A 1024-Channel CMOS Microelectrode Array With 26,400 Electrodes for Recording and Stimulation of Electrogenic Cells In Vitro

Spatially resolved electrical impedance methods for cell and particle characterization

Electrical impedance is an established technique used for cell and particle characterization. The temporal and spectral resolution of electrical impedance have been used to resolve basic cell characteristics like size and type, as well as to determine cell viability and activity. Such electrical impedance measurements are typically performed across the entire sample volume and can only provide an overall indication concerning the properties and state of that sample. For the study of heterogeneous structures such as cell layers, biological tissue, or polydisperse particle mixtures, an overall measured impedance value can only provide limited information and can lead to data misinterpretation. For the investigation of localized sample properties in complex heterogeneous structures/mixtures, the addition of spatial resolution to impedance measurements is necessary. Several spatially resolved impedance measurement techniques have been developed and applied to cell and particle research, including electrical impedance tomography, scanning electrochemical microscopy, and microelectrode arrays. This review provides an overview of spatially resolved impedance measurement methods and assesses their applicability for cell and particle characterization.

Intracellular Recording of Cardiomyocyte Action Potentials with Nanopatterned Volcano-Shaped Microelectrode Arrays

Micronanotechnology-based multielectrode arrays have led to remarkable progress in the field of transmembrane voltage recording of excitable cells. However, providing long-term optoporation- or electroporation-free intracellular access remains a considerable challenge. In this study, a novel type of nanopatterned volcano-shaped microelectrode (nanovolcano) is described that spontaneously fuses with the cell membrane and permits stable intracellular access. The complex nanostructure was manufactured following a simple and scalable fabrication process based on ion beam etching redeposition. The resulting ring-shaped structure provided passive intracellular access to neonatal rat cardiomyocytes. Intracellular action potentials were successfully recorded in vitro from different devices, and continuous recording for more than 1 h was achieved. By reporting transmembrane action potentials at potentially high spatial resolution without the need to apply physical triggers, the nanovolcanoes show distinct advantages over multielectrode arrays for the assessment of electrophysiological characteristics of cardiomyocyte networks at the transmembrane voltage level over time.

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.

Stimulation and Artifact-Suppression Techniques for In Vitro High-Density Microelectrode Array Systems

We present novel voltage stimulation buffers with controlled output current, along with recording circuits featuring adjustable high-pass cut-off filtering to perform efficient stimulation while actively suppressing stimulation artifacts in high-density microelectrode arrays. Owing to the dense packing and close proximity of the electrodes in such systems, a stimulation through one electrode can cause large electrical artifacts on neighboring electrodes that easily saturate the corresponding recording amplifiers. To suppress such artifacts, the high-pass corner frequencies of all available 2048 recording channels can be raised from several Hz to several kHz by applying a "soft-reset" or pole-shifting technique. With the implemented artifact suppression technique, the saturation time of the recording circuits, connected to electrodes in immediate vicinity to the stimulation site, could be reduced to less than 150 μs. For the stimulation buffer, we developed a circuit, which can operate in two modes: either control of only the stimulation voltage or control of current and voltage during stimulation. The voltage-only controlled mode employs a local common-mode feedback operational transconductance amplifier with a near rail-to-rail input/output range, suitable for driving high-capacitive loads. The current/voltage controlled mode is based on a positive current conveyor generating adjustable output currents, whereas its upper and lower output voltages are limited by two feedback loops. The current/voltage controlled circuit can generate stimulation pulses up to 30 μA with less than ±0.1% linearity error in the low-current mode and up to 300 μA with less than ±0.2% linearity error in the high-current mode.

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.

Compact and Low-Power Neural Spike Compression Using Undercomplete Autoencoders

Implantable microsystems that collect and transmit neural data are becoming very useful entities in the field of neuroscience. Limited by high data rates, on-chip compression is often required to transmit the recorded data without causing power dissipation at levels that would damage sensitive brain tissue. This paper presents a data compression system designed for brain-computer interfaces (BCIs) based on undercomplete autoencoders. To the best of our knowledge, the proposed system is the first to achieve an average spike reconstruction quality of 14-dB signal-to-noise-and-distortion ratio (SNDR) at a 32× compression ratio (CR), 18-dB SNDR at a 16× CR, 22-dB SNDR at an 8× CR, and 35-dB SNDR at a 4× CR of neural spikes. The spike detection and autoencoder-based compression modules are designed and implemented in a standard 45-nm CMOS process. The post-synthesis simulation results report that the compression module consumes between 1.4 and 222.5 [Formula: see text] of power per channel and takes between 0.018 and 0.082mm² of silicon area, depending on the desired CR and number of channels.

Dual-mode Microelectrode Array Featuring 20k Electrodes and High SNR for Extracellular Recording of Neural Networks

In recent electrophysiological studies, CMOS-based high-density microelectrode arrays (HD-MEA) have been widely used for studies of both in-vitro and in-vivo neuronal signals and network behavior. Yet, an open issue in MEA design concerns the tradeoff between signal-to-noise ratio (SNR) and number of readout channels. Here we present a new HD-MEA design in 0.18 μm CMOS technology, consisting of 19,584 electrodes at a pitch of 18.0 μm. By combing two readout structures, namely active-pixel-sensor (APS) and switch-matrix (SM) on a single chip, the dual-mode HD-MEA is capable of recording simultaneously from the entire array and achieving high signal-to-noise-ratio recordings on a subset of electrodes. The APS readout circuits feature a noise level of 10.9 μVrms for the action potential band (300 Hz - 5 kHz), while the noise level for the switch-matrix readout is 3.1 μVrms.

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.

Optimal Electrode Size for Multi-Scale Extracellular-Potential Recording From Neuronal Assemblies

Advances in microfabrication technology have enabled the production of devices containing arrays of thousands of closely spaced recording electrodes, which afford subcellular resolution of electrical signals in neurons and neuronal networks. Rationalizing the electrode size and configuration in such arrays demands consideration of application-specific requirements and inherent features of the electrodes. Tradeoffs among size, spatial density, sensitivity, noise, attenuation, and other factors are inevitable. Although recording extracellular signals from neurons with planar metal electrodes is fairly well established, the effects of the electrode characteristics on the quality and utility of recorded signals, especially for small, densely packed electrodes, have yet to be fully characterized. Here, we present a combined experimental and computational approach to elucidating how electrode size, and size-dependent parameters, such as impedance, baseline noise, and transmission characteristics, influence recorded neuronal signals. Using arrays containing platinum electrodes of different sizes, we experimentally evaluated the electrode performance in the recording of local field potentials (LFPs) and extracellular action potentials (EAPs) from the following cell preparations: acute brain slices, dissociated cell cultures, and organotypic slice cultures. Moreover, we simulated the potential spatial decay of point-current sources to investigate signal averaging using known signal sources. We demonstrated that the noise and signal attenuation depend more on the electrode impedance than on electrode size, per se, especially for electrodes <10 μm in width or diameter to achieve high-spatial-resolution readout. By minimizing electrode impedance of small electrodes (<10 μm) via surface modification, we could maximize the signal-to-noise ratio to electrically visualize the propagation of axonal EAPs and to isolate single-unit spikes. Due to the large amplitude of LFP signals, recording quality was high and nearly independent of electrode size. These findings should be of value in configuring in vitro and in vivo microelectrode arrays for extracellular recordings with high spatial resolution in various applications.

A 4.8-μVrms-Noise CMOS-Microelectrode Array With Density-Scalable Active Readout Pixels via Disaggregated Differential Amplifier Implementation

We demonstrate a 4.8-μV_rms noise microelectrode array (MEA) based on the complementary-metal-oxide-semiconductor active-pixel-sensors readout technique with disaggregated differential amplifier implementation. The circuit elements of the differential amplifier are divided into a readout pixel, a reference pixel, and a column circuit. This disaggregation contributes to the small area of the readout pixel, which is less than 81 μm². We observed neuron signals around 100 μV with 432 electrodes in a fabricated prototype chip. The implementation has technological feasibility of up to 12-μm-pitch electrode density and 6,912 readout channels for high-spatial resolution mapping of neuron network activity.

Single-Cell Electrical Stimulation Using CMOS-Based High-Density Microelectrode Arrays

Non-invasive electrical stimulation can be used to study and control neural activity in the brain or to alleviate somatosensory dysfunctions. One intriguing prospect is to precisely stimulate individual targeted neurons. Here, we investigated single-neuron current and voltage stimulation in vitro using high-density microelectrode arrays featuring 26,400 bidirectional electrodes at a pitch of 17.5 μm and an electrode area of 5 × 9 μm2. We determined optimal waveforms, amplitudes and durations for both stimulation modes. Owing to the high spatial resolution of our arrays and the close proximity of the electrodes to the respective neurons, we were able to stimulate the axon initial segments (AIS) with charges of less than 2 pC. This resulted in minimal artifact production and reliable readout of stimulation efficiency directly at the soma of the stimulated cell. Stimulation signals as low as 70 mV or 100 nA, with pulse durations as short as 18 μs, yielded measurable action potential initiation and propagation. We found that the required stimulation signal amplitudes decreased with cell growth and development and that stimulation efficiency did not improve at higher electric fields generated by simultaneous multi-electrode stimulation.

Accurate signal-source localization in brain slices by means of high-density microelectrode arrays

Extracellular recordings by means of high-density microelectrode arrays (HD-MEAs) have become a powerful tool to resolve subcellular details of single neurons in active networks grown from dissociated cells. To extend the application of this technology to slice preparations, we developed models describing how extracellular signals, produced by neuronal cells in slices, are detected by microelectrode arrays. The models help to analyze and understand the electrical-potential landscape in an in vitro HD-MEA-recording scenario based on point-current sources. We employed two modeling schemes, (i) a simple analytical approach, based on the method of images (MoI), and (ii) an approach, based on finite-element methods (FEM). We compared and validated the models with large-scale, high-spatiotemporal-resolution recordings of slice preparations by means of HD-MEAs. We then developed a model-based localization algorithm and compared the performance of MoI and FEM models. Both models provided accurate localization results and a comparable and negligible systematic error, when the point source was in saline, a condition similar to cell-culture experiments. Moreover, the relative random error in the x-y-z-localization amounted only up to 4.3% for z-distances up to 200 μm from the HD-MEA surface. In tissue, the systematic errors of both, MoI and FEM models were significantly higher, and a pre-calibration was required. Nevertheless, the FEM values proved to be closer to the tissue experimental results, yielding 5.2 μm systematic mean error, compared to 22.0 μm obtained with MoI. These results suggest that the medium volume or "saline height", the brain slice thickness and anisotropy, and the location of the reference electrode, which were included in the FEM model, considerably affect the extracellular signal and localization performance, when the signal source is at larger distance to the array. After pre-calibration, the relative random error of the z-localization in tissue was only 3% for z-distances up to 200 μm. We then applied the model and related detailed understanding of extracellular recordings to achieve an electrically-guided navigation of a stimulating micropipette, solely based on the measured HD-MEA signals, and managed to target spontaneously active neurons in an acute brain slice for electroporation.

Scaling Spike Detection and Sorting for Next-Generation Electrophysiology

Reliable spike detection and sorting, the process of assigning each detected spike to its originating neuron, are essential steps in the analysis of extracellular electrical recordings from neurons. The volume and complexity of the data from recently developed large-scale, high-density microelectrode arrays and probes, which allow recording from thousands of channels simultaneously, substantially complicate this task conceptually and computationally. This chapter provides a summary and discussion of recently developed methods to tackle these challenges and discusses the important aspect of algorithm validation, and assessment of detection and sorting quality.

Long-Term High-Density Extracellular Recordings Enable Studies of Muscle Cell Physiology

Skeletal (voluntary) muscle is the most abundant tissue in the body, thus making it an important biomedical research subject. Studies of neuromuscular transmission, including disorders of ion channels or receptors in autoimmune or genetic neuromuscular disorders, require high-spatial-resolution measurement techniques and an ability to acquire repeated recordings over time in order to track pharmacological interventions. Preclinical techniques for studying diseases of neuromuscular transmission can be enhanced by physiologic ex vivo models of tissue-tissue and cell-cell interactions. Here, we present a method, which allows tracking the development of primary skeletal muscle cells from myoblasts into mature contracting myotubes over more than 2 months. In contrast to most previous studies, the myotubes did not detach from the surface but instead formed functional networks between the myotubes, whose electrical signals were observed over the entire culturing period. Primary cultures of mouse myoblasts differentiated into contracting myotubes on a chip that contained an array of 26,400 platinum electrodes at a density of 3,265 electrodes per mm². Our ability to track extracellular action potentials at subcellular resolution enabled study of skeletal muscle development and kinetics, modes of spiking and spatio-temporal relationships between muscles. The developed system in turn enables creation of a novel electrophysiological platform for establishing ex vivo disease models.

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.

A Low-Power Current-Reuse Analog Front-End for High-Density Neural Recording Implants

Studying brain activity in vivo requires collecting bioelectrical signals from several microelectrodes simultaneously in order to capture neuron interactions. In this work, we present a new current-reuse analog front-end (AFE), which is scalable to very large numbers of recording channels, thanks to its small implementation silicon area and its low-power consumption. This current-reuse AFE, which is including a low-noise amplifier (LNA) and a programmable gain amplifier (PGA), employs a new fully differential current-mirror topology using fewer transistors, and improving several design parameters, such as power consumption and noise, over previous current-reuse amplifier circuit implementations. We show that the proposed current-reuse amplifier can provide a theoretical noise efficiency factor (NEF) as low as 1.01, which is the lowest reported theoretical NEF provided by an LNA topology. A foue-channel current-reuse AFE implemented in a CMOS 0.18-μm technology is presented as a proof-of-concept. T-network capacitive circuits are used to decrease the size of input capacitors and to increase the gain accuracy in the AFE. The measured performance of the whole AFE is presented. The total power consumption per channel, including the LNA and the PGA stage, is 9 μW (4.5 μW for LNA and 4.5 μW for PGA), for an input referred noise of 3.2 μV_rms, achieving a measured NEF of 1.94. The entire AFE presents three selectable gains of 35.04, 43.1, and 49.5 dB, and occupies a die area of 0.072 mm² per channel. The implemented circuit has a measured inter-channel rejection ratio of 54 dB. In vivo recording results obtained with the proposed AFE are reported. It successfully allows collecting low-amplitude extracellular action potential signals from a tungsten wire microelectrode implanted in the hippocampus of a laboratory mouse.

Statistically Reconstructed Multiplexing for Very Dense, High-Channel-Count Acquisition Systems

Multiplexing is an important strategy in multichannel acquisition systems. The per-channel antialiasing filters needed in the traditional multiplexing architecture limit its scalability for applications requiring high channel density, high channel count, and low noise. A particularly challenging example is multielectrode arrays for recording from neural systems. We show that conventional approaches must tradeoff recording density and noise performance, at a scale far from the ideal goal of one-to-one mapping between neurons and sensors. We present a multiplexing architecture without per-channel antialiasing filters. The sparsely sampled data are recovered through a compressed sensing strategy, involving statistical reconstruction and removal of the undersampled thermal noise. In doing so, we replace large analog components with digital signal processing blocks, which are much more amenable to scaled CMOS implementation. The resulting statistically reconstructed multiplexing architecture recovers input signals at significantly improved signal-to-noise ratios when compared to conventional multiplexing with antialiasing filters at the same per-channel area. We implement the new architecture in a 65 536-channel neural recording system and show that it is able to recover signals with performance comparable to conventional high-performance, single-channel systems, despite a more than four-orders-of-magnitude increase in channel density.

1024-Pixel CMOS Multimodality Joint Cellular Sensor/Stimulator Array for Real-Time Holistic Cellular Characterization and Cell-Based Drug Screening

This paper presents a fully integrated CMOS multimodality joint sensor/stimulator array with 1024 pixels for real-time holistic cellular characterization and drug screening. The proposed system consists of four pixel groups and four parallel signal-conditioning blocks. Every pixel group contains 16 × 16 pixels, and each pixel includes one gold-plated electrode, four photodiodes, and in-pixel circuits, within a pixel footprint. Each pixel supports real-time extracellular potential recording, optical detection, charge-balanced biphasic current stimulation, and cellular impedance measurement for the same cellular sample. The proposed system is fabricated in a standard 130-nm CMOS process. Rat cardiomyocytes are successfully cultured on-chip. Measured high-resolution optical opacity images, extracellular potential recordings, biphasic current stimulations, and cellular impedance images demonstrate the unique advantages of the system for holistic cell characterization and drug screening. Furthermore, this paper demonstrates the use of optical detection on the on-chip cultured cardiomyocytes to real-time track their cyclic beating pattern and beating rate.

Surface-modified CMOS IC electrochemical sensor array targeting single chromaffin cells for highly parallel amperometry measurements

Amperometry is a powerful method to record quantal release events from chromaffin cells and is widely used to assess how specific drugs modify quantal size, kinetics of release, and early fusion pore properties. Surface-modified CMOS-based electrochemical sensor arrays allow simultaneous recordings from multiple cells. A reliable, low-cost technique is presented here for efficient targeting of single cells specifically to the electrode sites. An SU-8 microwell structure is patterned on the chip surface to provide insulation for the circuitry as well as cell trapping at the electrode sites. A shifted electrode design is also incorporated to increase the flexibility of the dimension and shape of the microwells. The sensitivity of the electrodes is validated by a dopamine injection experiment. Microwells with dimensions slightly larger than the cells to be trapped ensure excellent single-cell targeting efficiency, increasing the reliability and efficiency for on-chip single-cell amperometry measurements. The surface-modified device was validated with parallel recordings of live chromaffin cells trapped in the microwells. Rapid amperometric spikes with no diffusional broadening were observed, indicating that the trapped and recorded cells were in very close contact with the electrodes. The live cell recording confirms in a single experiment that spike parameters vary significantly from cell to cell but the large number of cells recorded simultaneously provides the statistical significance.

Twenty-four-micrometer-pitch microelectrode array with 6912-channel readout at 12 kHz via highly scalable implementation for high-spatial-resolution mapping of action potentials

A 24-μm-pitch microelectrode array (MEA) with 6912 readout channels at 12 kHz and 23.2-μV_rms random noise is presented. The aim is to reduce noise in a "highly scalable" MEA with a complementary metal-oxide-semiconductor integration circuit (CMOS-MEA), in which a large number of readout channels and a high electrode density can be expected. Despite the small dimension and the simplicity of the in-pixel circuit for the high electrode-density and the relatively large number of readout channels of the prototype CMOS-MEA chip developed in this work, the noise within the chip is successfully reduced to less than half that reported in a previous work, for a device with similar in-pixel circuit simplicity and a large number of readout channels. Further, the action potential was clearly observed on cardiomyocytes using the CMOS-MEA. These results indicate the high-scalability of the CMOS-MEA. The highly scalable CMOS-MEA provides high-spatial-resolution mapping of cell action potentials, and the mapping can aid understanding of complex activities in cells, including neuron network activities.

Unsupervised Spike Sorting for Large-Scale, High-Density Multielectrode Arrays

We present a method for automated spike sorting for recordings with high-density, large-scale multielectrode arrays. Exploiting the dense sampling of single neurons by multiple electrodes, an efficient, low-dimensional representation of detected spikes consisting of estimated spatial spike locations and dominant spike shape features is exploited for fast and reliable clustering into single units. Millions of events can be sorted in minutes, and the method is parallelized and scales better than quadratically with the number of detected spikes. Performance is demonstrated using recordings with a 4,096-channel array and validated using anatomical imaging, optogenetic stimulation, and model-based quality control. A comparison with semi-automated, shape-based spike sorting exposes significant limitations of conventional methods. Our approach demonstrates that it is feasible to reliably isolate the activity of up to thousands of neurons and that dense, multi-channel probes substantially aid reliable spike sorting.

A very large-scale microelectrode array for cellular-resolution electrophysiology

In traditional electrophysiology, spatially inefficient electronics and the need for tissue-to-electrode proximity defy non-invasive interfaces at scales of more than a thousand low noise, simultaneously recording channels. Using compressed sensing concepts and silicon complementary metal-oxide-semiconductors (CMOS), we demonstrate a platform with 65,536 simultaneously recording and stimulating electrodes in which the per-electrode electronics consume an area of 25.5 μm by 25.5 μm. Application of this platform to mouse retinal studies is achieved with a high-performance processing pipeline with a 1 GB/s data rate. The platform records from 65,536 electrodes concurrently with a ~10 µV r.m.s. noise; senses spikes from more than 34,000 electrodes when recording across the entire retina; automatically sorts and classifies greater than 1700 neurons following visual stimulation; and stimulates individual neurons using any number of the 65,536 electrodes while observing spikes over the entire retina. The approaches developed here are applicable to other electrophysiological systems and electrode configurations.

Large electronics limit low-noise, non-invasive electrophysiological measurements to a thousand simultaneously recording channels. Here the authors build an array of 65k simultaneously recording and stimulating electrodes and use it to sort and classify single neurons across the entire mouse retina.

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.

High-Density Mapping of Brain Slices using a Large Multi-Functional High-Density CMOS Microelectrode Array System

We present a CMOS-based high-density microelectrode array (HD-MEA) system that enables high-density mapping of brain slices in-vitro with multiple readout modalities. The 4.48×2.43 mm2 array consists of 59,760 micro-electrodes at 13.5 µm pitch (5487 electrodes/mm2). The overall system features 2048 action-potential, 32 local-field-potential and 32 current recording channels, 32 impedance-measurement and 28 neurotransmitter-detection channels and 16 voltage/current stimulation channels. The system enables real-time and label-free monitoring of position, size, morphology and electrical activity of brain slices.

A Multi-Functional Microelectrode Array Featuring 59760 Electrodes, 2048 Electrophysiology Channels, Stimulation, Impedance Measurement and Neurotransmitter Detection Channels

Biological cells are characterized by highly complex phenomena and processes that are, to a great extent, interdependent. To gain detailed insights, devices designed to study cellular phenomena need to enable tracking and manipulation of multiple cell parameters in parallel; they have to provide high signal quality and high spatiotemporal resolution. To this end, we have developed a CMOS-based microelectrode array system that integrates six measurement and stimulation functions, the largest number to date. Moreover, the system features the largest active electrode array area to date (4.48×2.43 mm2) to accommodate 59,760 electrodes, while its power consumption, noise characteristics, and spatial resolution (13.5 μm electrode pitch) are comparable to the best state-of-the-art devices. The system includes: 2,048 action-potential (AP, bandwidth: 300 Hz to 10 kHz) recording units, 32 local-field-potential (LFP, bandwidth: 1 Hz to 300 Hz) recording units, 32 current recording units, 32 impedance measurement units, and 28 neurotransmitter detection units, in addition to the 16 dual-mode voltage-only or current/voltage-controlled stimulation units. The electrode array architecture is based on a switch matrix, which allows for connecting any measurement/stimulation unit to any electrode in the array and for performing different measurement/stimulation functions in parallel.

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

We present a novel, all-electric approach to record and to precisely control the activity of tens of individual presynaptic neurons. The method allows for parallel mapping of the efficacy of multiple synapses and of the resulting dynamics of postsynaptic neurons in a cortical culture. For the measurements, we combine an extracellular high-density microelectrode array, featuring 11’000 electrodes for extracellular recording and stimulation, with intracellular patch-clamp recording. We are able to identify the contributions of individual presynaptic neurons - including inhibitory and excitatory synaptic inputs - to postsynaptic potentials, which enables us to study dendritic integration. Since the electrical stimuli can be controlled at microsecond resolution, our method enables to evoke action potentials at tens of presynaptic cells in precisely orchestrated sequences of high reliability and minimum jitter. We demonstrate the potential of this method by evoking short- and long-term synaptic plasticity through manipulation of multiple synaptic inputs to a specific neuron.

Direct Interfacing of Neurons to Highly Integrated Microsystems

The use of large high-density transducer arrays enables fundamentally new neuroscientific insights through enabling high-throughput monitoring of action potentials of larger neuronal networks (> 1000 neurons) over extended time to see effects of disturbances or developmental effects, and through facilitating detailed investigations of neuronal signaling characteristics at subcellular level, for example, the study of axonal signal propagation that has been largely inaccessible to established methods. Applications include research in neural diseases and pharmacology.

State-of-the-art MEMS and microsystem tools for brain research

Mapping brain activity has received growing worldwide interest because it is expected to improve disease treatment and allow for the development of important neuromorphic computational methods. MEMS and microsystems are expected to continue to offer new and exciting solutions to meet the need for high-density, high-fidelity neural interfaces. Herein, the state-of-the-art in recording and stimulation tools for brain research is reviewed, and some of the most significant technology trends shaping the field of neurotechnology are discussed.

In vitro cyto-biocompatibility study of thin-film transistors substrates using an organotypic culture method

Thin-Film-Transistors Liquid-Crystal Display has become a standard in the field of displays. However, the structure of these devices presents interest not only in that field, but also for biomedical applications. One of the key components, called here TFT substrate, is a glass substrate with a dense and large array of thousands of transparent micro-electrodes that can be considered as a large scale multi-electrode array(s). Multi-electrode array(s) are widely used for in vitro electrical investigations on neurons and brain, allowing excitation, registration, and recording of their activity. However, the range of application of conventional multi-electrode array(s) is usually limited to some tens of cells in a homogeneous cell culture, because of a small area, small number and a low density of the micro-electrodes. TFT substrates do not have these limitations and the authors are currently studying the possibility to use TFT substrates as new tools for in vitro electrical investigation on tissues and organoids. In this respect, experiments to determine the cyto-biocompatibility of TFT substrates with tissues were conducted and are presented in this study. The investigation was performed using an organotypic culture method with explants of brain and liver tissues of chick embryos. The results in term of morphology, cell migration, cell density and adhesion were compared with the results from Thermanox^®, a conventional plastic for cell culture, and with polydimethylsiloxane, a hydrophobic silicone. The results with TFT substrates showed similar results as for the Thermanox^®, despite the TFT hydrophobicity. TFT substrates have a weak cell adhesion and promote cell migration similarly to Thermanox^®. It could be concluded that the TFT substrates are cyto-biocompatible with the two studied organs.

Electrical Identification and Selective Microstimulation of Neuronal Compartments Based on Features of Extracellular Action Potentials

A detailed, high-spatiotemporal-resolution characterization of neuronal responses to local electrical fields and the capability of precise extracellular microstimulation of selected neurons are pivotal for studying and manipulating neuronal activity and circuits in networks and for developing neural prosthetics. Here, we studied cultured neocortical neurons by using high-density microelectrode arrays and optical imaging, complemented by the patch-clamp technique, and with the aim to correlate morphological and electrical features of neuronal compartments with their responsiveness to extracellular stimulation. We developed strategies to electrically identify any neuron in the network, while subcellular spatial resolution recording of extracellular action potential (AP) traces enabled their assignment to the axon initial segment (AIS), axonal arbor and proximal somatodendritic compartments. Stimulation at the AIS required low voltages and provided immediate, selective and reliable neuronal activation, whereas stimulation at the soma required high voltages and produced delayed and unreliable responses. Subthreshold stimulation at the soma depolarized the somatic membrane potential without eliciting APs.

A short-impulse UWB BPSK transmitter for large-scale neural recording implants

In this paper, a short-impulse ultra-wide band (UWB) transmitter is introduced to enable large-scale neural recordings within miniature brain implants including thousands of channels. The proposed impulse radio UWB transmitter uses a BPSK modulation scheme, the carrier signal of which uses only two delayed impulses to encode the transmitted signal. The proposed UWB transmitter has been implemented into a CMOS 180 nm technology. It occupies 300 μm × 230 μm, and consumes only 6.7 pJ/bit from a 1.8-V supply. Experimental results show that the transmitter has a bandwidth of 2.6 GHz to 5.6 GHz and achieves a maximum data rate of 800 Mbps, which outperforms existing low-power UWB transmitters for similar applications.

Shielded Coaxial Optrode Arrays for Neurophysiology

Recent progress in the study of the brain has been greatly facilitated by the development of new tools capable of minimally-invasive, robust coupling to neuronal assemblies. Two prominent examples are the microelectrode array (MEA), which enables electrical signals from large numbers of neurons to be detected and spatiotemporally correlated, and optogenetics, which enables the electrical activity of cells to be controlled with light. In the former case, high spatial density is desirable but, as electrode arrays evolve toward higher density and thus smaller pitch, electrical crosstalk increases. In the latter, finer control over light input is desirable, to enable improved studies of neuroelectronic pathways emanating from specific cell stimulation. Here, we introduce a coaxial electrode architecture that is uniquely suited to address these issues, as it can simultaneously be utilized as an optical waveguide and a shielded electrode in dense arrays. Using optogenetically-transfected cells on a coaxial MEA, we demonstrate the utility of the architecture by recording cellular currents evoked from optical stimulation. We also show the capability for network recording by radiating an area of seven individually-addressed coaxial electrode regions with cultured cells covering a section of the extent.

22.8 Multi-Functional Microelectrode Array System Featuring 59,760 Electrodes, 2048 Electrophysiology Channels, Impedance and Neurotransmitter Measurement Units

Various CMOS-based micro-electrode arrays (MEAs) have been developed in recent years for extracellular electrophysiological recording/stimulation of electrogenic cells [1-5]. Mostly two approaches have been used: (i) the activepixel approach (APS) [2-4], which features simultaneous readout of all electrodes, however, at the expense of a comparably high noise level, and (ii) the switchmatrix (SM) approach, which yields better noise performance, whereas only a subset of electrodes (e.g.,1024) is simultaneously read out [5]. All systems feature, at most, voltage recording and/or voltage/current stimulation functionalities.

The role of micro-scale current sensing in biomedicine: A unifying view and design guidelines

The electrical activity of cells is regulated by ion fluxes and chemical signaling between them is sustained by redox-reactive molecules. Consequently, current sensing represents a straightforward way to interface electronics with biology and a common detection tool in several applications spanning from patch-clamp and nanopores to micro-scale impedance tracking. Reaching pA resolution at the ms timescale represents a challenge for the readout circuit and here all the criticalities involved in the optimal design of the sensing electrode are reviewed. Advantages vs. drawbacks and risks of the use of silicon as active vs. passive substrate respectively are illustrated by means of experimental examples.

Technology modules from micro- and nano-electronics for the life sciences

The capabilities of modern semiconductor manufacturing offer remarkable possibilities to be applied in life science research as well as for its commercialization. In this review, the technology modules available in micro- and nano-electronics are exemplarily presented for the case of 250 and 130 nm technology nodes. Preparation procedures and the different transistor types as available in complementary metal-oxide-silicon devices (CMOS) and BipolarCMOS (BiCMOS) technologies are introduced as key elements of comprehensive chip architectures. Techniques for circuit design and the elements of completely integrated bioelectronics systems are outlined. The possibility for life scientists to make use of these technology modules for their research and development projects via so-called multi-project wafer services is emphasized. Various examples from diverse fields such as (1) immobilization of biomolecules and cells on semiconductor surfaces, (2) biosensors operating by different principles such as affinity viscosimetry, impedance spectroscopy, and dielectrophoresis, (3) complete systems for human body implants and monitors for bioreactors, and (4) the combination of microelectronics with microfluidics either by chip-in-polymer integration as well as Si-based microfluidics are demonstrated from joint developments with partners from biotechnology and medicine. WIREs Nanomed Nanobiotechnol 2016, 8:355-377. doi: 10.1002/wnan.1367 For further resources related to this article, please visit the WIREs website.

A direct-to-drive neural data acquisition system

Driven by the increasing channel count of neural probes, there is much effort being directed to creating increasingly scalable electrophysiology data acquisition (DAQ) systems. However, all such systems still rely on personal computers for data storage, and thus are limited by the bandwidth and cost of the computers, especially as the scale of recording increases. Here we present a novel architecture in which a digital processor receives data from an analog-to-digital converter, and writes that data directly to hard drives, without the need for a personal computer to serve as an intermediary in the DAQ process. This minimalist architecture may support exceptionally high data throughput, without incurring costs to support unnecessary hardware and overhead associated with personal computers, thus facilitating scaling of electrophysiological recording in the future.

Reconstruction of recurrent synaptic connectivity of thousands of neurons from simulated spiking activity

Dynamics and function of neuronal networks are determined by their synaptic connectivity. Current experimental methods to analyze synaptic network structure on the cellular level, however, cover only small fractions of functional neuronal circuits, typically without a simultaneous record of neuronal spiking activity. Here we present a method for the reconstruction of large recurrent neuronal networks from thousands of parallel spike train recordings. We employ maximum likelihood estimation of a generalized linear model of the spiking activity in continuous time. For this model the point process likelihood is concave, such that a global optimum of the parameters can be obtained by gradient ascent. Previous methods, including those of the same class, did not allow recurrent networks of that order of magnitude to be reconstructed due to prohibitive computational cost and numerical instabilities. We describe a minimal model that is optimized for large networks and an efficient scheme for its parallelized numerical optimization on generic computing clusters. For a simulated balanced random network of 1000 neurons, synaptic connectivity is recovered with a misclassification error rate of less than 1 % under ideal conditions. We show that the error rate remains low in a series of example cases under progressively less ideal conditions. Finally, we successfully reconstruct the connectivity of a hidden synfire chain that is embedded in a random network, which requires clustering of the network connectivity to reveal the synfire groups. Our results demonstrate how synaptic connectivity could potentially be inferred from large-scale parallel spike train recordings.

Nanotechnology and neurophysiology

Neuroscience would be revolutionized by a technique to measure intracellular electrical potentials that would not disrupt cellular physiology and could be massively parallelized. Though such a technology does not yet exist, the technical hurdles for fabricating minimally disruptive, solid-state electrical probes have arguably been overcome in the field of nanotechnology. Nanoscale devices can be patterned with features on the same length scale as biological components, and several groups have demonstrated that nanoscale electrical probes can measure the transmembrane potential of electrogenic cells. Developing these nascent technologies into robust intracellular recording tools will now require a better understanding of device-cell interactions, especially the membrane-inorganic interface. Here we review the state-of-the art in nanobioelectronics, emphasizing the characterization and design of stable interfaces between nanoscale devices and cells.

Revealing neuronal function through microelectrode array recordings

Microelectrode arrays and microprobes have been widely utilized to measure neuronal activity, both in vitro and in vivo. The key advantage is the capability to record and stimulate neurons at multiple sites simultaneously. However, unlike the single-cell or single-channel resolution of intracellular recording, microelectrodes detect signals from all possible sources around every sensor. Here, we review the current understanding of microelectrode signals and the techniques for analyzing them. We introduce the ongoing advancements in microelectrode technology, with focus on achieving higher resolution and quality of recordings by means of monolithic integration with on-chip circuitry. We show how recent advanced microelectrode array measurement methods facilitate the understanding of single neurons as well as network function.

Highly integrated CMOS microsystems to interface with neurons at subcellular resolution

CMOS high-density transducer arrays enable fundamentally new neuroscientific insights through, e.g., facilitating investigation of axonal signaling characteristics, with the "axonal" side of neuronal activity being largely inaccessible to established methods. They also enable high-throughput monitoring of potentially all action potentials in a larger neuronal network (> 1000 neurons) over extended time to see developmental effects or effects of disturbances. Applications include research in neural diseases and pharmacology.