in vitro. Using embryonic rat retinas, we developed a model where retinal spheroids innervate thalamic targets through up to 6 mm long microfluidic channels. Using a combination of electrical stimulation and functional calcium imaging we assessed how channel length and electrical stimulation frequency affects thalamic target response. In the presented model we integrated up to 20 identical functional retinothalamic neural networks aligned on a single transparent microelectrode array, enhancing the robustness and quality of recorded functional data. We found that network integrity depends on channel length, with 0.5-2 mm channels maintaining over 90% morphological and 50% functional integrity. A reduced network integrity was recorded in longer channels. The results indicate a notable reduction in forward spike propagation in channels longer than 4 mm. Additionally, spike conduction fidelity decreased with increasing channel length. Yet, stimulation-induced thalamic target activity remained unaffected by channel length. Finally, the study found that a sustained thalamic calcium response could be elicited with stimulation frequencies up to 31 Hz, with higher frequencies leading to transient responses. In conclusion, this study presents a high-throughput platform that demonstrates how channel length affects retina to brain network formation and signal transmission in vitro.

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.

Activity-dependent tau cleavage by caspase-3 promotes neuronal dysfunction and synaptotoxicity

Tau-mediated toxicity is associated with cognitive decline and Alzheimer's disease (AD) progression. In particular, tau post-translational modifications (PTMs) are thought to generate aberrant tau species resulting in neuronal dysfunction. Despite being well characterized in postmortem AD brain, it is unclear how caspase-mediated C-terminal tau cleavage promotes neurodegeneration, as few studies have developed the models to dissect this pathogenic mechanism. Here, we show that proteasome impairment results in cleaved tau accumulation at the post-synaptic density (PSD), a process that is modulated by neuronal activity. Cleaved tau (at residue D421) impairs neuronal firing and causes inefficient initiation of network bursts, consistent with reduced excitatory drive. We propose that reduced neuronal activity, or silencing, is coupled to proteasome dysfunction, which drives cleaved tau accumulation at the PSD and subsequent synaptotoxicity. Our study connects three common themes in the progression of AD: impaired proteostasis, caspase-mediated tau cleavage, and synapse degeneration.

Engineering circuits of human iPSC-derived neurons and rat primary glia

Novel in vitro platforms based on human neurons are needed to improve early drug testing and address the stalling drug discovery in neurological disorders. Topologically controlled circuits of human induced pluripotent stem cell (iPSC)-derived neurons have the potential to become such a testing system. In this work, we build in vitro co-cultured circuits of human iPSC-derived neurons and rat primary glial cells using microfabricated polydimethylsiloxane (PDMS) structures on microelectrode arrays (MEAs). Our PDMS microstructures are designed in the shape of a stomach, which guides axons in one direction and thereby facilitates the unidirectional flow of information. Such circuits are created by seeding either dissociated cells or pre-aggregated spheroids at different neuron-to-glia ratios. Furthermore, an antifouling coating is developed to prevent axonal overgrowth in undesired locations of the microstructure. We assess the electrophysiological properties of different types of circuits over more than 50 days, including their stimulation-induced neural activity. Finally, we demonstrate the inhibitory effect of magnesium chloride on the electrical activity of our iPSC circuits as a proof-of-concept for screening of neuroactive compounds.

Incubator-independent perfusion system integrated with microfluidic device for continuous electrophysiology and microscopy readouts

Advances in primary and stem cell derived neuronal cell culture techniques and abundance of available neuronal cell types have enabledin vitroneuroscience as a substantial approach to modelin vivoneuronal networks. Survival of the cultured neurons is inevitably dependent on the cell culture incubators to provide stable temperature and humidity and to supply required CO₂levels for controlling the pH of culture medium. Therefore, imaging and electrophysiology recordings outside of the incubator are often limited to the short-term experimental sessions. This restricts our understanding of physiological events to the short snapshots of recorded data while the major part of temporal data is neglected. Multiple custom-made and commercially available platforms like integrated on-stage incubators have been designed to enable long-term microscopy. Nevertheless, long-term high-spatiotemporal electrophysiology recordings from developing neuronal networks needs to be addressed. In the present work an incubator-independent polydimethylsiloxane-based double-wall perfusion chamber was designed and integrated with multi-electrode arrays (MEAs) electrophysiology and compartmentalized microfluidic device to continuously record from engineered neuronal networks at sub-cellular resolution. Cell culture media underwent iterations of conditioning to the ambient CO₂and adjusting its pH to physiological ranges to retain a stable pH for weeks outside of the incubator. Double-wall perfusion chamber and an integrated air bubble trapper reduced media evaporation and osmolality drifts of the conditioned media for two weeks. Aligned microchannel-microfluidic device on MEA electrodes allowed neurite growth on top of the planar electrodes and amplified their extracellular activity. This enabled continuous sub-cellular resolution imaging and electrophysiology recordings from developing networks and their growing neurites. The on-chip versatile and self-contained system provides long-term, continuous and high spatiotemporal access to the network data and offers a robustin vitroplatform with many potentials to be applied on advanced cell culture systems including organ-on-chip and organoid models.

Microfluidic cell engineering on high-density microelectrode arrays for assessing structure-function relationships in living neuronal networks

Neuronal networks in dissociated culture combined with cell engineering technology offer a pivotal platform to constructively explore the relationship between structure and function in living neuronal networks. Here, we fabricated defined neuronal networks possessing a modular architecture on high-density microelectrode arrays (HD-MEAs), a state-of-the-art electrophysiological tool for recording neural activity with high spatial and temporal resolutions. We first established a surface coating protocol using a cell-permissive hydrogel to stably attach a polydimethylsiloxane microfluidic film on the HD-MEA. We then recorded the spontaneous neural activity of the engineered neuronal network, which revealed an important portrait of the engineered neuronal network-modular architecture enhances functional complexity by reducing the excessive neural correlation between spatially segregated modules. The results of this study highlight the impact of HD-MEA recordings combined with cell engineering technologies as a novel tool in neuroscience to constructively assess the structure-function relationships in neuronal networks.

Flexibility of in vitro cortical circuits influences resilience from microtrauma

Background

Small clusters comprising hundreds to thousands of neurons are an important level of brain architecture that correlates single neuronal properties to fulfill brain function, but the specific mechanisms through which this scaling occurs are not well understood. In this study, we developed an in vitro experimental platform of small neuronal circuits (islands) to probe the importance of structural properties for their development, physiology, and response to microtrauma.

Methods

Primary cortical neurons were plated on a substrate patterned to promote attachment in clusters of hundreds of cells (islands), transduced with GCaMP6f, allowed to mature until 10-13 days in vitro (DIV), and monitored with Ca²⁺ as a non-invasive proxy for electrical activity. We adjusted two structural factors-island size and cellular density-to evaluate their role in guiding spontaneous activity and network formation in neuronal islands.

Results

We found cellular density, but not island size, regulates of circuit activity and network function in this system. Low cellular density islands can achieve many states of activity, while high cellular density biases islands towards a limited regime characterized by low rates of activity and high synchronization, a property we summarized as "flexibility." The injury severity required for an island to lose activity in 50% of its population was significantly higher in low-density, high flexibility islands.

Conclusion

Together, these studies demonstrate flexible living cortical circuits are more resilient to microtrauma, providing the first evidence that initial circuit state may be a key factor to consider when evaluating the consequences of trauma to the cortex.

Microfluidics for Neuronal Cell and Circuit Engineering

The widespread adoption of microfluidic devices among the neuroscience and neurobiology communities has enabled addressing a broad range of questions at the molecular, cellular, circuit, and system levels. Here, we review biomedical engineering approaches that harness the power of microfluidics for bottom-up generation of neuronal cell types and for the assembly and analysis of neural circuits. Microfluidics-based approaches are instrumental to generate the knowledge necessary for the derivation of diverse neuronal cell types from human pluripotent stem cells, as they enable the isolation and subsequent examination of individual neurons of interest. Moreover, microfluidic devices allow to engineer neural circuits with specific orientations and directionality by providing control over neuronal cell polarity and permitting the isolation of axons in individual microchannels. Similarly, the use of microfluidic chips enables the construction not only of 2D but also of 3D brain, retinal, and peripheral nervous system model circuits. Such brain-on-a-chip and organoid-on-a-chip technologies are promising platforms for studying these organs as they closely recapitulate some aspects of in vivo biological processes. Microfluidic 3D neuronal models, together with 2D in vitro systems, are widely used in many applications ranging from drug development and toxicology studies to neurological disease modeling and personalized medicine. Altogether, microfluidics provide researchers with powerful systems that complement and partially replace animal models.

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.

Microfluidic electrode array chip for electrical stimulation-mediated axonal regeneration

The precise manipulation of the neural stem cell (NSC)-derived neural differentiation is still challenging, and there is a technological barrier to regulate the axonal regeneration in a controlled manner. Here, we developed a microfluidic chip integrated with a microelectrode array as an axonal guidance platform. The microfluidic electrode array chip consisted of two compartments and a bridge microchannel that could isolate and guide the axons. We demonstrated that the NSCs were largely differentiated into neural cells as the electric field was applied to the microfluidic electrode array chip. We also confirmed the synergistic effects of the electrical stimulation (ES) and neurotrophic factor (NF) on axonal outgrowth. This microfluidic electrode array chip can serve as a central nervous system (CNS) model for axonal injury and regeneration. Therefore, it could be a potentially powerful tool for an in vitro model of the axonal regeneration.

Coupling of in vitro Neocortical-Hippocampal Coculture Bursts Induces Different Spike Rhythms in Individual Networks

Brain-state alternation is important for long-term memory formation. Each brain state can be identified with a specific process in memory formation, e.g., encoding during wakefulness or consolidation during sleeping. The hippocampal-neocortical dialogue was proposed as a hypothetical framework for systems consolidation, which features different cross-frequency couplings between the hippocampus and distributed neocortical regions in different brain states. Despite evidence supporting this hypothesis, little has been reported about how information is processed with shifts in brain states. To address this gap, we developed an in vitro neocortical-hippocampal coculture model to study how activity coupling can affect connections between coupled networks. Neocortical and hippocampal neurons were cultured in two different compartments connected by a micro-tunnel structure. The network activity of the coculture model was recorded by microelectrode arrays underlying the substrate. Rhythmic bursting was observed in the spontaneous activity and electrical evoked responses. Rhythmic bursting activity in one compartment could couple to that in the other via axons passing through the micro-tunnels. Two types of coupling patterns were observed: slow-burst coupling (neocortex at 0.1–0.5 Hz and hippocampus at 1 Hz) and fast burst coupling (neocortex at 20–40 Hz and hippocampus at 4–10 Hz). The network activity showed greater synchronicity in the slow-burst coupling, as indicated by changes in the burstiness index. Network synchronicity analysis suggests the presence of different information processing states under different burst activity coupling patterns. Our results suggest that the hippocampal-neocortical coculture model possesses multiple modes of burst activity coupling between the cortical and hippocampal parts. With the addition of external stimulation, the neocortical-hippocampal network model we developed can elucidate the influence of state shifts on information processing.

Compartmentalized microfluidic chambers enable long-term maintenance and communication between human pluripotent stem cell-derived forebrain and midbrain neurons

Compartmentalized microfluidic devices are becoming increasingly popular and have proven to be valuable tools to probe neurobiological functions that are inherently difficult to study using traditional approaches. The ability of microfluidic devices to compartmentalize neurons offers considerable promise for disease modeling and drug discovery. Rodent cortical neurons/neural progenitors are commonly used in such studies but, while these cells mature rapidly, they do not possess the same receptors, ion channels and transport proteins found in human cortical neurons. Human pluripotent stem cell derived neurons offer a human phenotype, but their slow maturation offsets this phenotypic advantage, particularly over long-term culture where overgrowth and subsequent death of neurons may be a problem. In this work, we integrate the use of Matrigel as a 3D cell culture scaffold that enables high cell seeding density over a small fraction of the culture surface. This approach, in an open chamber microfluidic system, enables culture over a five-month period without the use of growth inhibitors. Matrigel was also uniquely utilized to hinder agonist diffusion across microchannels. We demonstrate the development of neuron-to-neuron communication networks by showing that electrical stimulation or the unilateral addition of agonists to one chamber resulted in activation of neurons in the adjacent chamber. Lastly, using a delayed neuron seeding strategy, we show that we can foster essentially one-way communication between separate populations of human forebrain and midbrain dopaminergic neuron containing cultures.

Brain-on-a-Chip: Characterizing the next generation of advanced in vitro platforms for modeling the central nervous system

The complexity of the human brain creates significant, almost insurmountable challenges for neurological drug development. Advanced in vitro platforms are increasingly enabling researchers to overcome these challenges, by mimicking key features of the brain's composition and functionality. Many of these platforms are called "Brains-on-a-Chip"-a term that was originally used to refer to microfluidics-based systems containing miniature engineered tissues, but that has since expanded to describe a vast range of in vitro central nervous system (CNS) modeling approaches. This Perspective seeks to refine the definition of a Brain-on-a-Chip for the next generation of in vitro platforms, identifying criteria that determine which systems should qualify. These criteria reflect the extent to which a given platform overcomes the challenges unique to in vitro CNS modeling (e.g., recapitulation of the brain's microenvironment; inclusion of critical subunits, such as the blood-brain barrier) and thereby provides meaningful added value over conventional cell culture systems. The paper further outlines practical considerations for the development and implementation of Brain-on-a-Chip platforms and concludes with a vision for where these technologies may be heading.

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.

Role of Noise in Spontaneous Activity of Networks of Neurons on Patterned Silicon Emulated by Noise–activated CMOS Neural Nanoelectronic Circuits

Background noise in biological cortical microcircuits constitutes a powerful resource to assess their computational tasks, including, for instance, the synchronization of spiking activity, the enhancement of the speed of information transmission, and the minimization of the corruption of signals. We explore the correlation of spontaneous firing activity of ≈ 100 biological neurons adhering to engineered scaffolds by governing the number of functionalized patterned connection pathways among groups of neurons. We then emulate the biological system by a series of noise-activated silicon neural network simulations. We show that by suitably tuning both the amplitude of noise and the number of synapses between the silicon neurons, the same controlled correlation of the biological population is achieved. Our results extend to a realistic silicon nanoelectronics neuron design using noise injection to be exploited in artificial spiking neural networks such as liquid state machines and recurrent neural networks for stochastic computation.

Experimental Platform to Study Spiking Pattern Propagation in Modular Networks In Vitro

The structured organization of connectivity in neural networks is associated with highly efficient information propagation and processing in the brain, in contrast with disordered homogeneous network architectures. Using microfluidic methods, we engineered modular networks of cultures using dissociated cells with unidirectional synaptic connections formed by asymmetric microchannels. The complexity of the microchannel geometry defined the strength of the synaptic connectivity and the properties of spiking activity propagation. In this study, we developed an experimental platform to study the effects of synaptic plasticity on a network level with predefined locations of unidirectionally connected cellular assemblies using multisite extracellular electrophysiology.

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.

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.

Bundled Three-Dimensional Human Axon Tracts Derived from Brain Organoids

Reestablishing cerebral connectivity is a critical part of restoring neuronal network integrity and brain function after trauma, stroke, and neurodegenerative diseases. Creating transplantable axon tracts in the laboratory is an unexplored strategy for overcoming the common barriers limiting axon regeneration in vivo, including growth-inhibiting factors and the limited outgrowth capacity of mature neurons in the brain. We describe the generation, phenotype, and connectivity of constrained three-dimensional human axon tracts derived from brain organoids. These centimeter-long constructs are encased in an agarose shell that permits physical manipulation and are composed of discrete cellular regions spanned by axon tracts, mirroring the separation of cerebral gray and white matter. Features of cerebral cortex also are emulated, as evidenced by the presence of neurons with different cortical layer phenotypes. This engineered neural tissue represents a first step toward potentially reconstructing brain circuits by physically replacing neuronal populations and long-range axon tracts in the brain.

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Transplantable 3D axon tracts are tissue engineered from human brain organoids

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Growth of organoid axons in a hydrogel column is enhanced compared with planar culture

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Organoids within engineered columns can maintain a laminar cortical architecture

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Functional connectivity across the construct is demonstrated using calcium imaging

µSpikeHunter: An advanced computational tool for the analysis of neuronal communication and action potential propagation in microfluidic platforms

Understanding neuronal communication is fundamental in neuroscience, but there are few methodologies offering detailed analysis for well-controlled conditions. By interfacing microElectrode arrays with microFluidics (μEF devices), it is possible to compartmentalize neuronal cultures with a specified alignment of axons and microelectrodes. This setup allows the extracellular recording of spike propagation with a high signal-to-noise ratio over the course of several weeks. Addressing these μEF devices, we developed an advanced yet easy-to-use publically available computational tool, μSpikeHunter, which provides a detailed quantification of several communication-related properties such as propagation velocity, conduction failure, spike timings, and coding mechanisms. The combination of μEF devices and μSpikeHunter can be used in the context of standard neuronal cultures or with co-culture configurations where, for example, communication between sensory neurons and other cell types is monitored and assessed. The ability to analyze axonal signals (in a user-friendly, time-efficient, high-throughput manner) opens the door to new approaches in studies of peripheral innervation, neural coding, and neuroregeneration, among many others. We demonstrate the use of μSpikeHunter in dorsal root ganglion neurons where we analyze the presence of both anterograde and retrograde signals in μEF devices. A fully functional version of µSpikeHunter is publically available for download from https://github.com/uSpikeHunter .

Impact of modular organization on dynamical richness in cortical networks

As in many naturally formed networks, the brain exhibits an inherent modular architecture that is the basis of its rich operability, robustness, and integration-segregation capacity. However, the mechanisms that allow spatially segregated neuronal assemblies to swiftly change from localized to global activity remain unclear. Here, we integrate microfabrication technology with in vitro cortical networks to investigate the dynamical repertoire and functional traits of four interconnected neuronal modules. We show that the coupling among modules is central. The highest dynamical richness of the network emerges at a critical connectivity at the verge of physical disconnection. Stronger coupling leads to a persistently coherent activity among the modules, while weaker coupling precipitates the activity to be localized solely within the modules. An in silico modeling of the experiments reveals that the advent of coherence is mediated by a trade-off between connectivity and subquorum firing, a mechanism flexible enough to allow for the coexistence of both segregated and integrated activities. Our results unveil a new functional advantage of modular organization in complex networks of nonlinear units.

Specific CA3 neurons decode neural information of dentate granule cells evoked by paired-pulse stimulation in co-cultured networks

CA3 and dentate gyrus (DG) neurons are cultured in two-chamber devices on multi-electrode arrays (MEAs) and connected via micro-tunnels. In order to evoke time-locked activity, paired-pulse stimulation is applied to 22 different sites and repeated 25 times in each well in 5 MEA co-cultures and results compared to CA3-CA3 and DG-DG networks homologous controls. In these hippocampal sub-regions, we focus on the mechanisms underpinning a network's ability to decode the identity of site specific stimulation from analysis of evoked network responses using a support vector machine classifier. Our results indicate that a pool of CA3 neurons is able to reliably decode the identity of DG stimulation site information.

Pattern separation and completion of distinct axonal inputs transmitted via micro-tunnels between co-cultured hippocampal dentate, CA3, CA1 and entorhinal cortex networks

OBJECTIVE

Functions ascribed to the hippocampal sub-regions for encoding episodic memories include the separation of activity patterns propagated from the entorhinal cortex (EC) into the dentate gyrus (DG) and pattern completion in CA3 region. Since a direct assessment of these functions is lacking at the level of specific axonal inputs, our goal is to directly measure the separation and completion of distinct axonal inputs in engineered pairs of hippocampal sub-regional circuits.

APPROACH

We co-cultured EC-DG, DG-CA3, CA3-CA1 or CA1-EC neurons in a two-chamber PDMS device over a micro-electrode array (MEA60), inter-connected via distinct axons that grow through the micro-tunnels between the compartments. Taking advantage of the axonal accessibility, we quantified pattern separation and completion of the evoked activity transmitted through the tunnels from source into target well. Since pattern separation can be inferred when inputs are more correlated than outputs, we first compared the correlations among axonal inputs with those of target somata outputs. We then compared, in an analog approach, the distributions of correlation distances between rate patterns of the axonal inputs inside the tunnels with those of the somata outputs evoked in the target well. Finally, in a digital approach, we measured the spatial population distances between binary patterns of the same axonal inputs and somata outputs.

MAIN RESULTS

We found the strongest separation of the propagated axonal inputs when EC was axonally connected to DG, with a decline in separation to CA3 and to CA1 for both rate and digital approaches. Furthermore, the digital approach showed stronger pattern completion in CA3, then CA1 and EC.

SIGNIFICANCE

To the best of our knowledge, these are the first direct measures of pattern separation and completion for axonal transmission to the somata target outputs at the rate and digital population levels in each of four stages of the EC-DG-CA3-CA1 circuit.

Design of Cultured Neuron Networks in vitro with Predefined Connectivity Using Asymmetric Microfluidic Channels

The architecture of neuron connectivity in brain networks is one of the basic mechanisms by which to organize and sustain a particular function of the brain circuitry. There are areas of the brain composed of well-organized layers of neurons connected by unidirectional synaptic connections (e.g., cortex, hippocampus). Re-engineering of the neural circuits with such a heterogeneous network structure in culture may uncover basic mechanisms of emergent information functions of these circuits. In this study, we present such a model designed with two subpopulations of primary hippocampal neurons (E18) with directed connectivity grown in a microfluidic device with asymmetric channels. We analysed and compared neurite growth in the microchannels with various shapes that promoted growth dominantly in one direction. We found an optimal geometric shape features of the microchannels in which the axons coupled two chambers with the neurons. The axons grew in the promoted direction and formed predefined connections during the first 6 days in vitro (DIV). The microfluidic devices were coupled with microelectrode arrays (MEAs) to confirm unidirectional spiking pattern propagation through the microchannels between two compartments. We found that, during culture development, the defined morphological and functional connectivity formed and was maintained for up to 25 DIV.

The advantage of topographic prominence-adopted filter for the detection of short-latency spikes of retinal ganglion cells

Electrical stimulation through retinal prosthesis elicits both short and long-latency retinal ganglion cell (RGC) spikes. Because the short-latency RGC spike is usually obscured by electrical stimulus artifact, it is very important to isolate spike from stimulus artifact. Previously, we showed that topographic prominence (TP) discriminator based algorithm is valid and useful for artifact subtraction. In this study, we compared the performance of forward backward (FB) filter only vs. TP-adopted FB filter for artifact subtraction. From the extracted retinae of rd1 mice, we recorded RGC spikes with 8×8 multielectrode array (MEA). The recorded signals were classified into four groups by distances between the stimulation and recording electrodes on MEA (200-400, 400-600, 600-800, 800-1000 µm). Fifty cathodic phase-1^st biphasic current pulses (duration 500 µs, intensity 5, 10, 20, 30, 40, 50, 60 µA) were applied at every 1 sec. We compared false positive error and false negative error in FB filter and TP-adopted FB filter. By implementing TP-adopted FB filter, short-latency spike can be detected better regarding sensitivity and specificity for detecting spikes regardless of the strength of stimulus and the distance between stimulus and recording electrodes.

Connecting the Brain to Itself through an Emulation

Pilot clinical trials of human patients implanted with devices that can chronically record and stimulate ensembles of hundreds to thousands of individual neurons offer the possibility of expanding the substrate of cognition. Parallel trains of firing rate activity can be delivered in real-time to an array of intermediate external modules that in turn can trigger parallel trains of stimulation back into the brain. These modules may be built in software, VLSI firmware, or biological tissue as in vitro culture preparations or in vivo ectopic construct organoids. Arrays of modules can be constructed as early stage whole brain emulators, following canonical intra- and inter-regional circuits. By using machine learning algorithms and classic tasks known to activate quasi-orthogonal functional connectivity patterns, bedside testing can rapidly identify ensemble tuning properties and in turn cycle through a sequence of external module architectures to explore which can causatively alter perception and behavior. Whole brain emulation both (1) serves to augment human neural function, compensating for disease and injury as an auxiliary parallel system, and (2) has its independent operation bootstrapped by a human-in-the-loop to identify optimal micro- and macro-architectures, update synaptic weights, and entrain behaviors. In this manner, closed-loop brain-computer interface pilot clinical trials can advance strong artificial intelligence development and forge new therapies to restore independence in children and adults with neurological conditions.

Narrow microtunnel technology for the isolation and precise identification of axonal communication among distinct hippocampal subregion networks

Communication between different sub regions of the hippocampus is fundamental to learning and memory. However accurate knowledge about information transfer between sub regions from access to the activity in individual axons is lacking. MEMS devices with microtunnels connecting two sub networks have begun to approach this problem but the commonly used 10 μm wide tunnels frequently measure signals from multiple axons. To reduce this complexity, we compared polydimethylsiloxane (PDMS) microtunnel devices each with a separate tunnel width of 2.5, 5 or 10 μm bridging two wells aligned over a multi electrode array (MEA). Primary rat neurons were grown in the chambers with neurons from the dentate gyrus on one side and hippocampal CA3 on the other. After 2–3 weeks of culture, spontaneous activity in the axons inside the tunnels was recorded. We report electrophysiological, exploratory data analysis for feature clustering and visual evidence to support the expectation that 2.5 μm wide tunnels have fewer axons per tunnel and therefore more clearly delineated signals than 10 or 5 μm wide tunnels. Several measures indicated that fewer axons per electrode enabled more accurate detection of spikes. A clustering analysis comparing the variations of spike height and width for different tunnel widths revealed tighter clusters representing unique spikes with less height and width variation when measured in narrow tunnels. Wider tunnels tended toward more diffuse clusters from a continuum of spike heights and widths. Standard deviations for multiple cluster measures, such as Average Dissimilarity, Silhouette Value (S) and Separation Factor (average dissimilarity/S value), support a conclusion that 2.5 μm wide tunnels containing fewer axons enable more precise determination of individual action potential peaks, their propagation direction, timing, and information transfer between sub networks.

Sparse and Specific Coding during Information Transmission between Co-cultured Dentate Gyrus and CA3 Hippocampal Networks

To better understand encoding and decoding of stimulus information in two specific hippocampal sub-regions, we isolated and co-cultured rat primary dentate gyrus (DG) and CA3 neurons within a two-chamber device with axonal connectivity via micro-tunnels. We tested the hypothesis that, in these engineered networks, decoding performance of stimulus site information would be more accurate when stimuli and information flow occur in anatomically correct feed-forward DG to CA3 vs. CA3 back to DG. In particular, we characterized the neural code of these sub-regions by measuring sparseness and uniqueness of the responses evoked by specific paired-pulse stimuli. We used the evoked responses in CA3 to decode the stimulation sites in DG (and vice-versa) by means of learning algorithms for classification (support vector machine, SVM). The device was placed over an 8 × 8 grid of extracellular electrodes (micro-electrode array, MEA) in order to provide a platform for monitoring development, self-organization, and improved access to stimulation and recording at multiple sites. The micro-tunnels were designed with dimensions 3 × 10 × 400 μm allowing axonal growth but not migration of cell bodies and long enough to exclude traversal by dendrites. Paired-pulse stimulation (inter-pulse interval 50 ms) was applied at 22 different sites and repeated 25 times in each chamber for each sub-region to evoke time-locked activity. DG-DG and CA3-CA3 networks were used as controls. Stimulation in DG drove signals through the axons in the tunnels to activate a relatively small set of specific electrodes in CA3 (sparse code). CA3-CA3 and DG-DG controls were less sparse in coding than CA3 in DG-CA3 networks. Using all target electrodes with the three highest spike rates (14%), the evoked responses in CA3 specified each stimulation site in DG with optimum uniqueness of 64%. Finally, by SVM learning, these evoked responses in CA3 correctly decoded the stimulation sites in DG for 43% of the trials, significantly higher than the reverse, i.e., how well-recording in DG could predict the stimulation site in CA3. In conclusion, our co-cultured model for the in vivo DG-CA3 hippocampal network showed sparse and specific responses in CA3, selectively evoked by each stimulation site in DG.

Multichannel activity propagation across an engineered axon network

OBJECTIVE

Although substantial progress has been made in mapping the connections of the brain, less is known about how this organization translates into brain function. In particular, the massive interconnectivity of the brain has made it difficult to specifically examine data transmission between two nodes of the connectome, a central component of the 'neural code.' Here, we investigated the propagation of multiple streams of asynchronous neuronal activity across an isolated in vitro 'connectome unit.'

APPROACH

We used the novel technique of axon stretch growth to create a model of a long-range cortico-cortical network, a modular system consisting of paired nodes of cortical neurons connected by axon tracts. Using optical stimulation and multi-electrode array recording techniques, we explored how input patterns are represented by cortical networks, how these representations shift as they are transmitted between cortical nodes and perturbed by external conditions, and how well the downstream node distinguishes different patterns.

MAIN RESULTS

Stimulus representations included direct, synaptic, and multiplexed responses that grew in complexity as the distance between the stimulation source and recorded neuron increased. These representations collapsed into patterns with lower information content at higher stimulation frequencies. With internodal activity propagation, a hierarchy of network pathways, including latent circuits, was revealed using glutamatergic blockade. As stimulus channels were added, divergent, non-linear effects were observed in local versus distant network layers. Pairwise difference analysis of neuronal responses suggested that neuronal ensembles generally outperformed individual cells in discriminating input patterns.

SIGNIFICANCE

Our data illuminate the complexity of spiking activity propagation in cortical networks in vitro, which is characterized by the transformation of an input into myriad outputs over several network layers. These results provide insight into how the brain potentially processes information and generates the neural code and could guide the development of clinical therapies based on multichannel brain stimulation.

Relative Contributions of Specific Activity Histories and Spontaneous Processes to Size Remodeling of Glutamatergic Synapses

The idea that synaptic properties are defined by specific pre- and postsynaptic activity histories is one of the oldest and most influential tenets of contemporary neuroscience. Recent studies also indicate, however, that synaptic properties often change spontaneously, even in the absence of specific activity patterns or any activity whatsoever. What, then, are the relative contributions of activity history-dependent and activity history-independent processes to changes synapses undergo? To compare the relative contributions of these processes, we imaged, in spontaneously active networks of cortical neurons, glutamatergic synapses formed between the same axons and neurons or dendrites under the assumption that their similar activity histories should result in similar size changes over timescales of days. The size covariance of such commonly innervated (CI) synapses was then compared to that of synapses formed by different axons (non-CI synapses) that differed in their activity histories. We found that the size covariance of CI synapses was greater than that of non-CI synapses; yet overall size covariance of CI synapses was rather modest. Moreover, momentary and time-averaged sizes of CI synapses correlated rather poorly, in perfect agreement with published electron microscopy-based measurements of mouse cortex synapses. A conservative estimate suggested that ~40% of the observed size remodeling was attributable to specific activity histories, whereas ~10% and ~50% were attributable to cell-wide and spontaneous, synapse-autonomous processes, respectively. These findings demonstrate that histories of naturally occurring activity patterns can direct glutamatergic synapse remodeling but also suggest that the contributions of spontaneous, possibly stochastic, processes are at least as great.

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.

Repeating Spatial-Temporal Motifs of CA3 Activity Dependent on Engineered Inputs from Dentate Gyrus Neurons in Live Hippocampal Networks

Anatomical and behavioral studies, and in vivo and slice electrophysiology of the hippocampus suggest specific functions of the dentate gyrus (DG) and the CA3 subregions, but the underlying activity dynamics and repeatability of information processing remains poorly understood. To approach this problem, we engineered separate living networks of the DG and CA3 neurons that develop connections through 51 tunnels for axonal communication. Growing these networks on top of an electrode array enabled us to determine whether the subregion dynamics were separable and repeatable. We found spontaneous development of polarized propagation of 80% of the activity in the native direction from DG to CA3 and different spike and burst dynamics for these subregions. Spatial-temporal differences emerged when the relationships of target CA3 activity were categorized with to the number and timing of inputs from the apposing network. Compared to times of CA3 activity when there was no recorded tunnel input, DG input led to CA3 activity bursts that were 7× more frequent, increased in amplitude and extended in temporal envelope. Logistic regression indicated that a high number of tunnel inputs predict CA3 activity with 90% sensitivity and 70% specificity. Compared to no tunnel input, patterns of >80% tunnel inputs from DG specified different patterns of first-to-fire neurons in the CA3 target well. Clustering dendrograms revealed repeating motifs of three or more patterns at up to 17 sites in CA3 that were importantly associated with specific spatial-temporal patterns of tunnel activity. The number of these motifs recorded in 3 min was significantly higher than shuffled spike activity and not seen above chance in control networks in which CA3 was apposed to CA3 or DG to DG. Together, these results demonstrate spontaneous input-dependent repeatable coding of distributed activity in CA3 networks driven by engineered inputs from DG networks. These functional configurations at measured times of activation (motifs) emerge from anatomically accurate feed-forward connections from DG through tunnels to CA3.

Feed-Forward Propagation of Temporal and Rate Information between Cortical Populations during Coherent Activation in Engineered In Vitro Networks

Transient propagation of information across neuronal assembles is thought to underlie many cognitive processes. However, the nature of the neural code that is embedded within these transmissions remains uncertain. Much of our understanding of how information is transmitted among these assemblies has been derived from computational models. While these models have been instrumental in understanding these processes they often make simplifying assumptions about the biophysical properties of neurons that may influence the nature and properties expressed. To address this issue we created an in vitro analog of a feed-forward network composed of two small populations (also referred to as assemblies or layers) of living dissociated rat cortical neurons. The populations were separated by, and communicated through, a microelectromechanical systems (MEMS) device containing a strip of microscale tunnels. Delayed culturing of one population in the first layer followed by the second a few days later induced the unidirectional growth of axons through the microtunnels resulting in a primarily feed-forward communication between these two small neural populations. In this study we systematically manipulated the number of tunnels that connected each layer and hence, the number of axons providing communication between those populations. We then assess the effect of reducing the number of tunnels has upon the properties of between-layer communication capacity and fidelity of neural transmission among spike trains transmitted across and within layers. We show evidence based on Victor-Purpura's and van Rossum's spike train similarity metrics supporting the presence of both rate and temporal information embedded within these transmissions whose fidelity increased during communication both between and within layers when the number of tunnels are increased. We also provide evidence reinforcing the role of synchronized activity upon transmission fidelity during the spontaneous synchronized network burst events that propagated between layers and highlight the potential applications of these MEMs devices as a tool for further investigation of structure and functional dynamics among neural populations.

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.

Barbed channels enhance unidirectional connectivity between neuronal networks cultured on multi electrode arrays

Cultured neurons on multi electrode arrays (MEAs) have been widely used to study various aspects of neuronal (network) functioning. A possible drawback of this approach is the lack of structure in these networks. At the single cell level, several solutions have been proposed to enable directed connectivity, and promising results were obtained. At the level of connected sub-populations, a few attempts have been made with promising results. First assessment of the designs' functionality, however, suggested room for further improvement. We designed a two chamber MEA aiming to create a unidirectional connection between the networks in both chambers (“emitting” and “receiving”). To achieve this unidirectionality, all interconnecting channels contained barbs that hindered axon growth in the opposite direction (from receiving to emitting chamber). Visual inspection showed that axons predominantly grew through the channels in the promoted direction. This observation was confirmed by spontaneous activity recordings. Cross-correlation between the signals from two electrodes inside the channels suggested signal propagation at ≈2 m/s from emitting to receiving chamber. Cross-correlation between the firing patterns in both chambers indicated that most correlated activity was initiated in the emitting chamber, which was also reflected by a significantly lower fraction of partial bursts (i.e., a one-chamber-only burst) in the emitting chamber. Finally, electrical stimulation in the emitting chamber induced a fast response in that chamber, and a slower response in the receiving chamber. Stimulation in the receiving chamber evoked a fast response in that chamber, but no response in the emitting chamber. These results confirm the predominantly unidirectional nature of the connecting channels from emitting to receiving chamber.

Functional connectivity in in vitro neuronal assemblies

Complex network topologies represent the necessary substrate to support complex brain functions. In this work, we reviewed in vitro neuronal networks coupled to Micro-Electrode Arrays (MEAs) as biological substrate. Networks of dissociated neurons developing in vitro and coupled to MEAs, represent a valid experimental model for studying the mechanisms governing the formation, organization and conservation of neuronal cell assemblies. In this review, we present some examples of the use of statistical Cluster Coefficients and Small World indices to infer topological rules underlying the dynamics exhibited by homogeneous and engineered neuronal networks.