High-density Microelectrode Arrays Research Articles

3D high-density microelectrode array with optical stimulation and drug delivery for investigating neural circuit dynamics

Investigation of neural circuit dynamics is crucial for deciphering the functional connections among regions of the brain and understanding the mechanism of brain dysfunction. Despite the advancements of neural circuit models in vitro, technologies for both precisely monitoring and modulating neural activities within three-dimensional (3D) neural circuit models have yet to be developed. Specifically, no existing 3D microelectrode arrays (MEAs) have integrated capabilities to stimulate surrounding neurons and to monitor the temporal evolution of the formation of a neural network in real time. Herein, we present a 3D high-density multifunctional MEA with optical stimulation and drug delivery for investigating neural circuit dynamics within engineered 3D neural tissues. We demonstrate precise measurements of synaptic latencies in 3D neural networks. We expect our 3D multifunctional MEA to open up opportunities for studies of neural circuits through precise, in vitro investigations of neural circuit dynamics with 3D brain models.

Electrophysiological Phenotype Characterization of Human iPSC-Derived Neuronal Cell Lines by Means of High-Density Microelectrode Arrays.

Recent advances in the field of cellular reprogramming have opened a route to studying the fundamental mechanisms underlying common neurological disorders. High-density microelectrode-arrays (HD-MEAs) provide unprecedented means to study neuronal physiology at different scales, ranging from network through single-neuron to subcellular features. In this work, HD-MEAs are used in vitro to characterize and compare human induced-pluripotent-stem-cell-derived dopaminergic and motor neurons, including isogenic neuronal lines modeling Parkinson's disease and amyotrophic lateral sclerosis. Reproducible electrophysiological network, single-cell and subcellular metrics are used for phenotype characterization and drug testing. Metrics, such as burst shape and axonal velocity, enable the distinction of healthy and diseased neurons. The HD-MEA metrics can also be used to detect the effects of dosing the drug retigabine to human motor neurons. Finally, it is shown that the ability to detect drug effects and the observed culture-to-culture variability critically depend on the number of available recording electrodes.

Electrical functional imaging.

High-density microelectrode arrays with dual-mode capabilities can ‘image’ electrical activity in neuronal cultures or slice preparations.

Electrical Imaging of Light-Induced Signals Across and Within Retinal Layers.

The mammalian retina processes sensory signals through two major pathways: a vertical excitatory pathway, which involves photoreceptors, bipolar cells, and ganglion cells, and a horizontal inhibitory pathway, which involves horizontal cells, and amacrine cells. This concept explains the generation of an excitatory center—inhibitory surround sensory receptive fields—but fails to explain the modulation of the retinal output by stimuli outside the receptive field. Electrical imaging of light-induced signal propagation at high spatial and temporal resolution across and within different retinal layers might reveal mechanisms and circuits involved in the remote modulation of the retinal output. Here we took advantage of a high-density complementary metal oxide semiconductor-based microelectrode array and investigated the light-induced propagation of local field potentials (LFPs) in vertical mouse retina slices. Surprisingly, the LFP propagation within the different retinal layers depends on stimulus duration and stimulus background. Application of the same spatially restricted light stimuli to flat-mounted retina induced ganglion cell activity at remote distances from the stimulus center. This effect disappeared if a global background was provided or if gap junctions were blocked. We hereby present a neurotechnological approach and demonstrated its application, in which electrical imaging evaluates stimulus-dependent signal processing across different neural layers.

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.

Optimization of stimulation parameters for epi-retinal implant based on biosafety consideration.

BackgroundOptimizing stimulation protocol is essential for clinical application of retinal prosthesis. Elongating stimulation pulse width (~25ms /phase) has been proposed as an effective method to improve spatial resolution of epi-retinal implants. However, it is unknown whether longer stimulus pulse width will increase the risk of damaging the retina. In addition, with the advent of next generation retinal prosthesis featuring high-density microelectrode array, it is tempting to optimizing a single set of parameters for all electrodes instead of optimizing parameters of each electrode, but this approach raised biosafety concern. We sought to study the effect of stimulus pulse width on the response of retinal ganglion cells to electrical stimulation, and evaluate if the single parameter set approach was valid based on biosafety measures.MethodsWe stimulated mouse retina using biphasic pulse waveform generated by chosen electrodes (single or a 3x3 assembly) from multiple microelectrode arrays, recorded their action potentials and performed spike sorting. We tested various stimulus intensity with two fixed pulse width: a short one for 1 millisecond per phase, and a long one for 25 milliseconds per phase. All these assays were performed on two mouse models: the wildtype C57BL/6J mice and the photoreceptor degenerated rd10 mice. The action-potential-frequency vs stimulus amplitude profiles were plotted, and three parameters were extracted: the threshold (the lowest stimulus amplitude activating RGC units), safety-limit (stimulus amplitude that attenuated the firing rate to half of the maximum response), and the stimulation amplitude range (the difference between threshold and safety limit parameters).ResultsIn single-electrode stimulation experiment, we found that on average 85% of the recorded units showed attenuated response to extreme stimulation; among those units, an average of 51% stopped responding during stimulation ramping and failed to recover after one-hour post-stimulation, indicating extreme stimulation can damage RGC units. Twenty-five-millisecond pulse stimulation significantly reduced safety-limit and stimulation-amplitude-range parameters of recorded RGC units compared to 1ms pulse stimulation. During stimulus amplitude ramping, the maximum proportion of responsive healthy RGC units was 51% on average in 25ms pulse condition, and 76% on average in 1ms pulse condition, indicating long pulse may inflict more strain on RGCs, and a significant amount of inappropriately stimulated RGCs always exist. The contrast of these proportions could be explained by the tight correlation between the threshold and safety-limit parameter in 25ms pulse condition. These results were corroborated by those from 3x3 array stimulation experiments.ConclusionBase on a biosafety measure (RGCs’ evoked firing rate in response to electrical stimulation), we proposed that longer stimulation pulse width could lead to reduced retinal response and thus highlighted the importance of carefully setting the stimulation amplitude in this case. Our results also suggested that optimizing a single set of parameters for all electrodes without individual tweaking always generated a significant amount of inappropriately stimulated RGCs, especially in the long pulse stimulation condition.

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.

Direct Activation of Primary Motor Cortex during Subthalamic But Not Pallidal Deep Brain Stimulation.

Deep brain stimulation (DBS) of the subthalamic nucleus (STN) and globus pallidus internus (GPi) is an effective treatment for parkinsonian motor signs. Though its therapeutic mechanisms remain unclear, it has been suggested that antidromic activation of the primary motor cortex (M1) plays a significant role in mediating its therapeutic effects. This study tested the hypothesis that antidromic activation of M1 is a prominent feature underlying the therapeutic effect of STN and GPi DBS. Single-unit activity in M1 was recorded using high-density microelectrode arrays in two parkinsonian nonhuman primates each implanted with DBS leads targeting the STN and GPi. Stimulation in each DBS target had similar therapeutic effects, however, antidromic activation of M1 was only observed during STN DBS. Although both animals undergoing STN DBS had similar beneficial effects, the proportion of antidromic-classified cells in each differed, 30 versus 6%. Over 4 h of continuous STN DBS, antidromic activation became less robust, whereas therapeutic benefits were maintained. Although antidromic activation waned over time, synchronization of spontaneous spiking in M1 was significantly reduced throughout the 4 h. Although we cannot discount the potential therapeutic role of antidromic M1 activation at least in the acute phase of STN DBS, the difference in observed antidromic activation between animals, and target sites, raise questions about its hypothesized role as the primary mechanism underlying the therapeutic effect of DBS. These results lend further support that reductions in synchronization at the level of M1 are an important factor in the therapeutic effects of DBS.SIGNIFICANCE STATEMENT Recently there has been great interest and debate regarding the potential role of motor cortical activation in the therapeutic mechanisms of deep brain stimulation (DBS) for Parkinson's disease. In this study we used chronically implanted high density microelectrode arrays in primary motor cortex (M1) to record neuronal population responses in parkinsonian nonhuman primates during subthalamic nucleus (STN) DBS and globus pallidus internus (GPi) DBS. Our results suggest a contribution of antidromic activation of M1 during STN DBS in disrupting synchronization in cortical neuronal populations; however, diminishing antidromic activity over time, and differences in observed antidromic activation between animals and target sites with antidromic activation not observed during GPi DBS, raise questions about its role as the primary mechanism underlying the therapeutic effect of DBS.

ZyON: Enabling Spike Sorting on APSoC-Based Signal Processors for High-Density Microelectrode Arrays

Multi-Electrode Arrays and High-Density Multi-Electrode Arrays of sensors are a key instrument in neuroscience research. Such devices are evolving to provide ever-increasing temporal and spatial resolution, paving the way to unprecedented results when it comes to understanding the behaviour of neuronal networks and interacting with them. However, in some experimental cases, in-place low-latency processing of the sensor data acquired by the arrays is required. This poses the need for high-performance embedded computing platforms capable of processing in real-time the stream of samples produced by the acquisition front-end to extract higher-level information. Previous work has demonstrated that Field-Programmable Gate Array and All-Programmable System-On-Chip devices are suitable target technology for the implementation of real-time processors of High-Density Multi-Electrode Arrays data. However, approaches available in literature can process a limited number of channels or are designed to execute only the first steps of the neural signal processing chain. In this work, we propose an All-Programmable System-On-Chip based implementation capable of sorting neural spikes acquired by the sensors, to associate the shape of each spike to a specific firing neuron. Our system, implemented on a Xilinx Z7020 All-Programmable System-On-Chip is capable of executing on-line spike sorting up to 5500 acquisition channels, 43x more than state-of-the-art alternatives, supporting 18KHz acquisition frequency. We present an experimental study on a commonly used reference dataset, using on-line refinement of the sorting clusters to improve accuracy up to 82%, with only 4% degradation with respect to off-line analysis.

An Integrated Biosensor System With a High-Density Microelectrode Array for Real-Time Electrochemical Imaging.

Electrochemical methods have been shown to be advantageous to life sciences by supporting studies and discoveries in metabolism activities, DNA analysis, and neurotransmitter signaling. Meanwhile, the integration of Microelectrode Array (MEA) and the accessibility of CMOS technology permit high-density electrochemical sensing method. This paper describes an electrochemical imaging system equipped with a custom CMOS microchip. The microchip holds a 3.6 mm × 3.6mm sensing area containing 16,064 Pt MEA, the associated 16,064 integrated read channels, and digital control circuits. The novel three-electrode system geometry with a 27.5μm spatial pitch enables cellular level chemical gradient imaging of bio-samples. The noise level of the on-chip read channel array allows amperometric detection of neurotransmitters such as norepinephrine (NE) with concentrations from 4μM to 512μM with 4.7pA/μM sensitivity (R2 = 0.98). Electrochemical response to dissolved oxygen (DO) concentration was also characterized by deoxygenated deionized water containing 5% to 80% of the ambient oxygen concentrations with 86pA/mg/L sensitivity (R2 = 0.89). The system also demonstrated selectivity to different target analytes using cyclic voltammetry method to simultaneously detect NE and uric acid. Also, a custom indium tin oxide with deposited Au glass electrode was integrated into the microfluidic system to enable pH measurement, ensuring the viability of bio-samples during experiments. Electrochemical images confirm the spatiotemporal performance at four frames per second while maintaining the sensitivity to target analytes. Finally, the overall system is controlled and continuously monitored by a MATLAB-based custom user interface, which is optimized for real-time high spatiotemporal resolution chemical imaging.

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.

Fluctuation Scaling of Neuronal Firing and Bursting in Spontaneously Active Brain Circuits

We employed high-density microelectrode arrays to investigate spontaneous firing patterns of neurons in brain circuits of the primary somatosensory cortex (S1) in mice. We recorded from over150 neurons for10min in each of eight different experiments, identified their location in S1, sorted their action potentials (spikes), and computed their power spectra and inter-spike interval (ISI) statistics. Of all persistently active neurons, 92% fired with a single dominant frequency- regularly firing neurons (RNs)- from1 to8Hz while 8% fired in burst with two dominant frequencies- bursting neurons (BNs)- corresponding to the inter-burst (2-6Hz) and intra-burst intervals (20-160Hz). RNs were predominantly located in layers2/3 and5/6 while BNs localized to layers4 and5. Across neurons, the standard deviation of ISI was a power law of its mean, a property known as fluctuation scaling, with a power law exponent of1 for RNs and1.25 for BNs. The power law implies that firing and bursting patterns are scale invariant: the firing pattern of a given RN or BN resembles that of another RN or BN, respectively, after a time contraction or dilation. An explanation for this scale invariance is discussed in the context of previous computational studies as well as its potential role in information processing.

Classification of Inhibitory and Excitatory Neurons of Dissociated Cultures Based on Action Potential Waveforms on High-density CMOS Microelectrode Arrays

Classification of Inhibitory and Excitatory Neurons of Dissociated Cultures Based on Action Potential Waveforms on High-density CMOS Microelectrode Arrays

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.

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.

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.

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.

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.

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.