Combination of High-density Microelectrode Array and Patch Clamp Recordings to Enable Studies of Multisynaptic Integration

Beyond a Transmission Cable-New Technologies to Reveal the Richness in Axonal Electrophysiology

The axon is a neuronal structure capable of processing, encoding, and transmitting information. This assessment contrasts with a limiting, but deeply rooted, perspective where the axon functions solely as a transmission cable of somatodendritic activity, sending signals in the form of stereotypical action potentials. This perspective arose, at least partially, because of the technical difficulties in probing axons: their extreme length-to-diameter ratio and intricate growth paths preclude the study of their dynamics through traditional techniques. Recent findings are challenging this view and revealing a much larger repertoire of axonal computations. Axons display complex signaling processes and structure-function relationships, which can be modulated via diverse activity-dependent mechanisms. Additionally, axons can exhibit patterns of activity that are dramatically different from those of their corresponding soma. Not surprisingly, many of these recent discoveries have been driven by novel technology developments, which allow for in vitro axon electrophysiology with unprecedented spatiotemporal resolution and signal-to-noise ratio. In this review, we outline the state-of-the-art in vitro toolset for axonal electrophysiology and summarize the recent discoveries in axon function it has enabled. We also review the increasing repertoire of microtechnologies for controlling axon guidance which, in combination with the available cutting-edge electrophysiology and imaging approaches, have the potential for more controlled and high-throughput in vitro studies. We anticipate that a larger adoption of these new technologies by the neuroscience community will drive a new era of experimental opportunities in the study of axon physiology and consequently, neuronal function.

Active Micro-Nano-Collaborative Bioelectronic Device for Advanced Electrophysiological Recording

The development of precise and sensitive electrophysiological recording platforms holds the utmost importance for research in the fields of cardiology and neuroscience. In recent years, active micro/nano-bioelectronic devices have undergone significant advancements, thereby facilitating the study of electrophysiology. The distinctive configuration and exceptional functionality of these active micro-nano-collaborative bioelectronic devices offer the potential for the recording of high-fidelity action potential signals on a large scale. In this paper, we review three-dimensional active nano-transistors and planar active micro-transistors in terms of their applications in electro-excitable cells, focusing on the evaluation of the effects of active micro/nano-bioelectronic devices on electrophysiological signals. Looking forward to the possibilities, challenges, and wide prospects of active micro-nano-devices, we expect to advance their progress to satisfy the demands of theoretical investigations and medical implementations within the domains of cardiology and neuroscience research.

Degree of differentiation impacts neurobiological signature and resistance to hypoxia of SH-SY5Y cells

Objective.SH-SY5Y cells are valuable neuronalin vitromodels for studying patho-mechanisms and treatment targets in brain disorders due to their easy maintenance, rapid expansion, and low costs. However, the use of various degrees of differentiation hampers appreciation of results and may limit the translation of findings to neurons or the brain. Here, we studied the neurobiological signatures of SH-SY5Y cells in terms of morphology, expression of neuronal markers, and functionality at various degrees of differentiation, as well as their resistance to hypoxia. We compared these to neurons derived from human induced pluripotent stem cells (hiPSCs), a well-characterized neuronalin vitromodel.Approach.We cultured SH-SY5Y cells and neurons derived from hiPSCs on glass coverslips or micro-electrode arrays. We studied expression of mature neuronal markers, electrophysiological activity, and sensitivity to hypoxia at various degrees of differentiation (one day up to three weeks) in SH-SY5Y cells. We used hiPSC derived neurons as a reference.Main results.Undifferentiated and shortly differentiated SH-SY5Y cells lacked neuronal characteristics. Expression of neuronal markers and formation of synaptic puncta increased during differentiation. Longer differentiation was associated with lower resistance to hypoxia. At three weeks of differentiation, MAP2 expression and vulnerability to hypoxia were similar to hiPSC-derived neurons, while the number of synaptic puncta and detected events were significantly lower. Our results show that at least three weeks of differentiation are necessary to obtain neurobiological signatures that are comparable to those of hiPSC-derived neurons, as well as similar sensitivities to metabolic stress. Significance.This indicates that extended differentiation protocols should be used to study neuronal characteristics and to model brain disorders with SH-SY5Y cells. We provided insights that may offer the basis for the utilization of SH-SY5Y cells as a more relevant neuronal model in the study of brain disorders.

An integrated perspective for the diagnosis and therapy of neurodevelopmental disorders - From an engineering point of view

Neurodevelopmental disorders (NDDs) are complex conditions with largely unknown pathophysiology. While many NDD symptoms are familiar, the cause of these disorders remains unclear and may involve a combination of genetic, biological, psychosocial, and environmental risk factors. Current diagnosis relies heavily on behaviorally defined criteria, which may be biased by the clinical team's professional and cultural expectations, thus a push for new biological-based biomarkers for NDDs diagnosis is underway. Emerging new research technologies offer an unprecedented view into the electrical, chemical, and physiological activity in the brain and with further development in humans may provide clinically relevant diagnoses. These could also be extended to new treatment options, which can start to address the underlying physiological issues. When combined with current speech, language, occupational therapy, and pharmacological treatment these could greatly improve patient outcomes. The current review will discuss the latest technologies that are being used or may be used for NDDs diagnosis and treatment. The aim is to provide an inspiring and forward-looking view for future research in the field.

A Novel 3D Helical Microelectrode Array for In Vitro Extracellular Action Potential Recording

Recent advances in cell and tissue engineering have enabled long-term three-dimensional (3D) in vitro cultures of human-derived neuronal tissues. Analogous two-dimensional (2D) tissue cultures have been used for decades in combination with substrate integrated microelectrode arrays (MEA) for pharmacological and toxicological assessments. While the phenotypic and cytoarchitectural arguments for 3D culture are clear, 3D MEA technologies are presently inadequate. This is mostly due to the technical challenge of creating vertical electrical conduction paths (or 'traces') using standardized biocompatible materials and fabrication techniques. Here, we have circumvented that challenge by designing and fabricating a novel helical 3D MEA comprised of polyimide, amorphous silicon carbide (a-SiC), gold/titanium, and sputtered iridium oxide films (SIROF). Electrochemical impedance spectroscopy (EIS) and cyclic voltammetry (CV) testing confirmed fully-fabricated MEAs should be capable of recording extracellular action potentials (EAPs) with high signal-to-noise ratios (SNR). We then seeded induced pluripotent stems cell (iPSC) sensory neurons (SNs) in a 3D collagen-based hydrogel integrated with the helical MEAs and recorded EAPs for up to 28 days in vitro from across the MEA volume. Importantly, this highly adaptable design does not intrinsically limit cell/tissue type, channel count, height, or total volume.

Functional imaging of brain organoids using high-density microelectrode arrays

ABSTRACT

Studies have provided evidence that human cerebral organoids (hCOs) recapitulate fundamental milestones of early brain development, but many important questions regarding their functionality and electrophysiological properties persist. High-density microelectrode arrays (HD-MEAs) represent an attractive analysis platform to perform functional studies of neuronal networks at the cellular and network scale. Here, we use HD-MEAs to derive large-scale electrophysiological recordings from sliced hCOs. We record the activity of hCO slices over several weeks and probe observed neuronal dynamics pharmacologically. Moreover, we present results on how the obtained recordings can be spike-sorted and subsequently studied across scales. For example, we show how to track single neurons across several days on the HD-MEA and how to infer axonal action potential velocities. We also infer putative functional connectivity from hCO recordings. The introduced methodology will contribute to a better understanding of developing neuronal networks in brain organoids and provide new means for their functional characterization.

IMPACT STATEMENT

Human cerebral organoids (hCOs) represent an attractive in vitro model system to study key physiological mechanisms underlying early neuronal network formation in tissue with healthy or disease-related genetic backgrounds. Despite remarkable advances in the generation of brain organoids, knowledge on the functionality of their neuronal circuits is still scarce. Here, we used complementary metal-oxide-semiconductor (CMOS)-based high-density microelectrode arrays (HD-MEAs) to perform large-scale recordings from sliced hCOs over several weeks and quantified their activity across scales. Using single-cell and network metrics, we were able to probe aspects of hCO neurophysiology that are more difficult to obtain with other techniques, such as patch clamping (lower yield) and calcium imaging (lower temporal resolution). These metrics included, for example, extracellular action potential (AP) waveform features and axonal AP velocity at the cellular level, as well as functional connectivity at the network level. Analysis was enabled by the large sensing area and the high spatiotemporal resolution provided by HD-MEAs, which allowed recordings from hundreds of neurons and spike sorting of their activity. Our results demonstrate that HD-MEAs provide a multi-purpose platform for the functional characterization of hCOs, which will be key in improving our understanding of this model system and assessing its relevance for translational research.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1557/s43577-022-00282-w.

High-Aspect-Ratio Nanoelectrodes Enable Long-Term Recordings of Neuronal Signals with Subthreshold Resolution

The further development of neurochips requires high-density and high-resolution recordings that also allow neuronal signals to be observed over a long period of time. Expanding fields of network neuroscience and neuromorphic engineering demand the multiparallel and direct estimations of synaptic weights, and the key objective is to construct a device that also records subthreshold events. Recently, 3D nanostructures with a high aspect ratio have become a particularly suitable interface between neurons and electronic devices, since the excellent mechanical coupling to the neuronal cell membrane allows very high signal-to-noise ratio recordings. In the light of an increasing demand for a stable, noninvasive and long-term recording at subthreshold resolution, a combination of vertical nanostraws with nanocavities is presented. These structures provide a spontaneous tight coupling with rat cortical neurons, resulting in high amplitude sensitivity and postsynaptic resolution capability, as directly confirmed by combined patch-clamp and microelectrode array measurements.

Assessing the Feasibility of Developing in vivo Neuroprobes for Parallel Intracellular Recording and Stimulation: A Perspective

Developing novel neuroprobes that enable parallel multisite, long-term intracellular recording and stimulation of neurons in freely behaving animals is a neuroscientist's dream. When fulfilled, it is expected to significantly enhance brain research at fundamental mechanistic levels including that of subthreshold signaling and computations. Here we assess the feasibility of merging the advantages of in vitro vertical nanopillar technologies that support intracellular recordings with contemporary concepts of in vivo extracellular field potential recordings to generate the dream neuroprobes that read the entire electrophysiological signaling repertoire.

Investigation of displacement of intracranial electrode induced by focused ultrasound stimulation

Transcranial focused ultrasound (tFUS) is an emerging neuromodulation technique to modulate brain activity non-invasively with high spatial specificity and focality. Given the influence of tFUS on brain activity, combining tFUS with multi-channel intracranial electrophysiological recordings enables monitoring of the activity of large populations of neurons with high temporal resolution. However, the physical interactions between tFUS and the electrode may affect a reliable assessment of neuronal activity, which remains poorly understood. In this paper, high-frequency ultrasound (HFUS) system was developed and integrated into tFUS neuromodulation system. The performance of the HFUS-based displacement tracking and analysis was evaluated by the theoretical analysis in the literature. The effects of various pressure levels on the displacements of the silicon-based microelectrode array in ex vivo brain tissue were investigated. The developed approach was capable of tracking and measuring the motion of a solid sphere in a tissue-mimicking phantom and measured displacements were comparable to theoretical predictions. The significant changes in the averaged peak displacements of the microelectrode array in ex vivo brain were observed with a pulse duration of 200 μs and a peak-to-peak pressure from 131 kPa at a center frequency of 500 kHz compared with the values from the negative control group. The present results demonstrate the relationship between several pressure levels and displacements of the microelectrode array in ex vivo brain through the developed approach. This approach can be used to determine a vibration-free threshold of ultrasound parameters in multi-channel intracranial recordings for a reliable assessment of electrophysiological activities of living neurons.

Extracellular detection of neuronal coupling

We developed a method to non-invasively detect synaptic relationships among neurons from in vitro networks. Our method uses microelectrode arrays on which neurons are cultured and from which propagation of extracellular action potentials (eAPs) in single axons are recorded at multiple electrodes. Detecting eAP propagation bypasses ambiguity introduced by spike sorting. Our methods identify short latency spiking relationships between neurons with properties expected of synaptically coupled neurons, namely they were recapitulated by direct stimulation and were sensitive to changing the number of active synaptic sites. Our methods enabled us to assemble a functional subset of neuronal connectivity in our cultures.

Nanotechnology: new opportunities for the development of patch-clamps

The patch-clamp technique is one of the best approaches to investigate neural excitability. Impressive improvements towards the automation of the patch-clamp technique have been made, but obvious limitations and hurdles still exist, such as parallelization, volume displacement in vivo, and long-term recording. Nanotechnologies have provided opportunities to overcome these hurdles by applying electrical devices on the nanoscale. Electrodes based on nanowires, nanotubes, and nanoscale field-effect transistors (FETs) are confirmed to be robust and less invasive tools for intracellular electrophysiological recording. Research on the interface between the nanoelectrode and cell membrane aims to reduce the seal conductance and further improve the recording quality. Many novel recording approaches advance the parallelization, and precision with reduced invasiveness, thus improving the overall intracellular recording system. The combination of nanotechnology and the present intracellular recording framework is a revolutionary and promising orientation, potentially becoming the next generation electrophysiological recording technique and replacing the conventional patch-clamp technique. Here, this paper reviews the recent advances in intracellular electrophysiological recording techniques using nanotechnology, focusing on the design of noninvasive and greatly parallelized recording systems based on nanoelectronics.

Influence of Neuronal Morphology on the Shape of Extracellular Recordings With Microelectrode Arrays: A Finite Element Analysis

OBJECTIVE

Measuring neuronal cell activity using microelectrode arrays reveals a great variety of derived signal shapes within extracellular recordings. However, possible mechanisms responsible for this variety have not yet been entirely determined, which might hamper any subsequent analysis of the recorded neuronal data.

METHODS

To investigate this issue, we propose a computational model based on the finite element method describing the electrical coupling between an electrically active neuron and an extracellular recording electrode in detail. This allows for a systematic study of possible parameters that may play an essential role in defining or altering the shape of the measured electrode potential.

RESULTS

Our results indicate that neuronal geometry, neurite structure, as well as the actual pathways of input potentials that evoke action potential generation, have a significant impact on the shape of the resulting extracellular electrode recording and explain most of the known variations of signal shapes.

CONCLUSION

The presented models offer a comprehensive insight into the effect of geometrical and morphological factors on the resulting electrode signal.

SIGNIFICANCE

Computational modeling complemented with experimental measurements shows much promise to yield meaningful insights into the electrical activity of a neuronal network.

Improving reliability and reducing costs of cardiotoxicity assessments using laser-induced cell poration on microelectrode arrays

Drug-induced cardiotoxicity is a major barrier to drug development and a main cause of withdrawal of marketed drugs. Drugs can strongly alter the spontaneous functioning of the heart by interacting with the cardiac membrane ion channels. If these effects only surface during in vivo preclinical tests, clinical trials or worse after commercialization, the societal and economic burden will be significant and seriously hinder the efficient drug development process. Hence, cardiac safety pharmacology requires in vitro electrophysiological screening assays of all drug candidates to predict cardiotoxic effects before clinical trials. In the past 10 years, microelectrode array (MEA) technology began to be considered a valuable approach in pharmaceutical applications. However, an effective tool for high-throughput intracellular measurements, compatible with pharmaceutical standards, is not yet available. Here, we propose laser-induced optoacoustic poration combined with CMOS-MEA technology as a reliable and effective platform to detect cardiotoxicity. This approach enables the acquisition of high-quality action potential recordings from large numbers of cardiomyocytes within the same culture well, providing reliable data using single-well MEA devices and single cardiac syncytia per each drug. Thus, this technology could be applied in drug safety screening platforms reducing times and costs of cardiotoxicity assessments, while simultaneously improving the data reliability.

Building Biomimetic Potency Tests for Islet Transplantation

Diabetes is a disease of insulin insufficiency, requiring many to rely on exogenous insulin with constant monitoring to avoid a fatal outcome. Islet transplantation is a recent therapy that can provide insulin independence, but the procedure is still limited by both the availability of human islets and reliable tests to assess their function. While stem cell technologies are poised to fill the shortage of transplantable cells, better methods are still needed for predicting transplantation outcome. To ensure islet quality, we propose that the next generation of islet potency tests should be biomimetic systems that match glucose stimulation dynamics and cell microenvironmental preferences and rapidly assess conditional and continuous insulin secretion with minimal manual handing. Here, we review the current approaches for islet potency testing and outline technologies and methods that can be used to arrive at a more predictive potency test that tracks islet secretory capacity in a relevant context. With the development of potency tests that can report on islet secretion dynamics in a context relevant to their intended function, islet transplantation can expand into a more widely accessible and reliable treatment option for individuals with diabetes.

Toward Closed-Loop Electrical Stimulation of Neuronal Systems: A Review

Biological neuronal cells communicate using neurochemistry and electrical signals. The same phenomena also allow us to probe and manipulate neuronal systems and communicate with them. Neuronal system malfunctions cause a multitude of symptoms and functional deficiencies that can be assessed and sometimes alleviated by electrical stimulation. Our working hypothesis is that real-time closed-loop full-duplex measurement and stimulation paradigms can provide more in-depth insight into neuronal networks and enhance our capability to control diseases of the nervous system. In this study, we review extracellular electrical stimulation methods used in in vivo, in vitro, and in silico neuroscience research and in the clinic (excluding methods mainly aimed at neuronal growth and other similar effects) and highlight the potential of closed-loop measurement and stimulation systems. A multitude of electrical stimulation and measurement-based methods are widely used in research and the clinic. Closed-loop methods have been proposed, and some are used in the clinic. However, closed-loop systems utilizing more complex measurement analysis and adaptive stimulation systems, such as artificial intelligence systems connected to biological neuronal systems, do not yet exist. Our review promotes the research and development of intelligent paradigms aimed at meaningful communications between neuronal and information and communications technology systems, "dialogical paradigms," which have the potential to take neuroscience and clinical methods to a new level.

MAPSYNE: Miniaturized micropipette system combined with high-density microelectrode arrays for automated manipulation of neuronal networks in-vitro

We present MAPSYNE, a miniaturized and automated system combining a high-density microelectrode array (HD-MEA) and a movable micropipette for studying, monitoring, and perturbing neurons in vitro. The system involves an all-electrical approach to automatically move a glass micropipette towards a target location on the HD-MEA surface, without the need for a microscope. Two methods of performing blind navigation are employed, (i) stop-measure-go approach wherein the pipette moves for a predefined distance before measuring its location then the process is repeated until the pipette reaches its destination, and (ii) predictive approach wherein the pipette is continuously tracked and moved. This automated system can be applied for unsupervised single-cell manipulation of neurons in a network, such as electroporation and local delivery of compounds.

Versatile live-cell activity analysis platform for characterization of neuronal dynamics at single-cell and network level

Chronic imaging of neuronal networks in vitro has provided fundamental insights into mechanisms underlying neuronal function. Current labeling and optical imaging methods, however, cannot be used for continuous and long-term recordings of the dynamics and evolution of neuronal networks, as fluorescent indicators can cause phototoxicity. Here, we introduce a versatile platform for label-free, comprehensive and detailed electrophysiological live-cell imaging of various neurogenic cells and tissues over extended time scales. We report on a dual-mode high-density microelectrode array, which can simultaneously record in (i) full-frame mode with 19,584 recording sites and (ii) high-signal-to-noise mode with 246 channels. We set out to demonstrate the capabilities of this platform with recordings from primary and iPSC-derived neuronal cultures and tissue preparations over several weeks, providing detailed morpho-electrical phenotypic parameters at subcellular, cellular and network level. Moreover, we develop reliable analysis tools, which drastically increase the throughput to infer axonal morphology and conduction speed.

Current methods of neuronal network imaging cannot be used for continuous, long-term functional recordings. Here, the authors present a dual-mode high-density microelectrode array, which can simultaneously record in full-frame and high-signal-to-noise modes for label-free electrophysiological measurements.

Compatibility Evaluation of Clustering Algorithms for Contemporary Extracellular Neural Spike Sorting

Deciphering useful information from electrophysiological data recorded from the brain, in-vivo or in-vitro, is dependent on the capability to analyse spike patterns efficiently and accurately. The spike analysis mechanisms are heavily reliant on the clustering algorithms that enable separation of spike trends based on their spatio-temporal behaviors. Literature review report several clustering algorithms over decades focused on different applications. Although spike analysis algorithms employ only a small subset of clustering algorithms, however, not much work has been reported on the compliance and suitability of such clustering algorithms for spike analysis. In our study, we have attempted to comment on the suitability of available clustering algorithms and performance capacity when exposed to spike analysis. In this regard, the study reports a compatibility evaluation on algorithms previously employed in spike sorting as well as the algorithms yet to be investigated for application in sorting neural spikes. The performance of the algorithms is compared in terms of their accuracy, confusion matrix and accepted validation indices. Three data sets comprising of easy, difficult, and real spike similarity with known ground-truth are chosen for assessment, ensuring a uniform testbed. The procedure also employs two feature-sets, principal component analysis and wavelets. The report also presents a statistical score scheme to evaluate the performance individually and overall. The open nature of the data sets, the clustering algorithms and the evaluation criteria make the proposed evaluation framework widely accessible to the research community. We believe that the study presents a reference guide for emerging neuroscientists to select the most suitable algorithms for their spike analysis requirements.

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.

High-Aspect-Ratio Nanostructured Surfaces as Biological Metamaterials

Materials patterned with high-aspect-ratio nanostructures have features on similar length scales to cellular components. These surfaces are an extreme topography on the cellular level and have become useful tools for perturbing and sensing the cellular environment. Motivation comes from the ability of high-aspect-ratio nanostructures to deliver cargoes into cells and tissues, access the intracellular environment, and control cell behavior. These structures directly perturb cells' ability to sense and respond to external forces, influencing cell fate, and enabling new mechanistic studies. Through careful design of their nanoscale structure, these systems act as biological metamaterials, eliciting unusual biological responses. While predominantly used to interface eukaryotic cells, there is growing interest in nonanimal and prokaryotic cell interfacing. Both experimental and theoretical studies have attempted to develop a mechanistic understanding for the observed behaviors, predominantly focusing on the cell-nanostructure interface. This review considers how high-aspect-ratio nanostructured surfaces are used to both stimulate and sense biological systems.

High-throughput microcircuit analysis of individual human brains through next-generation multineuron patch-clamp

Comparing neuronal microcircuits across different brain regions, species and individuals can reveal common and divergent principles of network computation. Simultaneous patch-clamp recordings from multiple neurons offer the highest temporal and subthreshold resolution to analyse local synaptic connectivity. However, its establishment is technically complex and the experimental performance is limited by high failure rates, long experimental times and small sample sizes. We introduce an in vitro multipatch setup with an automated pipette pressure and cleaning system facilitating recordings of up to 10 neurons simultaneously and sequential patching of additional neurons. We present hardware and software solutions that increase the usability, speed and data throughput of multipatch experiments which allowed probing of 150 synaptic connections between 17 neurons in one human cortical slice and screening of over 600 connections in tissue from a single patient. This method will facilitate the systematic analysis of microcircuits and allow unprecedented assessment of inter-individual variability.

A nanoelectrode array for obtaining intracellular recordings from thousands of connected neurons

Current electrophysiological or optical techniques cannot reliably perform simultaneous intracellular recordings from more than a few tens of neurons. Here we report a nanoelectrode array that can simultaneously obtain intracellular recordings from thousands of connected mammalian neurons in vitro. The array consists of 4,096 platinum-black electrodes with nanoscale roughness fabricated on top of a silicon chip that monolithically integrates 4,096 microscale amplifiers, configurable into pseudocurrent-clamp mode (for concurrent current injection and voltage recording) or into pseudovoltage-clamp mode (for concurrent voltage application and current recording). We used the array in pseudovoltage-clamp mode to measure the effects of drugs on ion-channel currents. In pseudocurrent-clamp mode, the array intracellularly recorded action potentials and postsynaptic potentials from thousands of neurons. In addition, we mapped over 300 excitatory and inhibitory synaptic connections from more than 1,700 neurons that were intracellularly recorded for 19 min. This high-throughput intracellular-recording technology could benefit functional connectome mapping, electrophysiological screening and other functional interrogations of neuronal networks.

Large-Scale Mapping of Axonal Arbors Using High-Density Microelectrode Arrays

Understanding the role of axons in neuronal information processing is a fundamental task in neuroscience. Over the last years, sophisticated patch-clamp investigations have provided unexpected and exciting data on axonal phenomena and functioning, but there is still a need for methods to investigate full axonal arbors at sufficient throughput. Here, we present a new method for the simultaneous mapping of the axonal arbors of a large number of individual neurons, which relies on their extracellular signals that have been recorded with high-density microelectrode arrays (HD-MEAs). The segmentation of axons was performed based on the local correlation of extracellular signals. Comparison of the results with both, ground truth and receiver operator characteristics, shows that the new segmentation method outperforms previously used methods. Using a standard HD-MEA, we mapped the axonal arbors of 68 neurons in <6 h. The fully automated method can be extended to new generations of HD-MEAs with larger data output and is estimated to provide data of axonal arbors of thousands of neurons within recording sessions of a few hours.

Large-Scale, High-Resolution Microelectrode Arrays for Interrogation of Neurons and Networks

High-density microelectrode arrays (HD-MEAs) are increasingly being used for the observation and manipulation of neurons and networks in vitro. Large-scale electrode arrays allow for long-term extracellular recording of the electrical activity from thousands of neurons simultaneously. Beyond population activity, it has also become possible to extract information of single neurons at subcellular level (e.g., the propagation of action potentials along axons). In effect, HD-MEAs have become an electrical imaging platform for label-free extraction of the structure and activation of cells in cultures and tissues. The quality of HD-MEA data depends on the resolution of the electrode array and the signal-to-noise ratio. In this chapter, we begin with an introduction to HD-MEA signals. We provide an overview of the developments on complementary metal-oxide-semiconductor or CMOS-based HD-MEA technology. We also discuss the factors affecting the performance of HD-MEAs and the trending application requirements that drive the efforts for future devices. We conclude with an outlook on the potential of HD-MEAs for advancing basic neuroscience and drug discovery.

Technologies to Study Action Potential Propagation With a Focus on HD-MEAs

Axons convey information in neuronal circuits via reliable conduction of action potentials (APs) from the axon initial segment (AIS) to the presynaptic terminals. Recent experimental findings increasingly evidence that the axonal function is not limited to the simple transmission of APs. Advances in subcellular-resolution recording techniques have shown that axons display activity-dependent modulation in spike shape and conduction velocity, which influence synaptic strength and latency. We briefly review here, how recent methodological developments facilitate the understanding of the axon physiology. We included the three most common methods, i.e., genetically encoded voltage imaging (GEVI), subcellular patch-clamp and high-density microelectrode arrays (HD-MEAs). We then describe the potential of using HD-MEAs in studying axonal physiology in more detail. Due to their robustness, amenability to high-throughput and high spatiotemporal resolution, HD-MEAs can provide a direct functional electrical readout of single cells and cellular ensembles at subcellular resolution. HD-MEAs can, therefore, be employed in investigating axonal pathologies, the effects of large-scale genomic interventions (e.g., with RNAi or CRISPR) or in compound screenings. A combination of extracellular microelectrode arrays (MEAs), intracellular microelectrodes and optical imaging may potentially reveal yet unexplored repertoires of axonal functions.

The Axon Initial Segment is the Dominant Contributor to the Neuron's Extracellular Electrical Potential Landscape

Extracellular voltage fields, produced by a neuron's action potentials, provide a widely used means for studying neuronal and neuronal-network function. The neuron's soma and dendrites are thought to drive the extracellular action potential (EAP) landscape, while the axon's contribution is usually considered less important. However, by recording voltages of single neurons in dissociated rat cortical cultures and Purkinje cells in acute mouse cerebellar slices through hundreds of densely packed electrodes, it is found, instead, that the axon initial segment dominates the measured EAP landscape, and, surprisingly, the soma only contributes to a minor extent. As expected, the recorded dominant signal has negative polarity (charge entering the cell) and initiates at the distal end. Interestingly, signals with positive polarity (charge exiting the cell) occur near some but not all dendritic branches and occur after a delay. Such basic knowledge about which neuronal compartments contribute to the extracellular voltage landscape is important for interpreting results from all electrical readout schemes. Finally, initiation of the electrical activity at the distal end of the axon initial segment (AIS) and subsequent spreading into the axon proper and backward through the proximal AIS toward the soma are confirmed. The corresponding extracellular waveforms across different neuronal compartments could be tracked.

A procedure to increase the power of Granger-causal analysis through temporal smoothing

BACKGROUND

How the human brain coordinates network activity to support cognition and behavior remains poorly understood. New high-resolution recording modalities facilitate a more detailed understanding of the human brain network. Several approaches have been proposed to infer functional networks, indicating the transient coordination of activity between brain regions, from neural time series. One category of approach is based on statistical modeling of time series recorded from multiple sensors (e.g., multivariate Granger causality). However, fitting such models remains computationally challenging as the history structure may be long in neural activity, requiring many model parameters to fully capture the dynamics.

NEW METHOD

We develop a method based on Granger causality that makes the assumption that the history dependence varies smoothly. We fit multivariate autoregressive models such that the coefficients of the lagged history terms are smooth functions. We do so by modelling the history terms with a lower dimensional spline basis, which requires many fewer parameters than the standard approach and increases the statistical power of the model.

RESULTS

We show that this procedure allows accurate estimation of brain dynamics and functional networks in simulations and examples of brain voltage activity recorded from a patient with pharmacoresistant epilepsy.

COMPARISON WITH EXISTING METHOD

The proposed method has more statistical power than the Granger method for networks of signals that exhibit extended and smooth history dependencies.

CONCLUSIONS

The proposed tool permits conditional inference of functional networks from many brain regions with extended history dependence, furthering the applicability of Granger causality to brain network science.

Automated in vivo patch-clamp evaluation of extracellular multielectrode array spike recording capability

Much innovation is currently aimed at improving the number, density, and geometry of electrodes on extracellular multielectrode arrays for in vivo recording of neural activity in the mammalian brain. To choose a multielectrode array configuration for a given neuroscience purpose, or to reveal design principles of future multielectrode arrays, it would be useful to have a systematic way of evaluating the spike recording capability of such arrays. We describe an automated system that performs robotic patch-clamp recording of a neuron being simultaneously recorded via an extracellular multielectrode array. By recording a patch-clamp data set from a neuron while acquiring extracellular recordings from the same neuron, we can evaluate how well the extracellular multielectrode array captures the spiking information from that neuron. To demonstrate the utility of our system, we show that it can provide data from the mammalian cortex to evaluate how the spike sorting performance of a close-packed extracellular multielectrode array is affected by bursting, which alters the shape and amplitude of spikes in a train. We also introduce an algorithmic framework to help evaluate how the number of electrodes in a multielectrode array affects spike sorting, examining how adding more electrodes yields data that can be spike sorted more easily. Our automated methodology may thus help with the evaluation of new electrode designs and configurations, providing empirical guidance on the kinds of electrodes that will be optimal for different brain regions, cell types, and species, for improving the accuracy of spike sorting. NEW & NOTEWORTHY We present an automated strategy for evaluating the spike recording performance of an extracellular multielectrode array, by enabling simultaneous recording of a neuron with both such an array and with patch clamp. We use our robot and accompanying algorithms to evaluate the performance of multielectrode arrays on supporting spike sorting.

Multisite Attenuated Intracellular Recordings by Extracellular Multielectrode Arrays, a Perspective

Multielectrode arrays (MEA) are used extensively for basic and applied electrophysiological research of neuronal- and cardiomyocyte-networks. Whereas immense progress has been made in realizing sophisticated MEA platforms of thousands of addressable, high-density, small diameter, low impedance sensors, the quality of the interfaces formed between excitable cells and classical planar sensor has not improved. As a consequence in vitro and in vivo MEA are “blind” to the rich and important “landscape” of sub-threshold synaptic potentials generated by individual neurons. Disregarding this essential fraction of network signaling repertoire has become the standard and almost the “scientific ideology” of MEA users. To overcome the inherent limitations of substrate integrated planar MEA platforms that only record extracellular field potentials, a number of laboratories have developed in vitro MEA for intracellular recordings. Most of these novel devices use vertical nano-rods or nano-wires that penetrate the plasma membrane of cultured cells and record the electrophysiological signaling in a manner similar to sharp intracellular microelectrodes. In parallel, our laboratory began to develop a bioinspired approach in-which cell biological energy resources are harnessed to self-force a cell into intimate contact with extracellular gold mushroom-shaped microelectrodes to record attenuated synaptic- and action-potentials with characteristic features of intracellular recordings. Here we describe some of the experiments that helped evolve the approach and elaborate on the biophysical principles that make it possible to record intracellular potentials by an array of extracellular electrode. We illustrate the qualities and limitations of the method and discuss prospects for further improvement of this technology.

A bio-image sensor for simultaneous detection of multi-neurotransmitters

We report here a new bio-image sensor for simultaneous detection of spatial and temporal distribution of multi-neurotransmitters. It consists of multiple enzyme-immobilized membranes on a 128 × 128 pixel array with read-out circuit. Apyrase and acetylcholinesterase (AChE), as selective elements, are used to recognize adenosine 5'-triphosphate (ATP) and acetylcholine (ACh), respectively. To enhance the spatial resolution, hydrogen ion (H⁺) diffusion barrier layers are deposited on top of the bio-image sensor and demonstrated their prevention capability. The results are used to design the space among enzyme-immobilized pixels and the null H⁺ sensor to minimize the undesired signal overlap by H⁺ diffusion. Using this bio-image sensor, we can obtain H⁺ diffusion-independent imaging of concentration gradients of ATP and ACh in real-time. The sensing characteristics, such as sensitivity and detection of limit, are determined experimentally. With the proposed bio-image sensor the possibility exists for customizable monitoring of the activities of various neurochemicals by using different kinds of proton-consuming or generating enzymes.

Revealing the distribution of transmembrane currents along the dendritic tree of a neuron from extracellular recordings

Revealing the current source distribution along the neuronal membrane is a key step on the way to understanding neural computations; however, the experimental and theoretical tools to achieve sufficient spatiotemporal resolution for the estimation remain to be established. Here, we address this problem using extracellularly recorded potentials with arbitrarily distributed electrodes for a neuron of known morphology. We use simulations of models with varying complexity to validate the proposed method and to give recommendations for experimental applications. The method is applied to in vitro data from rat hippocampus.