A novel lab-on-chip platform enabling axotomy and neuromodulation in a multi-nodal network

Functional Complexity of Engineered Neural Networks Self-Organized on Structured 3D Interfaces

Engineered neural networks are indispensable tools for studying neural function and dysfunction in controlled microenvironments. In vitro, neurons self-organize into complex assemblies with structural and functional features reminiscent to those observed for in vivo circuits. Traditionally, these models are established on planar interfaces, but studies suggest that the lack of a 3D growth space affects neuronal organization and function. While methods supporting 3D growth exist, reproducible 3D neuroengineering techniques compatible with electrophysiological recording methods are still needed. In this study, a reproducible biocompatible interface made of the polymer SU-8 to support 3D network development is developed. Using electron microscopy and immunocytochemistry, it is shown that neurons utilize these 3D interfaces to self-assemble into complex, multi-layered 3D networks. Furthermore, interfacing the 3D structures with custom microelectrode arrays enables characterizing of electrophysiological activity. Both planar control networks and 3D networks display complex interactions with integrated and segregated functional dynamics. However, control networks show stronger functional interconnections, higher entropy, and increased firing rates. In summary, the interfaces provide a versatile approach for supporting neural networks with a 3D growth environment, compatible with assorted electrophysiology and imaging techniques. This system can offer new insights into the impact of 3D topologies on neural network organization and function.

Biomaterials for neuroengineering: applications and challenges

Neurological injuries and diseases are a leading cause of disability worldwide, underscoring the urgent need for effective therapies. Neural regaining and enhancement therapies are seen as the most promising strategies for restoring neural function, offering hope for individuals affected by these conditions. Despite their promise, the path from animal research to clinical application is fraught with challenges. Neuroengineering, particularly through the use of biomaterials, has emerged as a key field that is paving the way for innovative solutions to these challenges. It seeks to understand and treat neurological disorders, unravel the nature of consciousness, and explore the mechanisms of memory and the brain's relationship with behavior, offering solutions for neural tissue engineering, neural interfaces and targeted drug delivery systems. These biomaterials, including both natural and synthetic types, are designed to replicate the cellular environment of the brain, thereby facilitating neural repair. This review aims to provide a comprehensive overview for biomaterials in neuroengineering, highlighting their application in neural functional regaining and enhancement across both basic research and clinical practice. It covers recent developments in biomaterial-based products, including 2D to 3D bioprinted scaffolds for cell and organoid culture, brain-on-a-chip systems, biomimetic electrodes and brain-computer interfaces. It also explores artificial synapses and neural networks, discussing their applications in modeling neural microenvironments for repair and regeneration, neural modulation and manipulation and the integration of traditional Chinese medicine. This review serves as a comprehensive guide to the role of biomaterials in advancing neuroengineering solutions, providing insights into the ongoing efforts to bridge the gap between innovation and clinical application.

Nanoporous platinum microelectrode arrays for neuroscience applications

Microelectrode arrays are invaluable tools for investigating the electrophysiological behaviour of neuronal networks with high spatiotemporal precision. In recent years, it has become increasingly common to functionalize such electrodes with highly porous platinum to increase their effective surface area, and hence their signal-to-noise ratio. Although such functionalization significantly improves the electrochemical performance of the electrodes, the impact of various electrode morphologies on biocompatibility and electrophysiological performance in cell cultures remains poorly understood. In this study, we introduce reproducible protocols for depositing highly porous platinum with varying morphologies on microelectrodes designed for neural cell cultures. We also evaluate the impact of morphology and electrode size on the signal-to-noise ratio in recordings from rat cortical neurons cultured on these electrodes. Our results indicate that electrodes with a uniform layer of highly nanoporous platinum offer the best trade-off between biocompatibility, electrochemical, and electrophysiological performance. While more microporous electrodes exhibited lower impedance, nanoporous electrodes detected higher extracellular signal amplitudes from neurons, suggesting reduced distance between perisomatic neuronal areas and the electrodes. Additionally, these nanoporous electrodes showed fewer thickness variations at their edges compared to the more porous electrodes. Such edges can be mechanically broken off during cell culturing and contribute to long-term cytotoxic effects, which is highly undesirable. We hope this work will contribute to better standardization in creating and utilizing nanoporous platinum microelectrodes for neuroscience applications. Improving the accessibility and reproducibility of this technology is crucial for enhancing the quality of electrophysiological data and advancing our understanding of neuronal network function and dysfunction.

Recent Progress in PDMS-Based Microfluidics Toward Integrated Organ-on-a-Chip Biosensors and Personalized Medicine

The organ-on-a-chip (OoC) technology holds significant promise for biosensors and personalized medicine by enabling the creation of miniature, patient-specific models of human organs. This review studies the recent advancements in the application of polydimethylsiloxane (PDMS) microfluidics for OoC purposes. It underscores the main fabrication technologies of PDMS microfluidic systems, such as photolithography, injection molding, hot embossing, and 3D printing. The review also highlights the crucial role of integrated biosensors within OoC platforms. These electrochemical, electrical, and optical sensors, integrated within the microfluidic environment, provide valuable insights into cellular behavior and drug response. Furthermore, the review explores the exciting potential of PDMS-based OoC technology for personalized medicine. OoC devices can forecast drug effectiveness and tailor therapeutic strategies for patients by incorporating patient-derived cells and replicating individual physiological variations, helping the healing process and accelerating recovery. This personalized approach can revolutionize healthcare by offering more precise and efficient treatment options. Understanding OoC fabrication and its applications in biosensors and personalized medicine can play a pivotal role in future implementations of multifunctional OoC biosensors.

Evolving alterations of structural organization and functional connectivity in feedforward neural networks after induced P301L tau mutation

Reciprocal structure-function relationships underlie both healthy and pathological behaviours in complex neural networks. Thus, understanding neuropathology and network dysfunction requires a thorough investigation of the complex interactions between structural and functional network reconfigurations in response to perturbation. Such adaptations are often difficult to study in vivo. For example, subtle, evolving changes in synaptic connectivity, transmission and the electrophysiological shift from healthy to pathological states, for example alterations that may be associated with evolving neurodegenerative disease, such as Alzheimer's, are difficult to study in the brain. Engineered in vitro neural networks are powerful models that enable selective targeting, manipulation and monitoring of dynamic neural network behaviour at the micro- and mesoscale in physiological and pathological conditions. In this study, we engineered feedforward cortical neural networks using two-nodal microfluidic devices with controllable connectivity interfaced with microelectrode arrays (mMEAs). We induced P301L mutated tau protein to the presynaptic node of these networks and monitored network dynamics over three weeks. Induced perturbation resulted in altered structural organization and extensive axonal retraction starting in the perturbed node. Perturbed networks also exhibited functional changes in intranodal activity, which manifested as an overall decline in both firing rate and bursting activity, with a progressive increase in synchrony over time and a decrease in internodal signal propagation between pre- and post-synaptic nodes. These results provide insights into dynamic structural and functional reconfigurations at the micro- and mesoscale as a result of evolving pathology and illustrate the utility of engineered networks as models of network function and dysfunction.

Exploring Kainic Acid-Induced Alterations in Circular Tripartite Networks with Advanced Analysis Tools

Brain activity implies the orchestrated functioning of interconnected brain regions. Typical in vitro models aim to mimic the brain using single human pluripotent stem cell-derived neuronal networks. However, the field is constantly evolving to model brain functions more accurately through the use of new paradigms, e.g., brain-on-a-chip models with compartmentalized structures and integrated sensors. These methods create novel data requiring more complex analysis approaches. The previously introduced circular tripartite network concept models the connectivity between spatially diverse neuronal structures. The model consists of a microfluidic device allowing axonal connectivity between separated neuronal networks with an embedded microelectrode array to record both local and global electrophysiological activity patterns in the closed circuitry. The existing tools are suboptimal for the analysis of the data produced with this model. Here, we introduce advanced tools for synchronization and functional connectivity assessment. We used our custom-designed analysis to assess the interrelations between the kainic acid (KA)-exposed proximal compartment and its nonexposed distal neighbors before and after KA. Novel multilevel circuitry bursting patterns were detected and analyzed in parallel with the inter- and intracompartmental functional connectivity. The effect of KA on the proximal compartment was captured, and the spread of this effect to the nonexposed distal compartments was revealed. KA induced divergent changes in bursting behaviors, which may be explained by distinct baseline activity and varied intra- and intercompartmental connectivity strengths. The circular tripartite network concept combined with our developed analysis advances importantly both face and construct validity in modeling human epilepsy in vitro.

The Profile of Network Spontaneous Activity and Functional Organization Interplay in Hierarchically Connected Modular Neural Networks In Vitro

Modern microtechnology methods are widely used to create neural networks on a chip with a connection architecture demonstrating properties of modularity and hierarchy similar to brain networks. Such in vitro networks serve as a valuable model for studying the interplay of functional architecture within modules, their activity, and the effectiveness of inter-module interaction. In this study, we use a two-chamber microfluidic platform to investigate functional connectivity and global activity in hierarchically connected modular neural networks. We found that the strength of functional connections within the module and the profile of network spontaneous activity determine the effectiveness of inter-modular interaction and integration activity in the network. The direction of intermodular activity propagation configures the different densities of inhibitory synapses in the network. The developed microfluidic platform holds the potential to explore function-structure relationships and efficient information processing in two- or multilayer neural networks, in both healthy and pathological states.

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.

Organ-on-a-Chip: Ubi sumus? Fundamentals and Design Aspects

This review outlines the evolutionary journey from traditional two-dimensional (2D) cell culture to the revolutionary field of organ-on-a-chip technology. Organ-on-a-chip technology integrates microfluidic systems to mimic the complex physiological environments of human organs, surpassing the limitations of conventional 2D cultures. This evolution has opened new possibilities for understanding cell-cell interactions, cellular responses, drug screening, and disease modeling. However, the design and manufacture of microchips significantly influence their functionality, reliability, and applicability to different biomedical applications. Therefore, it is important to carefully consider design parameters, including the number of channels (single, double, or multi-channels), the channel shape, and the biological context. Simultaneously, the selection of appropriate materials compatible with the cells and fabrication methods optimize the chips' capabilities for specific applications, mitigating some disadvantages associated with these systems. Furthermore, the success of organ-on-a-chip platforms greatly depends on the careful selection and utilization of cell resources. Advances in stem cell technology and tissue engineering have contributed to the availability of diverse cell sources, facilitating the development of more accurate and reliable organ-on-a-chip models. In conclusion, a holistic perspective of in vitro cellular modeling is provided, highlighting the integration of microfluidic technology and meticulous chip design, which play a pivotal role in replicating organ-specific microenvironments. At the same time, the sensible use of cell resources ensures the fidelity and applicability of these innovative platforms in several biomedical applications.

A Comprehensive Review of Organ-on-a-Chip Technology and Its Applications

Organ-on-a-chip (OOC) is an emerging technology that simulates an artificial organ within a microfluidic cell culture chip. Current cell biology research focuses on in vitro cell cultures due to various limitations of in vivo testing. Unfortunately, in-vitro cell culturing fails to provide an accurate microenvironment, and in vivo cell culturing is expensive and has historically been a source of ethical controversy. OOC aims to overcome these shortcomings and provide the best of both in vivo and in vitro cell culture research. The critical component of the OOC design is utilizing microfluidics to ensure a stable concentration gradient, dynamic mechanical stress modeling, and accurate reconstruction of a cellular microenvironment. OOC also has the advantage of complete observation and control of the system, which is impossible to recreate in in-vivo research. Multiple throughputs, channels, membranes, and chambers are constructed in a polydimethylsiloxane (PDMS) array to simulate various organs on a chip. Various experiments can be performed utilizing OOC technology, including drug delivery research and toxicology. Current technological expansions involve multiple organ microenvironments on a single chip, allowing for studying inter-tissue interactions. Other developments in the OOC technology include finding a more suitable material as a replacement for PDMS and minimizing artefactual error and non-translatable differences.

Micro-and mesoscale aspects of neurodegeneration in engineered human neural networks carrying the LRRK2 G2019S mutation

Mutations in the leucine-rich repeat kinase 2 (LRRK2) gene have been widely linked to Parkinson's disease, where the G2019S variant has been shown to contribute uniquely to both familial and sporadic forms of the disease. LRRK2-related mutations have been extensively studied, yet the wide variety of cellular and network events related to these mutations remain poorly understood. The advancement and availability of tools for neural engineering now enable modeling of selected pathological aspects of neurodegenerative disease in human neural networks in vitro. Our study revealed distinct pathology associated dynamics in engineered human cortical neural networks carrying the LRRK2 G2019S mutation compared to healthy isogenic control neural networks. The neurons carrying the LRRK2 G2019S mutation self-organized into networks with aberrant morphology and mitochondrial dynamics, affecting emerging structure-function relationships both at the micro-and mesoscale. Taken together, the findings of our study points toward an overall heightened metabolic demand in networks carrying the LRRK2 G2019S mutation, as well as a resilience to change in response to perturbation, compared to healthy isogenic controls.

Neuron(s)-on-a-Chip: A Review of the Design and Use of Microfluidic Systems for Neural Tissue Culture

Neuron-on-chip (NoC) systems-microfluidic devices in which neurons are cultured-have become a promising alternative to replace or minimize the use of animal models and have greatly facilitated in vitro research. Here, we review and discuss current developments in neuron-on-chip platforms, with a particular emphasis on existing biological models, culturing techniques, biomaterials, and topologies. We also discuss how the architecture, flow, and gradients affect neuronal growth, differentiation, and development. Finally, we discuss some of the most recent applications of NoCs in fundamental research (i.e., studies on the effects of electrical, mechanical/topological, or chemical stimuli) and in disease modeling.

Microfluidic Brain-on-a-Chip: From Key Technology to System Integration and Application

As an ideal in vitro model, brain-on-chip (BoC) is an important tool to comprehensively elucidate brain characteristics. However, the in vitro model for the definition scope of BoC has not been universally recognized. In this review, BoC is divided into brain cells-on-a- chip, brain slices-on-a-chip, and brain organoids-on-a-chip according to the type of culture on the chip. Although these three microfluidic BoCs are constructed in different ways, they all use microfluidic chips as carrier tools. This method can better meet the needs of maintaining high culture activity on a chip for a long time. Moreover, BoC has successfully integrated cell biology, the biological material platform technology of microenvironment on a chip, manufacturing technology, online detection technology on a chip, and so on, enabling the chip to present structural diversity and high compatibility to meet different experimental needs and expand the scope of applications. Here, the relevant core technologies, challenges, and future development trends of BoC are summarized.

Using Human-Induced Pluripotent Stem Cell Derived Neurons on Microelectrode Arrays to Model Neurological Disease: A Review

In situ physiological signals of in vitro neural disease models are essential for studying pathogenesis and drug screening. Currently, an increasing number of in vitro neural disease models are established using human-induced pluripotent stem cell (hiPSC) derived neurons (hiPSC-DNs) to overcome interspecific gene expression differences. Microelectrode arrays (MEAs) can be readily interfaced with two-dimensional (2D), and more recently, three-dimensional (3D) neural stem cell-derived in vitro models of the human brain to monitor their physiological activity in real time. Therefore, MEAs are emerging and useful tools to model neurological disorders and disease in vitro using human iPSCs. This is enabling a real-time window into neuronal signaling at the network scale from patient derived. This paper provides a comprehensive review of MEA's role in analyzing neural disease models established by hiPSC-DNs. It covers the significance of MEA fabrication, surface structure and modification schemes for hiPSC-DNs culturing and signal detection. Additionally, this review discusses advances in the development and use of MEA technology to study in vitro neural disease models, including epilepsy, autism spectrum developmental disorder (ASD), and others established using hiPSC-DNs. The paper also highlights the application of MEAs combined with hiPSC-DNs in detecting in vitro neurotoxic substances. Finally, the future development and outlook of multifunctional and integrated devices for in vitro medical diagnostics and treatment are discussed.

Recent advances in sensor-integrated brain-on-a-chip devices for real-time brain monitoring

Brain science has remained in the global spotlight as an important field of scientific and technological discovery. Numerous in vitro and in vivo animal studies have been performed to understand the pathological processes involved in brain diseases and develop strategies for their diagnosis and treatment. However, owing to species differences between animals and humans, several drugs have shown high rates of treatment failure in clinical settings, hindering the development of diagnostic and treatment modalities for brain diseases. In this scenario, microfluidic brain-on-a-chip (BOC) devices, which allow the direct use of human tissues for experiments, have emerged as novel tools for effectively avoiding species differences and performing screening for new drugs. Although microfluidic BOC technology has achieved significant progress in recent years, monitoring slight changes in neurochemicals, neurotransmitters, and environmental states in the brain has remained challenging owing to the brain's complex environment. Hence, the integration of BOC with new sensors that have high sensitivity and high selectivity is urgently required for the real-time dynamic monitoring of BOC parameters. As sensor-based technologies for BOC have not been summarized, here, we review the principle, fabrication process, and application-based classification of sensor-integrated BOC, and then summarize the opportunities and challenges for their development. Generally, sensor-integrated BOC enables real-time monitoring and dynamic analysis, accurately measuring minute changes in the brain and thus enabling the realization of in vivo brain analysis and drug development.

Advances in Nerve Injury Models on a Chip

Regeneration and functional recovery of the damaged nerve are challenging due to the need for effective therapeutic drugs, biomaterials, and approaches. The poor outcome of the treatment of nerve injury stems from the incomplete understanding of axonal biology and interactions between neurons and the surrounding environment, such as glial cells and extracellular matrix. Microfluidic devices, in combination with various injury techniques, have been applied to test biological hypotheses in nerve injury and nerve regeneration. The microfluidic devices provide multiple advantages over the in vitro cell culture on a petri dish and in vivo animal models because a specific part of the neuronal environment can be manipulated using physical and chemical interventions. In addition, single-cell behavior and interactions between neurons and glial cells can be visualized and quantified on microfluidic platforms. In this article, current in vitro nerve injury models on a chip that mimics in vivo axonal injuries and the regeneration process of axons are summarized. The microfluidic-based nerve injury models could enhance the understanding of the physiological and pathophysiological mechanisms of nerve tissues and simultaneously serve as powerful drug and biomaterial screening platforms.

Microfluidic Bi-Layer Platform to Study Functional Interaction between Co-Cultured Neural Networks with Unidirectional Synaptic Connectivity

The complex synaptic connectivity architecture of neuronal networks underlies cognition and brain function. However, studying the spiking activity propagation and processing in heterogeneous networks in vivo poses significant challenges. In this study, we present a novel two-layer PDMS chip that facilitates the culturing and examination of the functional interaction of two interconnected neural networks. We utilized cultures of hippocampal neurons grown in a two-chamber microfluidic chip combined with a microelectrode array. The asymmetric configuration of the microchannels between the chambers ensured the growth of axons predominantly in one direction from the Source chamber to the Target chamber, forming two neuronal networks with unidirectional synaptic connectivity. We showed that the local application of tetrodotoxin (TTX) to the Source network did not alter the spiking rate in the Target network. The results indicate that stable network activity in the Target network was maintained for at least 1-3 h after TTX application, demonstrating the feasibility of local chemical activity modulation and the influence of electrical activity from one network on the other. Additionally, suppression of synaptic activity in the Source network by the application of CPP and CNQX reorganized spatio-temporal characteristics of spontaneous and stimulus-evoked spiking activity in the Target network. The proposed methodology and results provide a more in-depth examination of the network-level functional interaction between neural circuits with heterogeneous synaptic connectivity.

Biosensor integrated brain-on-a-chip platforms: Progress and prospects in clinical translation

Because of the brain's complexity, developing effective treatments for neurological disorders is a formidable challenge. Research efforts to this end are advancing as in vitro systems have reached the point that they can imitate critical components of the brain's structure and function. Brain-on-a-chip (BoC) was first used for microfluidics-based systems with small synthetic tissues but has expanded recently to include in vitro simulation of the central nervous system (CNS). Defining the system's qualifying parameters may improve the BoC for the next generation of in vitro platforms. These parameters show how well a given platform solves the problems unique to in vitro CNS modeling (like recreating the brain's microenvironment and including essential parts like the blood-brain barrier (BBB)) and how much more value it offers than traditional cell culture systems. This review provides an overview of the practical concerns of creating and deploying BoC systems and elaborates on how these technologies might be used. Not only how advanced biosensing technologies could be integrated with BoC system but also how novel approaches will automate assays and improve point-of-care (PoC) diagnostics and accurate quantitative analyses are discussed. Key challenges providing opportunities for clinical translation of BoC in neurodegenerative disorders are also addressed.

Recent Progress and Perspectives on Neural Chip Platforms Integrating PDMS-Based Microfluidic Devices and Microelectrode Arrays

Recent years have witnessed a spurt of progress in the application of the encoding and decoding of neural activities to drug screening, diseases diagnosis, and brain-computer interactions. To overcome the constraints of the complexity of the brain and the ethical considerations of in vivo research, neural chip platforms integrating microfluidic devices and microelectrode arrays have been raised, which can not only customize growth paths for neurons in vitro but also monitor and modulate the specialized neural networks grown on chips. Therefore, this article reviews the developmental history of chip platforms integrating microfluidic devices and microelectrode arrays. First, we review the design and application of advanced microelectrode arrays and microfluidic devices. After, we introduce the fabrication process of neural chip platforms. Finally, we highlight the recent progress on this type of chip platform as a research tool in the field of brain science and neuroscience, focusing on neuropharmacology, neurological diseases, and simplified brain models. This is a detailed and comprehensive review of neural chip platforms. This work aims to fulfill the following three goals: (1) summarize the latest design patterns and fabrication schemes of such platforms, providing a reference for the development of other new platforms; (2) generalize several important applications of chip platforms in the field of neurology, which will attract the attention of scientists in the field; and (3) propose the developmental direction of neural chip platforms integrating microfluidic devices and microelectrode arrays.

Integrated biosensors for monitoring microphysiological systems

Microphysiological systems (MPSs), also known as organ-on-a-chip models, aim to recapitulate the functional components of human tissues or organs in vitro. Over the last decade, with the advances in biomaterials, 3D bioprinting, and microfluidics, numerous MPSs have emerged with applications to study diseased and healthy tissue models. Various organs have been modeled using MPS technology, such as the heart, liver, lung, and blood-brain barrier. An important aspect of in vitro modeling is the accurate phenotypical and functional characterization of the modeled organ. However, most conventional characterization methods are invasive and destructive and do not allow continuous monitoring of the cells in culture. On the other hand, microfluidic biosensors enable in-line, real-time sensing of target molecules with an excellent limit of detection and in a non-invasive manner, thereby effectively overcoming the limitation of the traditional techniques. Consequently, microfluidic biosensors have been increasingly integrated into MPSs and used for in-line target detection. This review discusses the state-of-the-art microfluidic biosensors by providing specific examples, detailing their main advantages in monitoring MPSs, and highlighting current developments in this field. Finally, we describe the remaining challenges and potential future developments to advance the current state-of-the-art in integrated microfluidic biosensors.

Validation of Functional Connectivity of Engineered Neuromuscular Junction With Recombinant Monosynaptic Pseudotyped ΔG-Rabies Virus Tracing

Current preclinical models of neurodegenerative disease, such as amyotrophic lateral sclerosis (ALS), can significantly benefit from in vitro neuroengineering approaches that enable the selective study and manipulation of neurons, networks, and functional units of interest. Custom-designed compartmentalized microfluidic culture systems enable the co-culture of different relevant cell types in interconnected but fluidically isolated microenvironments. Such systems can thus be applied for ALS disease modeling, as they enable the recapitulation and study of neuromuscular junctions (NMJ) through co-culturing of motor neurons and muscle cells in separate, but interconnected compartments. These in vitro systems are particularly relevant for investigations of mechanistic aspects of the ALS pathological cascade in engineered NMJ, as progressive loss of NMJ functionality may constitute one of the hallmarks of disease related pathology at early onset, in line with the dying back hypothesis. In such models, ability to test whether motor neuron degeneration in ALS starts at the nerve terminal or at the NMJ and retrogradely progresses to the motor neuron cell body largely relies on robust methods for verification of engineered NMJ functionality. In this study, we demonstrate the functionality of engineered NMJs within a microfluidic chip with a differentially perturbable microenvironment using a designer pseudotyped ΔG-rabies virus for retrograde monosynaptic tracing.

Intervertebral Disc-on-a-Chip as Advanced In Vitro Model for Mechanobiology Research and Drug Testing: A Review and Perspective

Discogenic back pain is one of the most diffused musculoskeletal pathologies and a hurdle to a good quality of life for millions of people. Existing therapeutic options are exclusively directed at reducing symptoms, not at targeting the underlying, still poorly understood, degenerative processes. Common intervertebral disc (IVD) disease models still do not fully replicate the course of degenerative IVD disease. Advanced disease models that incorporate mechanical loading are needed to investigate pathological causes and processes, as well as to identify therapeutic targets. Organs-on-chip (OoC) are microfluidic-based devices that aim at recapitulating tissue functions in vitro by introducing key features of the tissue microenvironment (e.g., 3D architecture, soluble signals and mechanical conditioning). In this review we analyze and depict existing OoC platforms used to investigate pathological alterations of IVD cells/tissues and discuss their benefits and limitations. Starting from the consideration that mechanobiology plays a pivotal role in both IVD homeostasis and degeneration, we then focus on OoC settings enabling to recapitulate physiological or aberrant mechanical loading, in conjunction with other relevant features (such as inflammation). Finally, we propose our view on design criteria for IVD-on-a-chip systems, offering a future perspective to model IVD mechanobiology.

Novel, Emerging Chip Models of the Blood-Brain Barrier and Future Directions

The use of microfluidic chips is now allowing for more advanced modelling of the blood-brain barrier (BBB) in vitro, recapitulating heterotypic interactions, 3D architecture, and physiological flow. This chapter will give an introduction to these new technologies and how they are being applied to model the BBB and neurovascular unit (NVU). A foundational understanding of the fluid dynamics germane to the effective use of these chips will be set and an overview of how physical phenomena at the microscale can be exploited to enable new possibilities to control the cell culture environment. The four main approaches to construct microfluidic blood vessel mimetics will be discussed with examples of how these techniques are being applied to model the BBB and more recently to study specific neurovascular disease processes. Finally, practical guidance will be given for researchers wishing to adopt these new techniques along with a summary of the challenges, limitations faced, and new opportunities opened up by these advanced cell culture systems.

Functional Characterization of Human Pluripotent Stem Cell-Derived Models of the Brain with Microelectrode Arrays

Human pluripotent stem cell (hPSC)-derived neuron cultures have emerged as models of electrical activity in the human brain. Microelectrode arrays (MEAs) measure changes in the extracellular electric potential of cell cultures or tissues and enable the recording of neuronal network activity. MEAs have been applied to both human subjects and hPSC-derived brain models. Here, we review the literature on the functional characterization of hPSC-derived two- and three-dimensional brain models with MEAs and examine their network function in physiological and pathological contexts. We also summarize MEA results from the human brain and compare them to the literature on MEA recordings of hPSC-derived brain models. MEA recordings have shown network activity in two-dimensional hPSC-derived brain models that is comparable to the human brain and revealed pathology-associated changes in disease models. Three-dimensional hPSC-derived models such as brain organoids possess a more relevant microenvironment, tissue architecture and potential for modeling the network activity with more complexity than two-dimensional models. hPSC-derived brain models recapitulate many aspects of network function in the human brain and provide valid disease models, but certain advancements in differentiation methods, bioengineering and available MEA technology are needed for these approaches to reach their full potential.

Bayesian supervised machine learning classification of neural networks with pathological perturbations

Objective.Extraction of temporal features of neuronal activity from electrophysiological data can be used for accurate classification of neural networks in healthy and pathologically perturbed conditions. In this study, we provide an extensive approach for the classification of humanin vitroneural networks with and without an underlying pathology, from electrophysiological recordings obtained using a microelectrode array (MEA) platform.Approach.We developed a Dirichlet mixture (DM) Point Process statistical model able to extract temporal features related to neurons. We then applied a machine learning algorithm to discriminate between healthy control and pathologically perturbedin vitroneural networks.Main Results.We found a high degree of separability between the classes using DM point process features (p-value <0.001 for all the features, paired t-test), which reaches 93.10 of accuracy (92.37 of ROC AUC) with the Random Forest classifier. In particular, results show a higher latency in firing for pathologically perturbed neurons (43 ± 16 ms versus 67 ± 31 ms,μIGfeature distribution).Significance.Our approach has been successful in extracting temporal features related to the neurons' behaviour, as well as distinguishing healthy from pathologically perturbed networks, including classification of responses to a transient induced perturbation.

Advances in microfluidic in vitro systems for neurological disease modeling

Neurological disorders are the leading cause of disability and the second largest cause of death worldwide. Despite significant research efforts, neurology remains one of the most failure-prone areas of drug development. The complexity of the human brain, boundaries to examining the brain directly in vivo, and the significant evolutionary gap between animal models and humans, all serve to hamper translational success. Recent advances in microfluidic in vitro models have provided new opportunities to study human cells with enhanced physiological relevance. The ability to precisely micro-engineer cell-scale architecture, tailoring form and function, has allowed for detailed dissection of cell biology using microphysiological systems (MPS) of varying complexities from single cell systems to "Organ-on-chip" models. Simplified neuronal networks have allowed for unique insights into neuronal transport and neurogenesis, while more complex 3D heterotypic cellular models such as neurovascular unit mimetics and "Organ-on-chip" systems have enabled new understanding of metabolic coupling and blood-brain barrier transport. These systems are now being developed beyond MPS toward disease specific micro-pathophysiological systems, moving from "Organ-on-chip" to "Disease-on-chip." This review gives an outline of current state of the art in microfluidic technologies for neurological disease research, discussing the challenges and limitations while highlighting the benefits and potential of integrating technologies. We provide examples of where such toolsets have enabled novel insights and how these technologies may empower future investigation into neurological diseases.

Integrating Biosensors in Organs-on-Chip Devices: A Perspective on Current Strategies to Monitor Microphysiological Systems

Organs-on-chip (OoC), often referred to as microphysiological systems (MPS), are advanced in vitro tools able to replicate essential functions of human organs. Owing to their unprecedented ability to recapitulate key features of the native cellular environments, they represent promising tools for tissue engineering and drug screening applications. The achievement of proper functionalities within OoC is crucial; to this purpose, several parameters (e.g., chemical, physical) need to be assessed. Currently, most approaches rely on off-chip analysis and imaging techniques. However, the urgent demand for continuous, noninvasive, and real-time monitoring of tissue constructs requires the direct integration of biosensors. In this review, we focus on recent strategies to miniaturize and embed biosensing systems into organs-on-chip platforms. Biosensors for monitoring biological models with metabolic activities, models with tissue barrier functions, as well as models with electromechanical properties will be described and critically evaluated. In addition, multisensor integration within multiorgan platforms will be further reviewed and discussed.

Current ex Vivo and in Vitro Approaches to Uncovering Mechanisms of Neurological Dysfunction after Traumatic Brain Injury

Traumatic brain injury often leads to progressive alterations at the molecular to circuit levels resulting in epilepsy and memory impairments. Ex vivo and in vitro models have provided a powerful platform for investigating the multimodal alteration after trauma. Recent ex vivo analyses using voltage sensitive dye imaging, optogenetics, and glutamate uncaging have revealed circuit abnormalities following in vivo brain injury. In vitro injury models have enabled examination of early and progressive changes in activity while development of three-dimensional organoids derived from human induced pluripotent stem cells have opened novel avenues for injury research. Here, we highlight recent advances in ex vivo and in vitro systems, focusing on their potential for advancing mechanistic understandings, possible limitations, and implications for therapeutics.

Layer-By-Layer: The Case for 3D Bioprinting Neurons to Create Patient-Specific Epilepsy Models

The ability to create three-dimensional (3D) models of brain tissue from patient-derived cells, would open new possibilities in studying the neuropathology of disorders such as epilepsy and schizophrenia. While organoid culture has provided impressive examples of patient-specific models, the generation of organised 3D structures remains a challenge. 3D bioprinting is a rapidly developing technology where living cells, encapsulated in suitable bioink matrices, are printed to form 3D structures. 3D bioprinting may provide the capability to organise neuronal populations in 3D, through layer-by-layer deposition, and thereby recapitulate the complexity of neural tissue. However, printing neuron cells raises particular challenges since the biomaterial environment must be of appropriate softness to allow for the neurite extension, properties which are anathema to building self-supporting 3D structures. Here, we review the topic of 3D bioprinting of neurons, including critical discussions of hardware and bio-ink formulation requirements.