Microelectrode Arrays Research Articles

Hyperexcitability and translational phenotypes in a preclinical mouse model of SYNGAP1-related intellectual disability

Disruption of SYNGAP1 directly causes a genetically identifiable neurodevelopmental disorder (NDD) called SYNGAP1-related intellectual disability (SRID). Without functional SynGAP1 protein, individuals are developmentally delayed and have prominent features of intellectual disability (ID), motor impairments, and epilepsy. Over the past two decades, there have been numerous discoveries indicating the critical role of Syngap1. Several rodent models with a loss of Syngap1 have been engineered, identifying precise roles in neuronal structure and function, as well as key biochemical pathways key for synapse integrity. Homozygous loss of SYNGAP1/Syngap1 is lethal. Heterozygous mutations of Syngap1 result in a broad range of behavioral phenotypes. Our in vivo functional data, using the original mouse model from the Huganir laboratory, corroborated behaviors including robust hyperactivity and deficits in learning and memory in young adults. Furthermore, we described impairments in the domain of sleep, characterized using neurophysiological data that was collected with wireless, telemetric electroencephalography (EEG). Syngap1+/− mice exhibited elevated spiking events and spike trains, in addition to elevated power, most notably in the delta power frequency. For the first time, we illustrated that primary neurons from Syngap1+/− mice displayed: 1) increased network firing activity, 2) greater bursts, 3) and shorter inter-burst intervals between peaks, by utilizing high density microelectrode arrays (HD-MEA). Our work bridges in vitro electrophysiological neuronal activity and function with in vivo neurophysiological brain activity and function. These data elucidate quantitative, translational biomarkers in vivo and in vitro that can be utilized for the development and efficacy assessment of targeted treatments for SRID.

In silico modeling of reservoir-based predictive coding in biological neuronal networks on microelectrode arrays

Reservoir computing and predictive coding together yield a computational model for exploring how neuronal dynamics in the mammalian cortex underpin temporal signal processing. Here, we construct an in-silico model of biological neuronal networks grown on microelectrode arrays and explore their computing capabilities through a sine wave prediction task in a reservoir-based predictive coding framework. Our results show that the time interval between stimulation pulses is a critical determinant of task performance. Additionally, under a fixed feedback latency, pulse amplitude modulation is a favorable encoding scheme for input signals. These findings provide practical guidelines for future implementation of the model in biological experiments.

Development of an evaluation method for addictive compounds based on electrical activity of human iPS cell-derived dopaminergic neurons using microelectrode array.

Addiction is known to occur through the consumption of substances such as pharmaceuticals, illicit drugs, food, alcohol and tobacco. These addictions can be viewed as drug addiction, resulting from the ingestion of chemical substances contained in them. Multiple neural networks, including the reward system, anti-reward/stress system and central immune system in the brain, are believed to be involved in the onset of drug addiction. Although various compound evaluations using microelectrode array (MEA) as an in vitro testing methods to evaluate neural activities have been conducted, methods for assessing addiction have not been established. In this study, we aimed to develop an in vitro method for assessing the addiction of compounds, as an alternative to animal experiments, using human iPS cell-derived dopaminergic neurons with MEA measurements. MEA data before and after chronic exposure revealed specific changes in addictive compounds compared to non-addictive compounds, demonstrating the ability to estimate addiction of compound. Additionally, conducting gene expression analysis on cultured samples after the tests revealed changes in the expression levels of various receptors (nicotine, dopamine and GABA) due to chronic administration of addictive compounds, suggesting the potential interpretation of these expression changes as addiction-like responses in MEA measurements. The addiction assessment method using MEA measurements in human iPS cell-derived dopaminergic neurons conducted in this study proves effective in evaluating addiction of compounds on human neural networks.

Astrocytes induce desynchronization and reduce predictability in neuron-astrocyte networks cultured on microelectrode arrays.

In this article, we aim to study how astrocytes control electrophysiological activity during neuronal network formation. We used a combination of spike/burst analysis, classification of spike waveforms based on various signal properties and tools from information theory to demonstrate how astrocytes modulate the electrical activity of neurons using microelectrode array (MEA) signals. We cultured rat primary cortical neurons and astrocytes on 60-electrode MEAs with different neuron/astrocyte ratios ranging from 'pure' neuronal cultures to co-cultures containing 50% neurons and 50% astrocytes. Our results show that astrocytes desynchronize the network and reduce predictability in the signals and affect the repolarization phase of the action potentials. Our work highlights that it is crucial to go beyond standard MEA analysis to assess how astrocytes control neuronal cultures and investigate any dysfunction that could potentially result in neuronal hyperactivity.

Breaking the burst: Unveiling mechanisms behind fragmented network bursts in patient-derived neurons

Fragmented network bursts (NBs) are observed as a phenotypic driver in many patient-derived neuronal networks on multi-electrode arrays (MEAs), but the pathophysiological mechanisms underlying this phenomenon are unknown. Here, we used our previously developed biophysically detailed in silico model to investigate these mechanisms. Fragmentation of NBs in our model simulations occurred only when the level of short-term synaptic depression (STD) was enhanced, suggesting that STD is a key player. Experimental validation with Dynasore, an STD enhancer, induced fragmented NBs in healthy neuronal networks invitro. Additionally, we showed that strong asynchronous neurotransmitter release, NMDA currents, or short-term facilitation (STF) can support the emergence of multiple fragments in NBs by producing excitation that persists after high-frequency firing stops. Our results provide important insights into disease mechanisms and potential pharmaceutical targets for neurological disorders modeled using human induced pluripotent stem cell (hiPSC)-derived neurons.

Recording and Interpretation of Active Calcium Transients in Induced Pluripotent Stem Cell-Derived Cardiomyocytes.

Calcium plays a pivotal role in the excitation-contraction coupling process in cardiomyocytes, a critical multi-parametric event leading to rhythmic contraction. Over the past few decades, calcium signaling in cardiomyocytes has been extensively studied in cardiovascular sciences. However, a standard methodology is needed not only to trace the calcium within cells but also to remove signal processing biases and to accurately interpret the features of calcium transient signals in relation to cardiomyocyte electrophysiology. This article outlines the use of genetically encoded calcium indicator (GCaMP) human-induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) to record calcium transients. These cells express a green fluorescent signal when calcium binds to intracellular calmodulin, a key regulator of calcium signaling. The extraction and processing of calcium transient waveforms are performed using ImageJ and MATLAB software. Key features of these waveforms are then identified and categorized based on their physiological relevance to cardiomyocyte function. Additionally, this work includes a Support Protocol for the successful replating of cardiomyocytes onto non-traditional culture platforms, such as metallic sensors and polymer-based substrates, to facilitate data multiplexing. The three Basic Protocols outlined here provide a comprehensive approach for maintaining, expanding, and differentiating the GCaMP hiPSCs, video recording of calcium transients, and the subsequent signal extraction, preprocessing, analysis, and data visualization. © 2024 The Author(s). Current Protocols published by Wiley Periodicals LLC. Basic Protocol 1: Maintenance, expansion, and differentiation of genetically encoded calcium indicator hiPSCs Support Protocol: Replating GCaMP hiPSC-CMs for stimulation and multielectrode array studies Basic Protocol 2: Video recording from calcium transients of GCaMP hiPSC-CMs Basic Protocol 3: Signal extraction, preprocessing, analysis, and data visualization.

Experimental study of oil-water two-phase flow patterns in a vertical large diameter pipe

The flow structure and the phase inversion have great influence on the flow measurement in vertical upward oil-water two-phase flow. This paper attempts to investigate the flow patterns in oil-water flows through a vertical upward large pipe with the designed mini-conductance array probes measurement system and the vertical multi-electrode array (VMEA) measurement system. According to the output waveform of the mini-conductance array probes, the oil-in-water flow, transition flow and water-in-oil flow can be identified effectively. The fluctuating signals of the VMEA is processed by the recurrence plot and the time-frequency representation, the results show that the VMEA conductance signal with average measurement characteristics can realize an effective identification of the above three flow patterns, which has a good agreement with the results of the mini-conductance array probes. Finally, via comparing with previous published flow pattern transition boundary models in different pipe diameters, it is founded that the boundary line of the transition to oil-in-water based on the kinematic wave-based model and the observation-based model in the same diameter pipe are consistent with our experimental data. And the pipe diameter affects the flow pattern transition, compared with the boundary in small diameter pipe, the phase inversion requires a larger oil velocity, and the transition zone becomes narrower in large diameter pipe.

Localization of neurons from extracellular footprints

Background:High density microelectrode arrays (HD-MEAs) are now widely used for both in-vitro and in-vivo recordings, as they allow spikes from hundreds of neurons to be recorded simultaneously. Since extracellular recordings do not allow visualization of the recorded neurons, algorithms are needed to estimate their physical positions, especially to track their movements when the are drifting away from recording devices. New Method:The objective of this study was to evaluate the performance of multiple algorithms for neuron localization solely from extracellular traces (MEA recordings), either artificial or obtained from mouse retina. The algorithms compared included center-of-mass, monopolar, and grid-based algorithms. The first method is a barycenter calculation. The second algorithm infers the position of the cell using triangulation with the assumption that the neuron behaves as a monopole. Finally, grid-based methods rely on comparing the recorded spike with a projection of spikes of hypothetical neurons with different positions. Results:The Grid-Based algorithm yielded the most satisfactory outcomes. The center-of-mass exhibited a minimal computational cost, yet its average localization was suboptimal. Monopolar algorithms gave cell localizations with an average error of less than 10μm, but they had considerable variability and a high computational cost. For the grid-based method, the variability was smaller, with satisfactory performance and low computational cost. Comparison with Existing Method(s):The accuracy of the different localization methods benchmarked in this article had not been properly tested with ground-truth recordings before. Conclusion:The objective of this article is to provide guidance to researchers on the selection of optimal methods for localizing neurons based on MEA recordings.

A novel cleanroom-free technique for simultaneous electrodeposition of polypyrrole onto array of IDuEs: Towards low-cost, stable and accurate point-of-care TBI diagnosis without trained manpower

Drop-casted polypyrrole (PPY) nanomaterial-based point-of-care Traumatic Brain Injury (TBI) immunosensing platforms reported previously demand trained manpower at field-test, due to poor adhesion between nanomaterial and electrode surface, limiting the point-of-care purpose. The usage of conventional clean-room-based physical and chemical vapor deposition techniques in creating strong adhesion is limited on account of cost and process complexity. Addressing this technical gap, we report a novel low-cost clean-room-free technique that can effectively electrodeposit the PPY simultaneously onto the working areas of array of Interdigitated microelectrodes (IDμEs) from the precursor solution. Through optimization of deposition cycles and molar concentration ratio of monomer and oxidizing agents, a high-quality nanomaterial was electrodeposited on IDμEs' surface. Further, by using the electrodeposited PPY as a bioelectrical transducer, the TBI-specific UCHL1 and GFAP target analytes were simultaneously detected in terms of variation of DC-Resistance and AC-Capacitance parameters, recorded through chemiresistive I-V and chemicapacitive C-F responses of bioelectrodes, respectively. Such simultaneous multianalyte-detection in terms of multiple parameters increases the diversity of decision-making parameters by several folds, inherently aids in enhancing the diagnostic accuracy of TBI test kit. Here, the efficiency of the electrodeposited PPY-based chemiresistive and chemicapacitive immunosensing platforms in detecting TBI-specific target analytes simultaneously in real-time human-plasma samples was analyzed in terms of sensitivity, resolution, LoD, RoD, long-term stability (30 weeks), and the same is compared with drop-cast PPY-based immunosensing platform. Notably, the electrodeposited PPY sensing platforms showed superior performance in terms of sensitivity, LoD, device variability and long-term stability without demanding any trained manpower in the field.

Spared ulnar nerve injury results in increased layer III–VI excitability in the pig somatosensory cortex

This study describes cortical recordings in a large animal nerve injury model. We investigated differences in primary somatosensory cortex (S1) hyperexcitability when stimulating injured and uninjured nerves and how different cortical layers contribute to S1 hyperexcitability after spared ulnar nerve injury. We used a multielectrode array to record single-neuron activity in the S1 of ten female Danish landrace pigs. Electrical stimulation of the injured and uninjured nerve evoked brain activity up to 3 h after injury. The peak amplitude and latency of early and late peristimulus time histogram responses were extracted for statistical analysis. Histological investigations determined the layer of the cortex in which each electrode contact was placed. Nerve injury increased the early peak amplitude compared with that of the control group. This difference was significant immediately after nerve injury when the uninjured nerve was stimulated, while it was delayed for the injured nerve. The amplitude of the early peak was increased in layers III–VI after nerve injury compared with the control. In layer III, S1 excitability was also increased compared with preinjury for the early peak. Furthermore, the late peak was significantly larger in layer III than in the other layers in the intervention and control group before and after injury. Thus, the most prominent increase in excitability occurred in layer III, which is responsible for the gain modulation of cortical output through layer V. Therefore, layer III neurons seem to have an important role in altered brain excitability after nerve injury.

Brain Function, Learning, and Role of Feedback in Complete Paralysis.

The determinants and driving forces of communication abilities in the locked-in state are poorly understood so far. Results from an experimental-clinical study on a completely paralyzed person involved in communication sessions after the implantation of a microelectrode array were retrospectively analyzed. The aim was to focus on the prerequisites and determinants for learning to control a brain-computer interface for communication in paralysis. A comparative examination of the communication results with the current literature was carried out in light of an ideomotor theory of thinking. We speculate that novel skill learning took place and that several aspects of the wording of sentences during the communication sessions reflect preserved cognitive and conscious processing. We also present some speculations on the operant learning procedure used for communication, which argues for the reformulation of the previously postulated hypothesis of the extinction of response planning and goal-directed ideas in the completely locked-in state. We highlight the importance of feedback and reinforcement in the thought-action-consequence associative chain necessary to maintain purposeful communication. Finally, we underline the necessity to consider the psychosocial context of patients and the duration of complete immobilization as determinants of the 'extinction of thinking' theory and to identify the actual barriers preventing communication in these patients.

Graphene Microelectrode Arrays, 4D Structured Illumination Microscopy, and a Machine Learning Spike Sorting Algorithm Permit the Analysis of Ultrastructural Neuronal Changes During Neuronal Signaling in a Model of Niemann-Pick Disease Type C.

Simultaneously recording network activity and ultrastructural changes of the synapse is essential for advancing understanding of the basis of neuronal functions. However, the rapid millisecond-scale fluctuations in neuronal activity and the subtle sub-diffraction resolution changes of synaptic morphology pose significant challenges to this endeavor. Here, specially designed graphene microelectrode arrays (G-MEAs) are used, which are compatible with high spatial resolution imaging across various scales as well as permit high temporal resolution electrophysiological recordings to address these challenges. Furthermore, alongside G-MEAs, an easy-to-implement machine learning algorithm is developed to efficiently process the large datasets collected from MEA recordings. It is demonstrated that the combined use of G-MEAs, machine learning (ML) spike analysis, and 4D structured illumination microscopy (SIM) enables monitoring the impact of disease progression on hippocampal neurons which are treated with an intracellular cholesterol transport inhibitor mimicking Niemann-Pick disease type C (NPC), and show that synaptic boutons, compared to untreated controls, significantly increase in size, leading to a loss in neuronal signaling capacity.

A Multi-Electrode Array Platform for Modeling Epilepsy Using Human Pluripotent Stem Cell-Derived Brain Assembloids.

Human brain organoids are three-dimensional (3D) structures derived from human pluripotent stem cells (hPSCs) that recapitulateaspects of fetal brain development. The fusion of dorsal with ventral regionally specified brain organoids in vitro generates assembloids, which have functionally integrated microcircuits with excitatory and inhibitory neurons. Due to their structural complexity and diverse population of neurons, assembloids have become a useful in vitro tool for studying aberrant network activity. Multi-electrode array (MEA) recordings serve as a method for capturing electrical field potentials, spikes, and longitudinal network dynamics from a population of neurons without compromising cell membrane integrity. However, adhering assembloids onto the electrodes for long-term recordings can be challenging due to their large size and limited contact surface area with the electrodes. Here, we demonstrate a method to plate assembloids onto MEA plates for recording electrophysiological activity over a 2-month span. Although the current protocol utilizes human cortical organoids, it can be broadly adapted to organoids differentiated to model other brain regions. This protocol establishes a robust, longitudinal, electrophysiological assay for studying the development of a neuronal network, and this platform has the potential to be used in drug screening for therapeutic development in epilepsy.

Isolating and Culturing Chick Embryonic Neurons on a Multi-Electrode Array

Isolating and Culturing Chick Embryonic Neurons on a Multi-Electrode Array

Isolating and Culturing Chick Embryonic Neurons on a Multi-Electrode Array

Isolating and Culturing Chick Embryonic Neurons on a Multi-Electrode Array

Transparent MXene Microelectrode Arrays for Multimodal Mapping of Neural Dynamics.

Transparent microelectrode arrays have proven useful in neural sensing, offering a clear interface for monitoring brain activity without compromising high spatial and temporal resolution. The current landscape of transparent electrode technology faces challenges in developing durable, highly transparent electrodes while maintaining low interface impedance and prioritizing scalable processing and fabrication methods. To address these limitations, we introduce artifact-resistant transparent MXene microelectrode arrays optimized for high spatiotemporal resolution recording of neural activity. With 60% transmittance at 550 nm, these arrays enable simultaneous imaging and electrophysiology for multimodal neural mapping. Electrochemical characterization shows low impedance of 563 ± 99 kΩ at 1 kHz and a charge storage capacity of 58 mC cm⁻² without chemical doping. In vivo experiments in rodent models demonstrate the transparent arrays' functionality and performance. In a rodent model of chemically-induced epileptiform activity, we tracked ictal wavefronts via calcium imaging while simultaneously recording seizure onset. In the rat barrel cortex, we recorded multi-unit activity across cortical depths, showing the feasibility of recording high-frequency electrophysiological activity. The transparency and optical absorption properties of Ti₃C₂Tx MXene microelectrodes enable high-quality recordings and simultaneous light-based stimulation and imaging without contamination from light-induced artifacts.

High-Quality Seizure-Like Activity from Acute Brain Slices Using a Complementary Metal-Oxide-Semiconductor High-Density Microelectrode Array System.

Complementary metal-oxide-semiconductor high-density microelectrode array (CMOS-HD-MEA) systems can record neurophysiological activity from cell cultures and ex vivo brain slices in unprecedented electrophysiological detail. CMOS-HD-MEAs were first optimized to record high-quality neuronal unit activity from cell cultures but have also been shown to produce quality data from acute retinal and cerebellar slices. Researchers have recently used CMOS-HD-MEAs to record local field potentials (LFPs) from acute, cortical rodent brain slices. One LFP of interest is seizure-like activity. While many users have produced brief, spontaneous epileptiform discharges using CMOS-HD-MEAs, few users reliably produce quality seizure-like activity. Many factors may contribute to this difficulty, including electrical noise, the inconsistent nature of producing seizure-like activity when using submerged recording chambers, and the limitation that 2D CMOS-MEA chips only record from the surface of the brain slice. The techniques detailed in this protocol should enable users to consistently induce and record high-quality seizure-like activity from acute brain slices with a CMOS-HD-MEA system. In addition, this protocol outlines the proper treatment of CMOS-HD-MEA chips, the management of solutions and brain slices during experimentation, and equipment maintenance.

Functional efficacy of the MAO-B inhibitor safinamide in murine substantia nigra pars compacta dopaminergic neurons in vitro: A comparative study with tranylcypromine

Safinamide (SAF) is currently used to treat Parkinson's disease (PD) symptoms based on its theoretical ability to potentiate the dopamine (DA) signal, blocking monoamine oxidase (MAO) B. The present work aims to highlight the functional relevance of SAF as an enhancer of the DA signal, by evaluating its ability to prolong recovery from DA-mediated firing inhibition of DAergic neurons of the substantia nigra pars compacta (SNpc), compared to another MAO antagonist, tranylcypromine (TCP). Using multielectrode array (MEA) and single electrode extracellular recordings of spontaneous spikes from presumed SNpc DAergic cells in vitro, we show that SAF (30 μM) mildly prolongs the DA-mediated firing inhibition, as opposed to the profound effect of TCP (10 μM). In patch-clamp recordings, we found that SAF (30 μM) significantly reduced the number of spikes evoked by depolarizing currents in SNpc DAergic neurons, in a sulpiride (1 μM) independent manner. According to our results, SAF marginally potentiates the DA signal in SNpc DAergic neurons, while exerting an inhibitory effect on the postsynaptic excitability acting on membrane conductances. Thus, we propose that the therapeutic effects of SAF in PD patients partially depends on MAO inhibition, while other MAO-independent sites of action could be more relevant.

Adsorptive Stripping Voltammetric Quercetin Determination in Pharmaceuticals and Urine Samples Using a Long Service-Life Array of Carbon Composite Microelectrodes.

This article presents for the first time a new working electrode with a long service life- the bismuth-plated array of carbon composite microelectrodes for the simple, fast and sensitive determination of quercetin by adsorptive stripping voltammetry. The main experimental conditions were selected. The calibration graph was linear from 1 × 10-9 to 2 × 10-8 mol L-1 with an accumulation time of 60 s. The detection limit was equal to 4.8 × 10-10 mol L-1. The relative standard deviation for 2 × 10-8 mol L-1 of quercetin was 4.4% (n = 7). Possible interference effects resulting from the presence of other organic and surface active compounds and interfering ions were studied. The developed procedure was successfully applied to determine quercetin in pharmaceutical preparations and the spiked urine samples.

Altered development and network connectivity in a human neuronal model of 15q11.2 deletion-related neurodevelopmental disorders.

The chromosome 15q11.2 locus is deleted in 1.5% of patients with genetic epilepsy and confers a risk for intellectual disability and schizophrenia. Individuals with this deletion demonstrate increased cortical thickness, decreased cortical surface area and white matter abnormalities. Human induced pluripotent stem cell (iPSC)-derived neural progenitor cells (NPC) from 15q11.2 deletion individuals exhibit early adhesion junction and migration abnormalities, but later neuronal development and function have not been fully assessed. Imaging studies indicating altered structure and network connectivity in the anterior brain regions and the cingulum suggest that in addition to alterations in progenitor dynamics, there may also be structural and functional changes within discrete networks of mature neurons. To explore this, we generated human forebrain cortical neurons from iPSCs derived from individuals with or without 15q11.2 deletion and used longitudinal imaging and multielectrode array analysis to evaluate neuronal development over time. 15q11.2 deleted neurons exhibited fewer connections and an increase in inhibitory neurons. Individual neurons had decreased neurite complexity and overall decreased neurite length. These structural changes were associated with a reduction in multiunit action potential generation, bursting and synchronization. The 15q11.2 deleted neurons also demonstrated specific functional deficits in glutamate and GABA mediated network activity and synchronization with a delay in the maturation of the inhibitory response to GABA. These data indicate that deletion of the 15q11.2 region is sufficient to impair the structural and functional maturation of cortical neuron networks which likely underlies the pathologic changes in humans with the 15q11.2 deletion.