Caged neuron MEA: a system for long-term investigation of cultured neural network connectivity

Portrait of intense communications within microfluidic neural networks

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

Synthesis of encapsulated ZnO nanowires provide low impedance alternatives for microelectrodes

Microelectrodes are commonly used in electrochemical analysis and biological sensing applications owing to their miniaturised dimensions. It is often desirable to improve the performance of microelectrodes by reducing their electrochemical impedance for increasing the signal-to-noise of the recorded signals. One successful route is to incorporate nanomaterials directly onto microelectrodes; however, it is essential that these fabrication routes are simple and repeatable. In this article, we demonstrate how to synthesise metal encapsulated ZnO nanowires (Cr/Au-ZnO NWs, Ti-ZnO NWs and Pt-ZnO NWs) to reduce the impedance of the microelectrodes. Electrochemical impedance modelling and characterisation of Cr/Au-ZnO NWs, Ti-ZnO NWs and Pt-ZnO NWs are carried out in conjunction with controls of planar Cr/Au and pristine ZnO NWs. It was found that the ZnO NW microelectrodes that were encapsulated with a 10 nm thin layer of Ti or Pt demonstrated the lowest electrochemical impedance of 400 ± 25 kΩ at 1 kHz. The Ti and Pt encapsulated ZnO NWs have the potential to offer an alternative microelectrode modality that could be attractive to electrochemical and biological sensing applications.

Neurons-on-a-Chip: In Vitro NeuroTools

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

Basic Research Approaches to Evaluate Cardiac Arrhythmia in Heart Failure and Beyond

Patients with heart failure often develop cardiac arrhythmias. The mechanisms and interrelations linking heart failure and arrhythmias are not fully understood. Historically, research into arrhythmias has been performed on affected individuals or in vivo (animal) models. The latter however is constrained by interspecies variation, demands to reduce animal experiments and cost. Recent developments in in vitro induced pluripotent stem cell technology and in silico modelling have expanded the number of models available for the evaluation of heart failure and arrhythmia. An agnostic approach, combining the modalities discussed here, has the potential to improve our understanding for appraising the pathology and interactions between heart failure and arrhythmia and can provide robust and validated outcomes in a variety of research settings. This review discusses the state of the art models, methodologies and techniques used in the evaluation of heart failure and arrhythmia and will highlight the benefits of using them in combination. Special consideration is paid to assessing the pivotal role calcium handling has in the development of heart failure and arrhythmia.

The Future of Neurotoxicology: A Neuroelectrophysiological Viewpoint

Neuroelectrophysiology is an old science, dating to the 18th century when electrical activity in nerves was discovered. Such discoveries have led to a variety of neurophysiological techniques, ranging from basic neuroscience to clinical applications. These clinical applications allow assessment of complex neurological functions such as (but not limited to) sensory perception (vision, hearing, somatosensory function), and muscle function. The ability to use similar techniques in both humans and animal models increases the ability to perform mechanistic research to investigate neurological problems. Good animal to human homology of many neurophysiological systems facilitates interpretation of data to provide cause-effect linkages to epidemiological findings. Mechanistic cellular research to screen for toxicity often includes gaps between cellular and whole animal/person neurophysiological changes, preventing understanding of the complete function of the nervous system. Building Adverse Outcome Pathways (AOPs) will allow us to begin to identify brain regions, timelines, neurotransmitters, etc. that may be Key Events (KE) in the Adverse Outcomes (AO). This requires an integrated strategy, from in vitro to in vivo (and hypothesis generation, testing, revision). Scientists need to determine intermediate levels of nervous system organization that are related to an AO and work both upstream and downstream using mechanistic approaches. Possibly more than any other organ, the brain will require networks of pathways/AOPs to allow sufficient predictive accuracy. Advancements in neurobiological techniques should be incorporated into these AOP-base neurotoxicological assessments, including interactions between many regions of the brain simultaneously. Coupled with advancements in optogenetic manipulation, complex functions of the nervous system (such as acquisition, attention, sensory perception, etc.) can be examined in real time. The integration of neurophysiological changes with changes in gene/protein expression can begin to provide the mechanistic underpinnings for biological changes. Establishment of linkages between changes in cellular physiology and those at the level of the AO will allow construction of biological pathways (AOPs) and allow development of higher throughput assays to test for changes to critical physiological circuits. To allow mechanistic/predictive toxicology of the nervous system to be protective of human populations, neuroelectrophysiology has a critical role in our future.

A Single-Neuron: Current Trends and Future Prospects

The brain is an intricate network with complex organizational principles facilitating a concerted communication between single-neurons, distinct neuron populations, and remote brain areas. The communication, technically referred to as connectivity, between single-neurons, is the center of many investigations aimed at elucidating pathophysiology, anatomical differences, and structural and functional features. In comparison with bulk analysis, single-neuron analysis can provide precise information about neurons or even sub-neuron level electrophysiology, anatomical differences, pathophysiology, structural and functional features, in addition to their communications with other neurons, and can promote essential information to understand the brain and its activity. This review highlights various single-neuron models and their behaviors, followed by different analysis methods. Again, to elucidate cellular dynamics in terms of electrophysiology at the single-neuron level, we emphasize in detail the role of single-neuron mapping and electrophysiological recording. We also elaborate on the recent development of single-neuron isolation, manipulation, and therapeutic progress using advanced micro/nanofluidic devices, as well as microinjection, electroporation, microelectrode array, optical transfection, optogenetic techniques. Further, the development in the field of artificial intelligence in relation to single-neurons is highlighted. The review concludes with between limitations and future prospects of single-neuron analyses.

Nanowired Bioelectric Interfaces

Biological systems have evolved biochemical, electrical, mechanical, and genetic networks to perform essential functions across various length and time scales. High-aspect-ratio biological nanowires, such as bacterial pili and neurites, mediate many of the interactions and homeostasis in and between these networks. Synthetic materials designed to mimic the structure of biological nanowires could also incorporate similar functional properties, and exploiting this structure-function relationship has already proved fruitful in designing biointerfaces. Semiconductor nanowires are a particularly promising class of synthetic nanowires for biointerfaces, given (1) their unique optical and electronic properties and (2) their high degree of synthetic control and versatility. These characteristics enable fabrication of a variety of electronic and photonic nanowire devices, allowing for the formation of well-defined, functional bioelectric interfaces at the biomolecular level to the whole-organ level. In this Focus Review, we first discuss the history of bioelectric interfaces with semiconductor nanowires. We next highlight several important, endogenous biological nanowires and use these as a framework to categorize semiconductor nanowire-based biointerfaces. Within this framework we then review the fundamentals of bioelectric interfaces with semiconductor nanowires and comment on both material choice and device design to form biointerfaces spanning multiple length scales. We conclude with a discussion of areas with the potential for greatest impact using semiconductor nanowire-enabled biointerfaces in the future.

Discerning Functional Connections in the Pulsed Neural Networks with the Dynamic Bayesian Network Structure Search Method Based on a Genetic Algorithm

It is important to explore potential structural characteristics of biological networks and regulatory mechanisms of network behaviors at the system level. In this study, a dynamic Bayesian network structure search method (DBNSSM) based on a genetic algorithm is employed to infer and locate functional connections in pulsed neural networks (PNNs) as typical artificial neural networks. In the process of network structure searching, a minimum description length score is calculated for each candidate network structure. The score indicates two characteristics of the network structure: (1) the likelihood based on network dynamic response data and (2) the complexity. Both should be considered together on selecting network structures. The DBNSSM is applied to analyze time-series data from PNNs, thereby discerns functional connections showing network structures collectively. It is feasible to analyze multichannel electrophysiological data of biological neural networks using the DBNSSM.

Bundling of axons through a capillary alginate gel enhances the detection of axonal action potentials using microelectrode arrays

Microelectrode arrays (MEAs) have become important tools in high throughput assessment of neuronal activity. However, geometric and electrical constraints largely limit their ability to detect action potentials to the neuronal soma. Enhancing the resolution of these systems to detect axonal action potentials has proved both challenging and complex. In this study, we have bundled sensory axons from dorsal root ganglia through a capillary alginate gel (Capgel™) interfaced with an MEA and observed an enhanced ability to detect spontaneous axonal activity compared with two-dimensional cultures. Moreover, this arrangement facilitated the long-term monitoring of spontaneous activity from the same bundle of axons at a single electrode. Finally, using waveform analysis for cultures treated with the nociceptor agonist capsaicin, we were able to dissect action potentials from multiple axons on an individual electrode, suggesting that this model can reproduce the functional complexity associated with sensory fascicles in vivo. This novel three-dimensional functional model of the peripheral nerve can be used to study the functional complexities of peripheral neuropathies and nerve regeneration as well as being utilized in the development of novel therapeutics.

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

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

Rewiring of neuronal networks during synaptic silencing

Analyzing the connectivity of neuronal networks, based on functional brain imaging data, has yielded new insight into brain circuitry, bringing functional and effective networks into the focus of interest for understanding complex neurological and psychiatric disorders. However, the analysis of network changes, based on the activity of individual neurons, is hindered by the lack of suitable meaningful and reproducible methodologies. Here, we used calcium imaging, statistical spike time analysis and a powerful classification model to reconstruct effective networks of primary rat hippocampal neurons in vitro. This method enables the calculation of network parameters, such as propagation probability, path length, and clustering behavior through the measurement of synaptic activity at the single-cell level, thus providing a fuller understanding of how changes at single synapses translate to an entire population of neurons. We demonstrate that our methodology can detect the known effects of drug-induced neuronal inactivity and can be used to investigate the extensive rewiring processes affecting population-wide connectivity patterns after periods of induced neuronal inactivity.

Interactions of Neurons with Physical Environments

Nerve growth strongly relies on multiple chemical and physical signals throughout development and regeneration. Currently, a cure for injured neuronal tissue is an unmet need. Recent advances in fabrication technologies and materials led to the development of synthetic interfaces for neurons. Such engineered platforms that come in 2D and 3D forms can mimic the native extracellular environment and create a deeper understanding of neuronal growth mechanisms, and ultimately advance the development of potential therapies for neuronal regeneration. This progress report aims to present a comprehensive discussion of this field, focusing on physical feature design and fabrication with additional information about considerations of chemical modifications. We review studies of platforms generated with a range of topographies, from micro-scale features down to topographical elements at the nanoscale that demonstrate effective interactions with neuronal cells. Fabrication methods are discussed as well as their biological outcomes. This report highlights the interplay between neuronal systems and the important roles played by topography on neuronal differentiation, outgrowth, and development. The influence of substrate structures on different neuronal cells and parameters including cell fate, outgrowth, intracellular remodeling, gene expression and activity is discussed. Matching these effects to specific needs may lead to the emergence of clinical solutions for patients suffering from neuronal injuries or brain-machine interface (BMI) applications.

A new microfluidic device design for a defined positioning of neurons in vitro

A new triangle-shaped microfluidic channel system for defined cell trapping is presented. Different variants of the same basic geometry were produced to reveal the best fitting parameter combinations regarding efficiency and sensitivity. Variants with differences in the trap gap width and the inter-trap distance were analyzed in detail by Computational Fluid Dynamics simulations and in experiments with artificial beads of different sizes (30, 60, 80 μm). Simulation analysis of flow dynamics and pressure profiles revealed strongly reduced pressure conditions and balanced flow rates inside the microfluidic channels compared to commonly used systems with meandering channels. Quantitative experiments with beads showed very good trapping results in all channel types with slight variations due to geometrical differences. Highest efficiency in terms of fast trap filling and low particle loss was shown with channel types having a larger trap gap width (20 μm) and/or a larger inter-trap distance (400 μm). Here, experimental success was achieved in almost 85% to 100% of all cases. Particle loss appeared significantly more often with large beads than with small beads. A significantly reduced trapping efficiency of about 50% was determined by using narrow trap gaps and a small inter-trap distance in combination with large 80 μm beads. The combination of the same parameters with small and medium beads led to an only slight decrease in trapping efficiency (80%). All channel types were tested qualitatively with invertebrate neurons from the pond snail Lymnaea stagnalis. The systems were appropriate to trap those sensitive neurons and to keep their viability in the trapping area at the same time.

Cytokines and cytokine networks target neurons to modulate long-term potentiation

Cytokines play crucial roles in the communication between brain cells including neurons and glia, as well as in the brain-periphery interactions. In the brain, cytokines modulate long-term potentiation (LTP), a cellular correlate of memory. Whether cytokines regulate LTP by direct effects on neurons or by indirect mechanisms mediated by non-neuronal cells is poorly understood. Elucidating neuron-specific effects of cytokines has been challenging because most brain cells express cytokine receptors. Moreover, cytokines commonly increase the expression of multiple cytokines in their target cells, thus increasing the complexity of brain cytokine networks even after single-cytokine challenges. Here, we review evidence on both direct and indirect-mediated modulation of LTP by cytokines. We also describe novel approaches based on neuron- and synaptosome-enriched systems to identify cytokines able to directly modulate LTP, by targeting neurons and synapses. These approaches can test multiple samples in parallel, thus allowing the study of multiple cytokines simultaneously. Hence, a cytokine networks perspective coupled with neuron-specific analysis may contribute to delineation of maps of the modulation of LTP by cytokines.

SiMEA: a framework for simulating neurons on multi-electrode array

A Multi-Electrode Array (MEA) is a practical device for recording the extracellular activity of in-vitro biological culture. Such culture - for instance neurons - is prone to mistakes leading to irrelevant recordings or no recording at all. Additionally, with the expenses generated by in-vitro culture, minimizing risks is a must. This paper proposes a framework designed and implemented for simulating the spatial positioning of neuronal cultures on a MEA. The framework serves as a sandbox for researchers to simulate the model of their MEA experiments before its eventual in-vitro implementation. The framework enables simulating the density of the plated culture, the death of cells over time, choosing diverse reconstructed morphologies of cells, and simulating their spiking activity in interaction with Brian2 simulator.

Advances in nanowire bioelectronics

Semiconductor nanowires represent powerful building blocks for next generation bioelectronics given their attractive properties, including nanometer-scale footprint comparable to subcellular structures and bio-molecules, configurable in nonstandard device geometries readily interfaced with biological systems, high surface-to-volume ratios, fast signal responses, and minimum consumption of energy. In this review article, we summarize recent progress in the field of nanowire bioelectronics with a focus primarily on silicon nanowire field-effect transistor biosensors. First, the synthesis and assembly of semiconductor nanowires will be described, including the basics of nanowire FETs crucial to their configuration as biosensors. Second, we will introduce and review recent results in nanowire bioelectronics for biomedical applications ranging from label-free sensing of biomolecules, to extracellular and intracellular electrophysiological recording.

A Novel Robot System Integrating Biological and Mechanical Intelligence Based on Dissociated Neural Network-Controlled Closed-Loop Environment

We propose the architecture of a novel robot system merging biological and artificial intelligence based on a neural controller connected to an external agent. We initially built a framework that connected the dissociated neural network to a mobile robot system to implement a realistic vehicle. The mobile robot system characterized by a camera and two-wheeled robot was designed to execute the target-searching task. We modified a software architecture and developed a home-made stimulation generator to build a bi-directional connection between the biological and the artificial components via simple binomial coding/decoding schemes. In this paper, we utilized a specific hierarchical dissociated neural network for the first time as the neural controller. Based on our work, neural cultures were successfully employed to control an artificial agent resulting in high performance. Surprisingly, under the tetanus stimulus training, the robot performed better and better with the increasement of training cycle because of the short-term plasticity of neural network (a kind of reinforced learning). Comparing to the work previously reported, we adopted an effective experimental proposal (i.e. increasing the training cycle) to make sure of the occurrence of the short-term plasticity, and preliminarily demonstrated that the improvement of the robot's performance could be caused independently by the plasticity development of dissociated neural network. This new framework may provide some possible solutions for the learning abilities of intelligent robots by the engineering application of the plasticity processing of neural networks, also for the development of theoretical inspiration for the next generation neuro-prostheses on the basis of the bi-directional exchange of information within the hierarchical neural networks.

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.

Qualitative and quantitative estimation of comprehensive synaptic connectivity in short- and long-term cultured rat hippocampal neurons with new analytical methods inspired by Scatchard and Hill plots

To investigate comprehensive synaptic connectivity, we examined Ca(2+) responses with quantitative electric current stimulation by indium-tin-oxide (ITO) glass electrode with transparent and high electro-conductivity. The number of neurons with Ca(2+) responses was low during the application of stepwise increase of electric current in short-term cultured neurons (less than 17 days in-vitro (DIV)). The neurons cultured over 17 DIV showed two-type responses: S-shaped (sigmoid) and monotonous saturated responses, and Scatchard plots well illustrated the difference of these two responses. Furthermore, sigmoid like neural network responses over 17 DIV were altered to the monotonous saturated ones by the application of the mixture of AP5 and CNQX, specific blockers of NMDA and AMPA receptors, respectively. This alternation was also characterized by the change of Hill coefficients. These findings indicate that the neural network with sigmoid-like responses has strong synergetic or cooperative synaptic connectivity via excitatory glutamate synapses.

Interfacing Inorganic Nanowire Arrays and Living Cells for Cellular Function Analysis

Inorganic nanowires are among the most attractive functional materials, which have emerged in the past two decades. They have demonstrated applications in information technology and energy conversion, but their utility in biological or biomedical research remains relatively under-explored. Although nanowire-based sensors have been frequently reported for biomolecular detection, interfacing nanowire arrays and living mammalian cells for the direct analysis of cellular functions is a very recent endeavor. Cell-penetrating nanowires enabled effective delivery of biomolecules, electrical and optical stimulation and recording of intracellular signals over a long period of time. Non-penetrating, high-density nanowire arrays display rich interactions between the nanostructured substrate and the micro/nanoscale features of cell surfaces. Such interactions enable efficient capture of rare cells including circulating tumor cells and trafficking leukocytes from complex biospecimens. It also serves as a platform for probing cell traction force and neuronal guidance. The most recent advances in the field that exploits nanowire arrays (both penetrating and non-penetrating) to perform rapid analysis of cellular functions potentially for disease diagnosis and monitoring are reviewed.

Agarose-Based Substrate Modification Technique for Chemical and Physical Guiding of Neurons In Vitro

A new low cost and highly reproducible technique is presented that provides patterned cell culture substrates. These allow for selective positioning of cells and a chemically and mechanically directed guiding of their extensions. The patterned substrates consist of structured agarose hydrogels molded from reusable silicon micro templates. These templates consist of pins arranged equidistantly in squares, connected by bars, which mold corresponding wells and channels in the nonadhesive agarose hydrogel. Subsequent slice production with a standard vibratome, comprising the described template pattern, completes substrate production. Invertebrate neurons of locusts and pond snails are used for this application as they offer the advantage over vertebrate cells as being very large and suitable for cultivation in low cell density. Their neurons adhere to and grow only on the adhesive areas not covered by the agarose. Agarose slices of 50 μm thickness placed on glass, polystyrene, or MEA surfaces position and immobilize the neurons in the wells, and the channels guide their neurite outgrowth toward neighboring wells. In addition to the application with invertebrate neurons, the technique may also provide the potential for the application of a wide range of cell types. Long-term objective is the achievement of isolated low-density neuronal networks on MEAs or different culture substrates for various network analysis applications.

Sloppiness in spontaneously active neuronal networks

Various plasticity mechanisms, including experience-dependent, spontaneous, as well as homeostatic ones, continuously remodel neural circuits. Yet, despite fluctuations in the properties of single neurons and synapses, the behavior and function of neuronal assemblies are generally found to be very stable over time. This raises the important question of how plasticity is coordinated across the network. To address this, we investigated the stability of network activity in cultured rat hippocampal neurons recorded with high-density multielectrode arrays over several days. We used parametric models to characterize multineuron activity patterns and analyzed their sensitivity to changes. We found that the models exhibited sloppiness, a property where the model behavior is insensitive to changes in many parameter combinations, but very sensitive to a few. The activity of neurons with sloppy parameters showed faster and larger fluctuations than the activity of a small subset of neurons associated with sensitive parameters. Furthermore, parameter sensitivity was highly correlated with firing rates. Finally, we tested our observations from cell cultures on an in vivo recording from monkey visual cortex and we confirm that spontaneous cortical activity also shows hallmarks of sloppy behavior and firing rate dependence. Our findings suggest that a small subnetwork of highly active and stable neurons supports group stability, and that this endows neuronal networks with the flexibility to continuously remodel without compromising stability and function.

Application of hierarchical dissociated neural network in closed-loop hybrid system integrating biological and mechanical intelligence

Neural networks are considered the origin of intelligence in organisms. In this paper, a new design of an intelligent system merging biological intelligence with artificial intelligence was created. It was based on a neural controller bidirectionally connected to an actual mobile robot to implement a novel vehicle. Two types of experimental preparations were utilized as the neural controller including 'random' and '4Q' (cultured neurons artificially divided into four interconnected parts) neural network. Compared to the random cultures, the '4Q' cultures presented absolutely different activities, and the robot controlled by the '4Q' network presented better capabilities in search tasks. Our results showed that neural cultures could be successfully employed to control an artificial agent; the robot performed better and better with the stimulus because of the short-term plasticity. A new framework is provided to investigate the bidirectional biological-artificial interface and develop new strategies for a future intelligent system using these simplified model systems.

A single-cell correlative nanoelectromechanosensing approach to detect cancerous transformation: monitoring the function of F-actin microfilaments in the modulation of the ion channel activity

Cancerous transformation may be dependent on correlation between electrical disruptions in the cell membrane and mechanical disruptions of cytoskeleton structures. Silicon nanotube (SiNT)-based electrical probes, as ultra-accurate signal recorders with subcellular resolution, may create many opportunities for fundamental biological research and biomedical applications. Here, we used this technology to electrically monitor cellular mechanosensing. The SiNT probe was combined with an electrically activated glass micropipette aspiration system to achieve a new cancer diagnostic technique that is based on real-time correlation between mechanical and electrical behaviour of single cells. Our studies demonstrated marked changes in the electrical response following increases in the mechanical aspiration force in healthy cells. In contrast, such responses were extremely weak for malignant cells. Confocal microscopy results showed the impact of actin microfilament remodelling on the reduction of the electrical response for aspirated cancer cells due to the significant role of actin in modulating the ion channel activity in the cell membrane.

Spatial information in large-scale neural recordings

To record from a given neuron, a recording technology must be able to separate the activity of that neuron from the activity of its neighbors. Here, we develop a Fisher information based framework to determine the conditions under which this is feasible for a given technology. This framework combines measurable point spread functions with measurable noise distributions to produce theoretical bounds on the precision with which a recording technology can localize neural activities. If there is sufficient information to uniquely localize neural activities, then a technology will, from an information theoretic perspective, be able to record from these neurons. We (1) describe this framework, and (2) demonstrate its application in model experiments. This method generalizes to many recording devices that resolve objects in space and should be useful in the design of next-generation scalable neural recording systems.

‘Body-on-a-Chip’ Technology and Supporting Microfluidics

In order to effectively streamline current drug development protocols, there is a need to generate high information content preclinical screens capable of generating data with a predictive power in relation to the activity of novel therapeutics in humans. Given the poor predictive power of animal models, and the lack of complexity and interconnectivity of standard in vitro culture methodologies, many investigators are now moving toward the development of physiologically and functionally accurate culture platforms composed of human cells to investigate cellular responses to drug compounds in high-throughput preclinical studies. The generation of complex, multi-organ in vitro platforms, built to recapitulate physiological dimensions, flow rates and shear stresses, is being investigated as the logical extension of this drive. Production and application of a biologically accurate multi-organ platform, or ‘body-on-a-chip’, would facilitate the correct modelling of the dynamic and interconnected state of living systems for high-throughput drug studies as well as basic and applied biomolecular research. This chapter will discuss current technologies aimed at producing ‘body-on-a-chip’ models, as well as highlighting recent advances and important challenges still to be met in the development of biomimetic single-organ systems for drug development purposes.

Label-free characterization of emerging human neuronal networks

The emergent self-organization of a neuronal network in a developing nervous system is the result of a remarkably orchestrated process involving a multitude of chemical, mechanical and electrical signals. Little is known about the dynamic behavior of a developing network (especially in a human model) primarily due to a lack of practical and non-invasive methods to measure and quantify the process. Here we demonstrate that by using a novel optical interferometric technique, we can non-invasively measure several fundamental properties of neural networks from the sub-cellular to the cell population level. We applied this method to quantify network formation in human stem cell derived neurons and show for the first time, correlations between trends in the growth, transport, and spatial organization of such a system. Quantifying the fundamental behavior of such cell lines without compromising their viability may provide an important new tool in future longitudinal studies.

Sub-10-nm intracellular bioelectronic probes from nanowire-nanotube heterostructures

The miniaturization of bioelectronic intracellular probes with a wide dynamic frequency range can open up opportunities to study biological structures inaccessible by existing methods in a minimally invasive manner. Here, we report the design, fabrication, and demonstration of intracellular bioelectronic devices with probe sizes less than 10 nm. The devices are based on a nanowire-nanotube heterostructure in which a nanowire field-effect transistor detector is synthetically integrated with a nanotube cellular probe. Sub-10-nm nanotube probes were realized by a two-step selective etching approach that reduces the diameter of the nanotube free-end while maintaining a larger diameter at the nanowire detector necessary for mechanical strength and electrical sensitivity. Quasi-static water-gate measurements demonstrated selective device response to solution inside the nanotube, and pulsed measurements together with numerical simulations confirmed the capability to record fast electrophysiological signals. Systematic studies of the probe bandwidth in different ionic concentration solutions revealed the underlying mechanism governing the time response. In addition, the bandwidth effect of phospholipid coatings, which are important for intracellular recording, was investigated and modeled. The robustness of these sub-10-nm bioelectronics probes for intracellular interrogation was verified by optical imaging and recording the transmembrane resting potential of HL-1 cells. These ultrasmall bioelectronic probes enable direct detection of cellular electrical activity with highest spatial resolution achieved to date, and with further integration into larger chip arrays could provide a unique platform for ultra-high-resolution mapping of activity in neural networks and other systems.

Sub-10-nm intracellular bioelectronic probes from nanowire-nanotube heterostructures

The miniaturization of bioelectronic intracellular probes with a wide dynamic frequency range can open up opportunities to study biological structures inaccessible by existing methods in a minimally invasive manner. Here, we report the design, fabrication, and demonstration of intracellular bioelectronic devices with probe sizes less than 10 nm. The devices are based on a nanowire-nanotube heterostructure in which a nanowire field-effect transistor detector is synthetically integrated with a nanotube cellular probe. Sub-10-nm nanotube probes were realized by a two-step selective etching approach that reduces the diameter of the nanotube free-end while maintaining a larger diameter at the nanowire detector necessary for mechanical strength and electrical sensitivity. Quasi-static water-gate measurements demonstrated selective device response to solution inside the nanotube, and pulsed measurements together with numerical simulations confirmed the capability to record fast electrophysiological signals. Systematic studies of the probe bandwidth in different ionic concentration solutions revealed the underlying mechanism governing the time response. In addition, the bandwidth effect of phospholipid coatings, which are important for intracellular recording, was investigated and modeled. The robustness of these sub-10-nm bioelectronics probes for intracellular interrogation was verified by optical imaging and recording the transmembrane resting potential of HL-1 cells. These ultrasmall bioelectronic probes enable direct detection of cellular electrical activity with highest spatial resolution achieved to date, and with further integration into larger chip arrays could provide a unique platform for ultra-high-resolution mapping of activity in neural networks and other systems.

Nano-volume drop patterning for rapid on-chip neuronal connect-ability assays

The ability of neurons to extend projections and to form physical connections among them (i.e., "connect-ability") is altered in several neuropathologies. The quantification of these alterations is an important read-out to investigate pathogenic mechanisms and for research and development of neuropharmacological therapies, however current morphological analysis methods are very time-intensive. Here, we present and characterize a novel on-chip approach that we propose as a rapid assay. Our approach is based on the definition on a neuronal cell culture substrate of discrete patterns of adhesion protein spots (poly-d-lysine, 23 ± 5 μm in diameter) characterized by controlled inter-spot separations of increasing distance (from 40 μm to 100 μm), locally adsorbed in an adhesion-repulsive agarose layer. Under these conditions, the connect-ability of wild type primary neurons from rodents is shown to be strictly dependent on the inter-spot distance, and can be rapidly documented by simple optical read-outs. Moreover, we applied our approach to identify connect-ability defects in neurons from a mouse model of 22q11.2 deletion syndrome/DiGeorge syndrome, by comparative trials with wild type preparations. The presented results demonstrate the sensitivity and reliability of this novel on-chip-based connect-ability approach and validate the use of this method for the rapid assessment of neuronal connect-ability defects in neuropathologies.

Nanoelectronics meets biology: from new nanoscale devices for live-cell recording to 3D innervated tissues

High spatiotemporal resolution interfaces between electrical sensors and biological systems, from single live cells to tissues, is crucial for many areas, including fundamental biophysical studies as well as medical monitoring and intervention. Herein, we summarize recent progress in the development and application of novel nanoscale devices for intracellular electrical recording of action potentials and the effort of merging electronic and biological systems seamlessly in three dimensions by using macroporous nanoelectronic scaffolds. The uniqueness of these nanoscale devices for minimally invasive, large-scale, high spatial resolution, and three-dimensional neural activity mapping are highlighted.

Nanoelectronics-biology frontier: From nanoscopic probes for action potential recording in live cells to three-dimensional cyborg tissues

Semiconductor nanowires configured as the active channels of field-effect transistors (FETs) have been used as detectors for high-resolution electrical recording from single live cells, cell networks, tissues and organs. Extracellular measurements with substrate supported silicon nanowire (SiNW) FETs, which have projected active areas orders of magnitude smaller than conventional microfabricated multielectrode arrays (MEAs) and planar FETs, recorded action potential and field potential signals with high signal-to-noise ratio and temporal resolution from cultured neurons, cultured cardiomyocytes, acute brain slices and whole animal hearts. Measurements made with modulation-doped nanoscale active channel SiNW FETs demonstrate that signals recorded from cardiomyocytes are highly localized and have improved time resolution compared to larger planar detectors. In addition, several novel three-dimensional (3D) transistor probes, which were realized using advanced nanowire synthesis methods, have been implemented for intracellular recording. These novel probes include (i) flexible 3D kinked nanowire FETs, (ii) branched intracellular nanotube SiNW FETs, and (iii) active silicon nanotube FETs. Following phospholipid modification of the probes to mimic the cell membrane, the kinked nanowire, branched intracellular nanotube and active silicon nanotube FET probes recorded full-amplitude intracellular action potentials from spontaneously firing cardiomyocytes. Moreover, these probes demonstrated the capability of reversible, stable, and long-term intracellular recording, thus indicating the minimal invasiveness of the new nanoscale structures and suggesting biomimetic internalization via the phospholipid modification. Simultaneous, multi-site intracellular recording from both single cells and cell networks were also readily achieved by interfacing independently addressable nanoprobe devices with cells. Finally, electronic and biological systems have been seamlessly merged in 3D for the first time using macroporous nanoelectronic scaffolds that are analogous to synthetic tissue scaffold and the extracellular matrix in tissue. Free-standing 3D nanoelectronic scaffolds were cultured with neurons, cardiomyocytes and smooth muscle cells to yield electronically-innervated synthetic or 'cyborg' tissues. Measurements demonstrate that innervated tissues exhibit similar cell viability as with conventional tissue scaffolds, and importantly, demonstrate that the real-time response to drugs and pH changes can be mapped in 3D through the tissues. These results open up a new field of research, wherein nanoelectronics are merged with biological systems in 3D thereby providing broad opportunities, ranging from a nanoelectronic/tissue platform for real-time pharmacological screening in 3D to implantable 'cyborg' tissues enabling closed-loop monitoring and treatment of diseases. Furthermore, the capability of high density scale-up of the above extra- and intracellular nanoscopic probes for action potential recording provide important tools for large-scale high spatio-temporal resolution electrical neural activity mapping in both 2D and 3D, which promises to have a profound impact on many research areas, including the mapping of activity within the brain.

Control of neural network patterning using collagen gel photothermal etching

Two-dimensional (2D) micropatterning techniques have been developed to guide dissociated neurons into predefined distributions on solid substrates, such as glass and plastic. Micropatterning methods using three-dimensional (3D) substrates or scaffolds that reproduce aspects of the in vivo microenvironment could facilitate the engineering of functional tissues for transplantation or more robust experimental models. We developed a 3D collagen gel photothermal etching method using an infrared laser that precisely controls the area of cell adhesion and neurite projection by etching a small targeted section of the collage gel. It was then possible to guide neural network formation under microscopic observation. After conventional cell seeding, we succeeded in creating isolated 3D networks, while controlling (1) the number of each neural subtype (neurons, glia, and fluorescently-labeled neurons) and (2) the direction of neurite elongation. Neurons seeded on a 10-μm-thick collagen gel survived longer and projected greater numbers of neurites than neurons growing on 2D culture substrates. Intracellular Ca(2+) imaging revealed both synchronous and discordant oscillations in different neuronal populations that suggested the pattern and strength of synaptic connectivity. This photothermal etching technique allows for the creation of designed 3D neural networks during cultivation for use in studies of synaptic transmission, neuron-glial signaling, pathogenesis, and drug responses.

Microtechnologies to fuel neurobiological research with nanometer precision

The interface between engineering and molecular life sciences has been fertile ground for advancing our understanding of complex biological systems. Engineered microstructures offer a diverse toolbox for cellular and molecular biologists to direct the placement of cells and small organisms, and to recreate biological functions in vitro: cells can be positioned and connected in a designed fashion, and connectivity and community effects of cells studied. Because of the highly polar morphology and finely compartmentalized functions of neurons, microfabricated cell culture systems and related on-chip technologies have become an important enabling platform for studying development, function and degeneration of the nervous system at the molecular and cellular level. Here we review some of the compartmentalization techniques developed so far to highlight how high-precision control of neuronal connectivity allows new approaches for studying axonal and synaptic biology.

Nanowire electrodes for high-density stimulation and measurement of neural circuits

Brain-machine interfaces (BMIs) that can precisely monitor and control neural activity will likely require new hardware with improved resolution and specificity. New nanofabricated electrodes with feature sizes and densities comparable to neural circuits may lead to such improvements. In this perspective, we review the recent development of vertical nanowire (NW) electrodes that could provide highly parallel single-cell recording and stimulation for future BMIs. We compare the advantages of these devices and discuss some of the technical challenges that must be overcome for this technology to become a platform for next-generation closed-loop BMIs.

Advances in microfluidics-based experimental methods for neuroscience research

The application of microfluidics to neuroscience applications has always appealed to neuroscientists because of the capability to control the cellular microenvironment in both a spatial and temporal manner. Recently, there has been rapid development of biological micro-electro-mechanical systems (BioMEMS) for both fundamental and applied neuroscience research. In this review, we will discuss the applications of BioMEMS to various topics in the field of neuroscience. The purpose of this review is to summarise recent advances in the components and design of the BioMEMS devices, in vitro disease models, electrophysiology and neural stem cell research. We envision that microfluidics will play a key role in future neuroscience research, both fundamental and applied research.

A simplified micropatterning method for straight-line neurite extension of cultured hippocampal neurons

We report a simplified micropatterning method for the straight-line extension of the neurites of cultured neurons. We prepared a poly-D-lysine (PDL)-patterned surface using a polydimethylsiloxane microfluidic stamp. Hippocampal neurons were cultured on the PDL-bound substrate with the stamp removed, allowing for conventional cell seeding and detailed optical observation without fluorescent label. Cultured neurons elongated neurites along straight lines at the single-cell level and displayed spontaneous firing as detected by time-lapse imaging and Ca(2+) imaging.

Multi-compartment neuron-glia co-culture platform for localized CNS axon-glia interaction study

Formation of myelin sheaths by oligodendrocytes (OLs) in the central nervous system (CNS) is essential for rapid nerve impulse conduction. Reciprocal signaling between axons and OLs orchestrates myelinogenesis but remains largely elusive. In this study, we present a multi-compartment CNS neuron-glia microfluidic co-culture platform. The platform is capable of conducting parallel localized drug and biomolecule treatments while carrying out multiple co-culture conditions in a single device for studying axon-glia interactions at a higher throughput. The "micro-macro hybrid soft-lithography master fabrication" (MMHSM) technique enables a large number of precisely replicated PDMS devices incorporating both millimeter and micrometer scale structures to be rapidly fabricated without any manual reservoir punching processes. Axons grown from the neuronal somata were physically and fluidically isolated inside the six satellite axon/glia compartments for localized treatments. Astrocytes, when seeded and co-cultured after the establishment of the isolated axons in the satellite axon/glia compartments, were found to physically damage the established axonal layer, as they tend to grow underneath the axons. In contrast, oligodendrocyte progenitor cells (OPCs) could be co-cultured successfully with the isolated axons and differentiated into mature myelin basic protein-expressing OLs with processes aligning to neighboring axons. OPCs inside the six axon/glia compartments were treated with a high concentration of ceramide (150 μM) to confirm the fluidic isolation among the satellite compartments. In addition, isolated axons were treated with varying concentrations of chondroitin sulfate proteoglycan (CSPG, 0-25 μg ml(-1)) within a single device to demonstrate the parallel localized biomolecular treatment capability of the device. These results indicate that the proposed platform can be used as a powerful tool to study CNS axonal biology and axon-glia interactions with the capacity for localized biomolecular treatments.

Model-free reconstruction of excitatory neuronal connectivity from calcium imaging signals

A systematic assessment of global neural network connectivity through direct electrophysiological assays has remained technically infeasible, even in simpler systems like dissociated neuronal cultures. We introduce an improved algorithmic approach based on Transfer Entropy to reconstruct structural connectivity from network activity monitored through calcium imaging. We focus in this study on the inference of excitatory synaptic links. Based on information theory, our method requires no prior assumptions on the statistics of neuronal firing and neuronal connections. The performance of our algorithm is benchmarked on surrogate time series of calcium fluorescence generated by the simulated dynamics of a network with known ground-truth topology. We find that the functional network topology revealed by Transfer Entropy depends qualitatively on the time-dependent dynamic state of the network (bursting or non-bursting). Thus by conditioning with respect to the global mean activity, we improve the performance of our method. This allows us to focus the analysis to specific dynamical regimes of the network in which the inferred functional connectivity is shaped by monosynaptic excitatory connections, rather than by collective synchrony. Our method can discriminate between actual causal influences between neurons and spurious non-causal correlations due to light scattering artifacts, which inherently affect the quality of fluorescence imaging. Compared to other reconstruction strategies such as cross-correlation or Granger Causality methods, our method based on improved Transfer Entropy is remarkably more accurate. In particular, it provides a good estimation of the excitatory network clustering coefficient, allowing for discrimination between weakly and strongly clustered topologies. Finally, we demonstrate the applicability of our method to analyses of real recordings of in vitro disinhibited cortical cultures where we suggest that excitatory connections are characterized by an elevated level of clustering compared to a random graph (although not extreme) and can be markedly non-local.

Unraveling the general organizing principles of connectivity in neural circuits is a crucial step towards understanding brain function. However, even the simpler task of assessing the global excitatory connectivity of a culture in vitro, where neurons form self-organized networks in absence of external stimuli, remains challenging. Neuronal cultures undergo spontaneous switching between episodes of synchronous bursting and quieter inter-burst periods. We introduce here a novel algorithm which aims at inferring the connectivity of neuronal cultures from calcium fluorescence recordings of their network dynamics. To achieve this goal, we develop a suitable generalization of Transfer Entropy, an information-theoretic measure of causal influences between time series. Unlike previous algorithmic approaches to reconstruction, Transfer Entropy is data-driven and does not rely on specific assumptions about neuronal firing statistics or network topology. We generate simulated calcium signals from networks with controlled ground-truth topology and purely excitatory interactions and show that, by restricting the analysis to inter-bursts periods, Transfer Entropy robustly achieves a good reconstruction performance for disparate network connectivities. Finally, we apply our method to real data and find evidence of non-random features in cultured networks, such as the existence of highly connected hub excitatory neurons and of an elevated (but not extreme) level of clustering.

Emergent functional properties of neuronal networks with controlled topology

The interplay between anatomical connectivity and dynamics in neural networks plays a key role in the functional properties of the brain and in the associated connectivity changes induced by neural diseases. However, a detailed experimental investigation of this interplay at both cellular and population scales in the living brain is limited by accessibility. Alternatively, to investigate the basic operational principles with morphological, electrophysiological and computational methods, the activity emerging from large in vitro networks of primary neurons organized with imposed topologies can be studied. Here, we validated the use of a new bio-printing approach, which effectively maintains the topology of hippocampal cultures in vitro and investigated, by patch-clamp and MEA electrophysiology, the emerging functional properties of these grid-confined networks. In spite of differences in the organization of physical connectivity, our bio-patterned grid networks retained the key properties of synaptic transmission, short-term plasticity and overall network activity with respect to random networks. Interestingly, the imposed grid topology resulted in a reinforcement of functional connections along orthogonal directions, shorter connectivity links and a greatly increased spiking probability in response to focal stimulation. These results clearly demonstrate that reliable functional studies can nowadays be performed on large neuronal networks in the presence of sustained changes in the physical network connectivity.

Spatio-temporal inter-ictal activity recorded from human epileptic hippocampal slices

Epilepsy is a medical syndrome that produces seizures affecting a variety of mental and physical functions. The actual mechanisms of the onset and termination of the seizure are still unclear. While medical therapies can suppress the symptoms of seizures, 30% of patients do not respond well. Temporal lobectomy is a common surgical treatment for medically refractory epilepsy. Part of the hippocampus is removed from the patient. In this study, we have developed an in vitro epileptic model in human hippocampal slices resected from patients suffering from intractable mesial temporal lobe epilepsy. Using a planar multielectrode array system, spatio-temporal inter-ictal activity can be consistently recorded in high-potassium (8 mM), low-magnesium (0.25 mM) aCSF with additional 100 µM 4-aminopyridine. The induced inter-ictal activity can be recorded in different regions including dentate, CA1 and Subiculum. We hope the experimental model built in this study will help us understand more about seizure generation, as well as providing insights into prevention and novel therapeutics.