Revealing neuronal function through microelectrode array recordings

Nanoencapsulated Optical Fiber-Based PEC Microelectrode: Highly Sensitive and Specific Detection of NT-proBNP and Its Implantable Performance

Microelectrodes offer exceptional sensitivity, rapid response, and versatility, making them ideal for real-time detection and monitoring applications. Photoelectrochemical (PEC) sensors have shown great value in many fields due to their high sensitivity, fast response, and ease of operation. Nevertheless, conventional PEC sensing relies on cumbersome external light sources and bulky electrodes, hindering its miniaturization and implantation, thereby limiting its application in real-time disease monitoring. To overcome these limitations, we developed a nanoencapsulated optical fiber (OF)-based PEC microelectrode. The microelectrode features TiO2/CdS nanocrystals and bis (2,2'-bipyridine) (10-methylphenanthroline [3,2-a:2'3'-c] pyridine ruthenium(II) dichloride ([Ru(bpy)2dppz]2+) @dsDNA/Au@epigallocatechin gallate nanoparticle (EGCG NP) layers. And its application for the detection of N-terminal pro-brain natriuretic peptide (NT-proBNP) as a biomarker of cardiovascular diseases was explored. An extensive linear range of 1-5000 pg mL-1 combined with a low detection limit of 0.36 pg mL-1 was achieved. This range covers not only the recommended threshold for excluding cardiovascular diseases in the clinical diagnosis of individuals across all age groups but also the prognostic target value. The sensor exhibited excellent selectivity and stability and notable labeling recovery capability in serum tests. Critically, the sensor successfully discriminated the alterations in NT-proBNP secretion levels within human smooth muscle cells, comparing pre- and poststimulation by platelet-derived growth factor-BB. Even more significantly, the skin puncture experiment conducted in mice demonstrated the remarkable implantability and biological compatibility of the OF-PEC microelectrode. This addresses critical challenges commonly faced by microelectrodes when used as implanted devices, such as minimizing invasive trauma, mitigating inflammation, and preventing biofouling, thereby firmly establishing their suitability for the development of advanced implantable sensing devices. Therefore, the present OF microelectrode PEC biosensor is not only cost-effective, easy to operate, and miniaturized but also holds significant potential for enabling more precise, more minimally invasive, and continuous monitoring of biological markers without causing inflammation. This capability is crucial for early disease detection, tracking disease progression, and facilitating personalized treatment strategies, which expands the practical application of PEC sensors.

Multi-material Electrohydrodynamic Printing of Bioelectronics with Sub-Microscale 3D Gold Pillars for In Vitro Extra- and Intra-Cellular Electrophysiological Recordings

Micro/nanoscale 3D bioelectrodes gain increasing interest for electrophysiological recording of electroactive cells. Although 3D printing has shown promise to flexibly fabricate 3D bioelectronics compared with conventional microfabrication, relatively-low resolution limits the printed bioelectrode for high-quality signal monitoring. Here, a novel multi-material electrohydrodynamic printing (EHDP) strategy is proposed to fabricate bioelectronics with sub-microscale 3D gold pillars for in vitro electrophysiological recordings. EHDP is employed to fabricate conductive circuits for signal transmission, which are passivated by polyimide via extrusion-based printing. Laser-assisted EHDP is developed to produce 3D gold pillars featuring a diameter of 0.64 ± 0.04 µm. The 3D gold pillars demonstrate stable conductivity under the cell-culture environment. Living cells can conformally grow onto these sub-microscale 3D pillars with a height below 5 µm, which facilitates the highly-sensitive recording of extracellular signals with amplitudes <15 µV. The 3D pillars can apply electroporation currents to reversibly open the cellular membrane for intracellular recording, facilitating the measurement of subtle cellular electrophysiological activities. As a proof-of-concept demonstration, fully-printed chips with multiple culturing chambers and sensing bioelectronics are fabricated for zone-specific electrophysiological recording in drug testing. The proposed multi-material EHDP strategy enables rapid prototyping of organ-on-a-chip systems with 3D bioelectronics for high-quality electrophysiological recordings.

Harnessing the potential of human induced pluripotent stem cells, functional assays and machine learning for neurodevelopmental disorders

Neurodevelopmental disorders (NDDs) affect 4.7% of the global population and are associated with delays in brain development and a spectrum of impairments that can lead to lifelong disability and even mortality. Identification of biomarkers for accurate diagnosis and medications for effective treatment are lacking, in part due to the historical use of preclinical model systems that do not translate well to the clinic for neurological disorders, such as rodents and heterologous cell lines. Human-induced pluripotent stem cells (hiPSCs) are a promising in vitro system for modeling NDDs, providing opportunities to understand mechanisms driving NDDs in human neurons. Functional assays, including patch clamping, multielectrode array, and imaging-based assays, are popular tools employed with hiPSC disease models for disease investigation. Recent progress in machine learning (ML) algorithms also presents unprecedented opportunities to advance the NDD research process. In this review, we compare two-dimensional and three-dimensional hiPSC formats for disease modeling, discuss the applications of functional assays, and offer insights on incorporating ML into hiPSC-based NDD research and drug screening.

High-density multielectrode arrays bring cellular resolution to neuronal activity and network analyses of corticospinal motor neurons

Corticospinal motor neurons (CSMN), located in the motor cortex of the brain, are one of the key components of the motor neuron circuitry. They are in part responsible for the initiation and modulation of voluntary movement, and their degeneration is the hallmark for numerous diseases, such as amyotrophic lateral sclerosis (ALS), hereditary spastic paraplegia, and primary lateral sclerosis. Cortical hyperexcitation followed by in-excitability suggests the early involvement of cortical dysfunction in ALS pathology. However, a high-spatiotemporal resolution on our understanding of their functional health and connectivity is lacking. Here, we combine optical imaging with high-density microelectrode array (HD-MEA) system enabling single cell resolution and utilize UCHL1-eGFP mice to bring cell-type specificity to our understanding of the electrophysiological features of healthy CSMN, as they mature and form network connections with other cortical neurons, in vitro. This novel approach lays the foundation for future cell-type specific analyses of CSMN that are diseased due to different underlying causes with cellular precision, and it will allow the assessment of their functional response to compound treatment, especially for drug discovery efforts in upper motor neuron diseases.

Reducing education inequalities through cloud-enabled live-cell biotechnology

Biotechnology holds the potential to drive innovations across various fields from agriculture to medicine. However, despite numerous interventions, biotechnology education remains highly unequal worldwide. Historically, the high costs and potential exposure to hazardous materials have hindered biotechnology education. Integration of cloud technologies into classrooms has emerged as an alternative solution that is already enabling biotechnology experiments to reach thousands of students globally. We describe several innovations that collectively facilitate real-time experimentation in biotechnology education in remote locations. These advances enable remote access to scientific data and live experiments, promote collaborative research, and ensure educational inclusivity. We propose cloud-enabled live-cell biotechnology as a mechanism for reducing inequalities in biotechnology education and promoting sustainable development.

A light-addressable potentiometric sensor-based extracellular calcium dynamic monitoring and imaging platform for cellular calcium channel drug evaluation

Disruption and dysregulation of cellular calcium channel function can lead to diseases such as ischemic stroke, heart failure, and arrhythmias. Corresponding calcium channel drugs typically require preliminary efficacy evaluations using in vitro models such as cells and simulated tissues before clinical testing. However, traditional detection and evaluation methods often encounter challenges in long-term continuous monitoring and lack calcium specificity. In this study, a dynamic monitoring system based on ion-sensitive membranes for light-addressable potentiometric sensor (LAPS) was developed to meet the demand for monitoring changes in extracellular calcium ion (Ca2+) concentration in live cells. The effects of Ca2+ channel agonists and blockers on 2D and 3D HL-1 cells were investigated, with changes in extracellular Ca2+ concentration reflecting cellular calcium metabolism, facilitating drug evaluation. Additionally, calcium imaging technology with optical addressing capability complemented the LAPS system's ability to perceive 3D cell morphology, enhancing its drug evaluation capabilities. This work provides a novel, label-free, specific, and stable technique for monitoring cellular calcium metabolism. It achieves both continuous monitoring at single points and custom sensing area calcium imaging, holding significant implications for drug screening and disease treatment related to human calcium homeostasis.

Electrical excitability of neuronal networks based on the voltage threshold of electrical stimulation

Microelectrode arrays (MEAs) have been widely used in studies on the electrophysiological features of neuronal networks. In classic MEA experiments, spike or burst rates and spike waveforms are the primary characteristics used to evaluate the neuronal network excitability. Here, we introduced a new method to assess the excitability using the voltage threshold of electrical stimulation. We tested the stability of the voltage threshold during the experiment and demonstrated the reliability of our method by examining the effect of Ni2+ on neocortical neuronal networks of acute brain slices from rats. Moreover, we compared our new method with the spontaneous activity analysis, which is one of the most commonly used methods in protocols for large-scale drug screening with MEA; our new method performed better in the experiments investigating the neocortical neuronal network excitability after the application of Ni2+. Based on the results from our study, our new method has great potential for use in large-scale screening of drugs.

Decoding neuronal networks: A Reservoir Computing approach for predicting connectivity and functionality

In this study, we address the challenge of analyzing electrophysiological measurements in neuronal networks. Our computational model, based on the Reservoir Computing Network (RCN) architecture, deciphers spatio-temporal data obtained from electrophysiological measurements of neuronal cultures. By reconstructing the network structure on a macroscopic scale, we reveal the connectivity between neuronal units. Notably, our model outperforms common methods such as Cross-Correlation, Transfer-Entropy, and a recently developed related algorithm in predicting the network's connectivity map. Furthermore, we experimentally validate its ability to forecast network responses to specific inputs, including localized optogenetic stimuli.

Towards measurements of absolute membrane potential in Bacillus subtilis using fluorescence lifetime

Membrane potential (MP) changes can provide a simple readout of bacterial functional and metabolic state or stress levels. While several optical methods exist for measuring fast changes in MP in excitable cells, there is a dearth of such methods for absolute and precise measurements of steady-state membrane potentials (MPs) in bacterial cells. Conventional electrode-based methods for the measurement of MP are not suitable for calibrating optical methods in small bacterial cells. While optical measurement based on Nernstian indicators have been successfully used, they do not provide absolute or precise quantification of MP or its changes. We present a novel, calibrated MP recording approach to address this gap. In this study, we used a fluorescence lifetime-based approach to obtain a single-cell resolved distribution of the membrane potential and its changes upon extracellular chemical perturbation in a population of bacterial cells for the first time. Our method is based on (i) a unique VoltageFluor (VF) optical transducer, whose fluorescence lifetime varies as a function of MP via photoinduced electron transfer (PeT) and (ii) a quantitative phasor-FLIM analysis for high-throughput readout. This method allows MP changes to be easily visualized, recorded and quantified. By artificially modulating potassium concentration gradients across the membrane using an ionophore, we have obtained a Bacillus subtilis-specific MP versus VF lifetime calibration and estimated the MP for unperturbed B. subtilis cells to be -65 mV (in MSgg), 127 mV (in M9) and that for chemically depolarized cells as -14 mV (in MSgg). We observed a population level MP heterogeneity of ~6-10 mV indicating a considerable degree of diversity of physiological and metabolic states among individual cells. Our work paves the way for deeper insights into bacterial electrophysiology and bioelectricity research.

Revealing single-neuron and network-activity interaction by combining high-density microelectrode array and optogenetics

The synchronous activity of neuronal networks is considered crucial for brain function. However, the interaction between single-neuron activity and network-wide activity remains poorly understood. This study explored this interaction within cultured networks of rat cortical neurons. Employing a combination of high-density microelectrode array recording and optogenetic stimulation, we established an experimental setup enabling simultaneous recording and stimulation at a precise single-neuron level that can be scaled to the level of the whole network. Leveraging our system, we identified a network burst-dependent response change in single neurons, providing a possible mechanism for the network-burst-dependent loss of information within the network and consequent cognitive impairment during epileptic seizures. Additionally, we directly recorded a leader neuron initiating a spontaneous network burst and characterized its firing properties, indicating that the bursting activity of hub neurons in the brain can initiate network-wide activity. Our study offers valuable insights into brain networks characterized by a combination of bottom-up self-organization and top-down regulation.

Reverse engineering of feedforward cortical-Hippocampal microcircuits for modelling neural network function and dysfunction

Engineered biological neural networks are indispensable models for investigation of neural function and dysfunction from the subcellular to the network level. Notably, advanced neuroengineering approaches are of significant interest for their potential to replicate the topological and functional organization of brain networks. In this study, we reverse engineered feedforward neural networks of primary cortical and hippocampal neurons, using a custom-designed multinodal microfluidic device with Tesla valve inspired microtunnels. By interfacing this device with nanoporous microelectrodes, we show that the reverse engineered multinodal neural networks exhibit capacity for both segregated and integrated functional activity, mimicking brain network dynamics. To advocate the broader applicability of our model system, we induced localized perturbations with amyloid beta to study the impact of pathology on network functionality. Additionally, we demonstrate long-term culturing of subregion- and layer specific neurons extracted from the entorhinal cortex and hippocampus of adult Alzheimer's-model mice and rats. Our results thus highlight the potential of our approach for reverse engineering of anatomically relevant multinodal neural networks to study dynamic structure-function relationships in both healthy and pathological conditions.

Monitoring Electrochemical Dynamics through Single-Molecule Imaging of hBN Surface Emitters in Organic Solvents

Electrochemical techniques conventionally lack spatial resolution and average local information over an entire electrode. While advancements in spatial resolution have been made through scanning probe methods, monitoring dynamics over large areas is still challenging, and it would be beneficial to be able to decouple the probe from the electrode itself. In this work, we leverage single molecule microscopy to spatiotemporally monitor analyte surface concentrations over a wide area using unmodified hexagonal boron nitride (hBN) in organic solvents. Through a sensing scheme based on redox-active species interactions with fluorescent emitters at the surface of hBN, we observe a region of a linear decrease in the number of emitters against increasingly positive potentials applied to a nearby electrode. We find consistent trends in electrode reaction kinetics vs overpotentials between potentiostat-reported currents and optically read emitter dynamics, showing Tafel slopes greater than 290 mV·decade-1. Finally, we draw on the capabilities of spectral single-molecule localization microscopy (SMLM) to monitor the fluorescent species' identity, enabling multiplexed readout. Overall, we show dynamic measurements of analyte concentration gradients on a micrometer-length scale with nanometer-scale depth and precision. Considering the many scalable options for engineering fluorescent emitters with two-dimensional (2D) materials, our method holds promise for optically detecting a range of interacting species with exceptional localization precision.

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.

Multimodal Mapping of Electrical and Mechanical Latency of Human-Induced Pluripotent Stem Cell-Derived Cardiomyocyte Layers

The synchronization of the electrical and mechanical coupling assures the physiological pump function of the heart, but life-threatening pathologies may jeopardize this equilibrium. Recently, human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) have emerged as a model for personalized investigation because they can recapitulate human diseased traits, such as compromised electrical capacity or mechanical circuit disruption. This research avails the model of hiPSC-CMs and showcases innovative techniques to study the electrical and mechanical properties as well as their modulation due to inherited cardiomyopathies. In this work, hiPSC-CMs carrying either Brugada syndrome (BRU) or dilated cardiomyopathy (DCM), were organized in a bilayer configuration to first validate the experimental methods and second mimic the physiological environment. High-density CMOS-based microelectrode arrays (HD-MEA) have been employed to study the electrical activity. Furthermore, mechanical function was investigated via quantitative video-based evaluation, upon stimulation with a β-adrenergic agonist. This study introduces two experimental methods. First, high-throughput mechanical measurements in the hiPSC-CM layers (xy-inspection) are obtained using both a recently developed optical tracker (OPT) and confocal reference-free traction force microscopy (cTFM) aimed to quantify cardiac kinematics. Second, atomic force microscopy (AFM) with FluidFM probes, combined with the xy-inspection methods, supplemented a three-dimensional understanding of cell-cell mechanical coupling (xyz-inspection). This particular combination represents a multi-technique approach to detecting electrical and mechanical latency among the cell layers, examining differences and possible implications following inherited cardiomyopathies. It can not only detect disease characteristics in the proposed in vitro model but also quantitatively assess its response to drugs, thereby demonstrating its feasibility as a scalable tool for clinical and pharmacological studies.

Multifunctional Conductive Hydrogel Interface for Bioelectronic Recording and Stimulation

The past few decades have witnessed the rapid advancement and broad applications of flexible bioelectronics, in wearable and implantable electronics, brain-computer interfaces, neural science and technology, clinical diagnosis, treatment, etc. It is noteworthy that soft and elastic conductive hydrogels, owing to their multiple similarities with biological tissues in terms of mechanics, electronics, water-rich, and biological functions, have successfully bridged the gap between rigid electronics and soft biology. Multifunctional hydrogel bioelectronics, emerging as a new generation of promising material candidates, have authentically established highly compatible and reliable, high-quality bioelectronic interfaces, particularly in bioelectronic recording and stimulation. This review summarizes the material basis and design principles involved in constructing hydrogel bioelectronic interfaces, and systematically discusses the fundamental mechanism and unique advantages in bioelectrical interfacing with the biological surface. Furthermore, an overview of the state-of-the-art manufacturing strategies for hydrogel bioelectronic interfaces with enhanced biocompatibility and integration with the biological system is presented. This review finally exemplifies the unprecedented advancement and impetus toward bioelectronic recording and stimulation, especially in implantable and integrated hydrogel bioelectronic systems, and concludes with a perspective expectation for hydrogel bioelectronics in clinical and biomedical applications.

A fully automatic multichannel neural spike sorting algorithm with spike reduction and positional feature

Objective: The sorting of neural spike data recorded by multichannel and high channel neural probes such as Neuropixels, especially in real-time, remains a significant technical challenge. Most neural spike sorting algorithms focus on sorting neural spikes post-hoc for high sorting accuracy-but reducing the processing delay for fast sorting, potentially even live sorting, is generally not possible with these algorithms.Approach: Here we report our Graph nEtwork Multichannel sorting (GEMsort) algorithm, which is largely based on graph network, to allow rapid neural spike sorting for multiple neural recording channels. This was accomplished by two innovations: In GEMsort, duplicated neural spikes recorded from multiple channels were eliminated from duplicate channels by only selecting the highest amplitude neural spike in any channel for subsequent processing. In addition, the channel from which the representative neural spike was recorded was used as an additional feature to differentiate between neural spikes recorded from different neurons having similar temporal features.Main results: Synthetic and experimentally recorded multichannel neural recordings were used to evaluate the sorting performance of GEMsort. The sorting results of GEMsort were also compared with two other state-of-the-art sorting algorithms (Kilosort and Mountainsort) in sorting time and sorting agreements.Significance: GEMsort allows rapidly sort neural spikes and is highly suitable to be implemented with digital circuitry for high processing speed and channel scalability.

Exploring Kainic Acid-Induced Alterations in Circular Tripartite Networks with Advanced Analysis Tools

Brain activity implies the orchestrated functioning of interconnected brain regions. Typical in vitro models aim to mimic the brain using single human pluripotent stem cell-derived neuronal networks. However, the field is constantly evolving to model brain functions more accurately through the use of new paradigms, e.g., brain-on-a-chip models with compartmentalized structures and integrated sensors. These methods create novel data requiring more complex analysis approaches. The previously introduced circular tripartite network concept models the connectivity between spatially diverse neuronal structures. The model consists of a microfluidic device allowing axonal connectivity between separated neuronal networks with an embedded microelectrode array to record both local and global electrophysiological activity patterns in the closed circuitry. The existing tools are suboptimal for the analysis of the data produced with this model. Here, we introduce advanced tools for synchronization and functional connectivity assessment. We used our custom-designed analysis to assess the interrelations between the kainic acid (KA)-exposed proximal compartment and its nonexposed distal neighbors before and after KA. Novel multilevel circuitry bursting patterns were detected and analyzed in parallel with the inter- and intracompartmental functional connectivity. The effect of KA on the proximal compartment was captured, and the spread of this effect to the nonexposed distal compartments was revealed. KA induced divergent changes in bursting behaviors, which may be explained by distinct baseline activity and varied intra- and intercompartmental connectivity strengths. The circular tripartite network concept combined with our developed analysis advances importantly both face and construct validity in modeling human epilepsy in vitro.

Novel Multiparametric Bioelectronic Measurement System for Monitoring Virus-Induced Alterations in Functional Neuronal Networks

Development and optimisation of bioelectronic monitoring techniques like microelectrode array-based field potential measurement and impedance spectroscopy for the functional, label-free and non-invasive monitoring of in vitro neuronal networks is widely investigated in the field of biosensors. Thus, these techniques were individually used to demonstrate the capabilities of, e.g., detecting compound-induced toxicity in neuronal culture models. In contrast, extended application for investigating the effects of central nervous system infecting viruses are rarely described. In this context, we wanted to analyse the effect of herpesviruses on functional neuronal networks. Therefore, we developed a unique hybrid bioelectronic monitoring platform that allows for performing field potential monitoring and impedance spectroscopy on the same microelectrode. In the first step, a neuronal culture model based on primary hippocampal cells from neonatal rats was established with reproducible and stable synchronised electrophysiological network activity after 21 days of cultivation on microelectrode arrays. For a proof of concept, the pseudorabies model virus PrV Kaplan-ΔgG-GFP was applied and the effect on the neuronal networks was monitored by impedance spectroscopy and field potential measurement for 72 h in a multiparametric mode. Analysis of several bioelectronic parameters revealed a virus concentration-dependent degeneration of the neuronal network within 24-48 h, with a significant early change in electrophysiological activity, subsequently leading to a loss of activity and network synchronicity. In conclusion, we successfully developed a microelectrode array-based hybrid bioelectronic measurement platform for quantitative monitoring of pathologic effects of a herpesvirus on electrophysiological active neuronal networks.

Invasive Brain Computer Interface for Motor Restoration in Spinal Cord Injury: A Systematic Review

STUDY DESIGN

Systematic review of the literature.

OBJECTIVES

In recent years, brain-computer interface (BCI) has emerged as a potential treatment for patients with spinal cord injury (SCI). This is the first systematic review of the literature on invasive closed-loop BCI technologies for the treatment of SCI in humans.

MATERIALS AND METHODS

A comprehensive search of PubMed MEDLINE, Web of Science, and Ovid EMBASE was conducted following Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines.

RESULTS

Of 8316 articles collected, 19 studies met all the inclusion criteria. Data from 21 patients were extracted from these studies. All patients sustained a cervical SCI and were treated using either a BCI with intracortical microelectrode arrays (n = 18, 85.7%) or electrocorticography (n = 3, 14.3%). To decode these neural signals, machine learning and statistical models were used: support vector machine in eight patients (38.1%), linear estimator in seven patients (33.3%), Hidden Markov Model in three patients (14.3%), and other in three patients (14.3%). As the outputs, ten patients (47.6%) underwent noninvasive functional electrical stimulation (FES) with a cuff; one (4.8%) had an invasive FES with percutaneous stimulation, and ten (47.6%) used an external device (neuroprosthesis or virtual avatar). Motor function was restored in all patients for each assigned task. Clinical outcome measures were heterogeneous across all studies.

CONCLUSIONS

Invasive techniques of BCI show promise for the treatment of SCI, but there is currently no technology that can restore complete functional autonomy in patients with SCI. The current techniques and outcomes of BCI vary greatly. Because invasive BCIs are still in the early stages of development, further clinical studies should be conducted to optimize the prognosis for patients with SCI.

Improvements for recording retinal function with Microelectrode Arrays

A microelectrode array (MEA) is a configuration of multiple electrodes that enables the concurrent targeting of multiple sites for extracellular recording and stimulation. By utilizing light pulses or electrical stimulations, MEA recordings unveil the complex patterns of electrical activities that arise from the signaling processes within the retinal network. Here, we present a stepwise approach for using microelectrode arrays (MEAs) for recording action potentials from the mouse retina in response to electrical and light stimuli. We provide detailed techniques accompanied by description of a custom optical system, example recordings, troubleshooting guidelines, and data processing methods including spike sorting and code resources for analyzing light and electrical responses. The comprehensive nature of this paper aims to guide researchers in utilizing MEAs effectively for investigating retinal functionality. In particular, it can be easy to have a MEA experiment fail, but hard to identify the source of the failure. This paper is meant to demystify that process. It includes:•A description of MEA setup, recording, and spike data validation.•A troubleshooting guide for common failure modes in MEA recordings from mouse retina.•Spike detection and sorting to precisely extract distinctive action potential.

Ion detection in a DNA nanopore FET device

An ion detection device that combines a DNA-origami nanopore and a field-effect transistor (FET) was designed and modeled to determine sensitivity of the nanodevice to the local cellular environment. Such devices could be integrated into a live cell, creating an abiotic-biotic interface integrated with semiconductor electronics. A continuum model is used to describe the behavior of ions in an electrolyte solution. The drift-diffusion equations are employed to model the ion distribution, taking into account the electric fields and concentration gradients. This was matched to the results from electric double layer theory to verify applicability of the model to a bio-sensing environment. The FET device combined with the nanopore is shown to have high sensitivity to ion concentration and nanopore geometry, with the electrical double layer behavior governing the device characteristics. A logarithmic relationship was found between ion concentration and a single FET current, generating up to 200 nA of current difference with a small applied bias.

Stable, chronic in-vivo recordings from a fully wireless subdural-contained 65,536-electrode brain-computer interface device

Minimally invasive, high-bandwidth brain-computer-interface (BCI) devices can revolutionize human applications. With orders-of-magnitude improvements in volumetric efficiency over other BCI technologies, we developed a 50-μm-thick, mechanically flexible micro-electrocorticography (μECoG) BCI, integrating 256×256 electrodes, signal processing, data telemetry, and wireless powering on a single complementary metal-oxide-semiconductor (CMOS) substrate containing 65,536 recording and 16,384 stimulation channels, from which we can simultaneously record up to 1024 channels at a given time. Fully implanted below the dura, our chip is wirelessly powered, communicating bi-directionally with an external relay station outside the body. We demonstrated chronic, reliable recordings for up to two weeks in pigs and up to two months in behaving non-human primates from somatosensory, motor, and visual cortices, decoding brain signals at high spatiotemporal resolution.

Versatile micro-electrode array to monitor human iPSC derived 3D neural tissues at air-liquid interface

Engineered 3D neural tissues made of neurons and glial cells derived from human induced pluripotent stem cells (hiPSC) are among the most promising tools in drug discovery and neurotoxicology. They represent a cheaper, faster, and more ethical alternative to in vivo animal testing that will likely close the gap between in vitro animal models and human clinical trials. Micro-Electrode Array (MEA) technology is known to provide an assessment of compound effects on neural 2D cell cultures and acute tissue preparations by real-time, non-invasive, and long-lasting electrophysiological monitoring of spontaneous and evoked neuronal activity. Nevertheless, the use of engineered 3D neural tissues in combination with MEA biochips still involves series of constraints, such as drastically limited diffusion of oxygen and nutrients within tissues mainly due to the lack of vascularization. Therefore, 3D neural tissues are extremely sensitive to experimental conditions and require an adequately designed interface that provides optimal tissue survival conditions. A well-suited technique to overcome this issue is the combination of the Air-Liquid Interface (ALI) tissue culture method with the MEA technology. We have developed a full 3D neural tissue culture process and a data acquisition system composed of high-end electronics and novel MEA biochips based on porous, flexible, thin-film membranes integrating recording electrodes, named as "Strip-MEA," to allow the maintenance of an ALI around the 3D neural tissues. The main motivation of the porous MEA biochips development was the possibility to monitor and to study the electrical activity of 3D neural tissues under different recording configurations, (i) the Strip-MEA can be placed below a tissue, (ii) or by taking advantage of the ALI, be directly placed on top of the tissue, or finally, (iii) it can be embedded into a larger neural tissue generated by the fusion of two (or more) tissues placed on both sides of the Strip-MEA allowing the recording from its inner part. This paper presents the recording and analyses of spontaneous activity from the three positioning configurations of the Strip-MEAs. Obtained results are discussed with the perspective of developing in vitro models of brain diseases and/or impairment of neural network functioning.

Highly stretchable and customizable microneedle electrode arrays for intramuscular electromyography

Stretchable three-dimensional (3D) penetrating microelectrode arrays have potential utility in various fields, including neuroscience, tissue engineering, and wearable bioelectronics. These 3D microelectrode arrays can penetrate and conform to dynamically deforming tissues, thereby facilitating targeted sensing and stimulation of interior regions in a minimally invasive manner. However, fabricating custom stretchable 3D microelectrode arrays presents material integration and patterning challenges. In this study, we present the design, fabrication, and applications of stretchable microneedle electrode arrays (SMNEAs) for sensing local intramuscular electromyography signals ex vivo. We use a unique hybrid fabrication scheme based on laser micromachining, microfabrication, and transfer printing to enable scalable fabrication of individually addressable SMNEA with high device stretchability (60 to 90%). The electrode geometries and recording regions, impedance, array layout, and length distribution are highly customizable. We demonstrate the use of SMNEAs as bioelectronic interfaces in recording intramuscular electromyography from various muscle groups in the buccal mass of Aplysia.

RIPK3 promotes neuronal survival by suppressing excitatory neurotransmission during CNS viral infection

While recent work has identified roles for immune mediators in the regulation of neural activity, the capacity for cell intrinsic innate immune signaling within neurons to influence neurotransmission remains poorly understood. However, the existing evidence linking immune signaling with neuronal function suggests that modulation of neurotransmission may serve previously undefined roles in host protection during infection of the central nervous system. Here, we identify a specialized function for RIPK3, a kinase traditionally associated with necroptotic cell death, in preserving neuronal survival during neurotropic flavivirus infection through the suppression of excitatory neurotransmission. We show that RIPK3 coordinates transcriptomic changes in neurons that suppress neuronal glutamate signaling, thereby desensitizing neurons to excitotoxic cell death. These effects occur independently of the traditional functions of RIPK3 in promoting necroptosis and inflammatory transcription. Instead, RIPK3 promotes phosphorylation of the key neuronal regulatory kinase CaMKII, which in turn activates the transcription factor CREB to drive a neuroprotective transcriptional program and suppress deleterious glutamatergic signaling. These findings identify an unexpected function for a canonical cell death protein in promoting neuronal survival during viral infection through the modulation of neuronal activity, highlighting new mechanisms of neuroimmune crosstalk.

Simple dynamic cell culture system reduces recording noise in microelectrode array recordings

Microelectrode arrays (MEAs) have applications in drug discovery, toxicology, and basic research. They measure the electrophysiological response of tissue cultures to quantify changes upon exposure to biochemical stimuli. Unfortunately, manual addition of chemicals introduces significant noise in the recordings. Here, we report a simple-to-fabricate fluidic system that addresses this issue. We show that cell cultures can be successfully established in the fluidic compartment under continuous flow conditions and that the addition of chemicals introduces minimal noise in the recordings. This dynamic cell culture system represents an improvement over traditional tissue culture wells used in MEAs, facilitating electrophysiology measurements.

Graphical abstract

Cellular nucleus image-based smarter microscope system for single cell analysis

Cell imaging technology is undoubtedly a powerful tool for studying single-cell heterogeneity due to its non-invasive and visual advantages. It covers microscope hardware, software, and image analysis techniques, which are hindered by low throughput owing to abundant hands-on time and expertise. Herein, a cellular nucleus image-based smarter microscope system for single-cell analysis is reported to achieve high-throughput analysis and high-content detection of cells. By combining the hardware of an automatic fluorescence microscope and multi-object recognition/acquisition software, we have achieved more advanced process automation with the assistance of Robotic Process Automation (RPA), which realizes a high-throughput collection of single-cell images. Automated acquisition of single-cell images has benefits beyond ease and throughout and can lead to uniform standard and higher quality images. We further constructed a single-cell image database-based convolutional neural network (Efficient Convolutional Neural Network, E-CNN) exceeding 20618 single-cell nucleus images. Computational analysis of large and complex data sets enhances the content and efficiency of single-cell analysis with the assistance of Artificial Intelligence (AI), which breaks through the super-resolution microscope's hardware limitation, such as specialized light sources with specific wavelengths, advanced optical components, and high-performance graphics cards. Our system can identify single-cell nucleus images that cannot be artificially distinguished with an accuracy of 95.3%. Overall, we build an ordinary microscope into a high-throughput analysis and high-content smarter microscope system, making it a candidate tool for Imaging cytology.

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

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

Disrupting abnormal neuronal oscillations with adaptive delayed feedback control

Closed-loop neuronal stimulation has a strong therapeutic potential for neurological disorders such as Parkinson's disease. However, at the moment, standard stimulation protocols rely on continuous open-loop stimulation and the design of adaptive controllers is an active field of research. Delayed feedback control (DFC), a popular method used to control chaotic systems, has been proposed as a closed-loop technique for desynchronisation of neuronal populations but, so far, was only tested in computational studies. We implement DFC for the first time in neuronal populations and access its efficacy in disrupting unwanted neuronal oscillations. To analyse in detail the performance of this activity control algorithm, we used specialised in vitro platforms with high spatiotemporal monitoring/stimulating capabilities. We show that the conventional DFC in fact worsens the neuronal population oscillatory behaviour, which was never reported before. Conversely, we present an improved control algorithm, adaptive DFC (aDFC), which monitors the ongoing oscillation periodicity and self-tunes accordingly. aDFC effectively disrupts collective neuronal oscillations restoring a more physiological state. Overall, these results support aDFC as a better candidate for therapeutic closed-loop brain stimulation.

Wireless closed-loop deep brain stimulation using microelectrode array probes

Deep brain stimulation (DBS), including optical stimulation and electrical stimulation, has been demonstrated considerable value in exploring pathological brain activity and developing treatments for neural disorders. Advances in DBS microsystems based on implantable microelectrode array (MEA) probes have opened up new opportunities for closed-loop DBS (CL-DBS) in situ. This technology can be used to detect damaged brain circuits and test the therapeutic potential for modulating the output of these circuits in a variety of diseases simultaneously. Despite the success and rapid utilization of MEA probe-based CL-DBS microsystems, key challenges, including excessive wired communication, need to be urgently resolved. In this review, we considered recent advances in MEA probe-based wireless CL-DBS microsystems and outlined the major issues and promising prospects in this field. This technology has the potential to offer novel therapeutic options for psychiatric disorders in the future.

Surgical Implantation of Brain Computer Interfaces

This article discusses the function and capabilities of brain computer interfaces as a novel approach to rehabilitation for a variety of neurological disorders.

Connectome-based reservoir computing with the conn2res toolbox

The connection patterns of neural circuits form a complex network. How signaling in these circuits manifests as complex cognition and adaptive behaviour remains the central question in neuroscience. Concomitant advances in connectomics and artificial intelligence open fundamentally new opportunities to understand how connection patterns shape computational capacity in biological brain networks. Reservoir computing is a versatile paradigm that uses high-dimensional, nonlinear dynamical systems to perform computations and approximate cognitive functions. Here we present conn2res: an open-source Python toolbox for implementing biological neural networks as artificial neural networks. conn2res is modular, allowing arbitrary network architecture and dynamics to be imposed. The toolbox allows researchers to input connectomes reconstructed using multiple techniques, from tract tracing to noninvasive diffusion imaging, and to impose multiple dynamical systems, from spiking neurons to memristive dynamics. The versatility of the conn2res toolbox allows us to ask new questions at the confluence of neuroscience and artificial intelligence. By reconceptualizing function as computation, conn2res sets the stage for a more mechanistic understanding of structure-function relationships in brain networks.

Numerical investigation of a graphene-on-semiconductor device for optical monitoring of cell electrophysiology

Spatially resolved sensing devices for electrostatic potentials are extremely useful for characterization of living cells, however, many current techniques lack the speed necessary to capture spatially resolved, functional information of cells in real-time. Here, an optical sensing technique is proposed based on graphene on a semiconductor stack operating in the near-infrared spectrum. By modeling coherent interference of multiply reflected beam paths within the semiconductor stack, we demonstrate how the device produces a continuous reflectivity change in response to graphene Fermi energy which is ideal for sensing changes in local electrostatic fields produced by action potentials of living cells. By coupling the device with a high-speed camera, we propose this platform will allow for high-speed imaging of action potentials over a large sensing area with micron scale resolution.

Development of Specialized Microelectrode Arrays with Local Electroporation Functionality

When a cell or tissue is exposed to a pulsed electric field (100-1000 V/cm), the cellular membrane permeabilizes for biomolecules that cannot pass an intact cellular membrane. During this electropermeabilization (EP), plasmid deoxyribonucleic acid sequences encoding therapeutic or regulatory genes can enter the cell, which is called gene electrotransfer (GET). GET using micro-/nano technology provides higher spatial resolution and operates with lower voltage amplitudes compared to conventional bulk EP. Microelectrode arrays (MEAs), which are usually used for the recording and stimulation of neuronal signals, can be utilized for GET as well. In this study, we developed a specialized MEA for local EP of adherent cells. Our manufacturing process provides a most flexible electrode and substrate material selection. We used electrochemical impedance spectroscopy to characterize the impedance of the MEAs and the impact of an adherent cellular layer. We verified the local EP functionality of the MEAs by loading a fluorophore dye into human embryonic kidney 293T cells. Finally, we demonstrated a GET with a subsequent green fluorescent protein expression by the cells. Our experiments prove that a high spatial resolution of GET can be obtained using MEAs.

Recent Advancements in Graphene-Based Implantable Electrodes for Neural Recording/Stimulation

Implantable electrodes represent a groundbreaking advancement in nervous system research, providing a pivotal tool for recording and stimulating human neural activity. This capability is integral for unraveling the intricacies of the nervous system's functionality and for devising innovative treatments for various neurological disorders. Implantable electrodes offer distinct advantages compared to conventional recording and stimulating neural activity methods. They deliver heightened precision, fewer associated side effects, and the ability to gather data from diverse neural sources. Crucially, the development of implantable electrodes necessitates key attributes: flexibility, stability, and high resolution. Graphene emerges as a highly promising material for fabricating such electrodes due to its exceptional properties. It boasts remarkable flexibility, ensuring seamless integration with the complex and contoured surfaces of neural tissues. Additionally, graphene exhibits low electrical resistance, enabling efficient transmission of neural signals. Its transparency further extends its utility, facilitating compatibility with various imaging techniques and optogenetics. This paper showcases noteworthy endeavors in utilizing graphene in its pure form and as composites to create and deploy implantable devices tailored for neural recordings and stimulations. It underscores the potential for significant advancements in this field. Furthermore, this paper delves into prospective avenues for refining existing graphene-based electrodes, enhancing their suitability for neural recording applications in in vitro and in vivo settings. These future steps promise to revolutionize further our capacity to understand and interact with the neural research landscape.

Driving electrochemical reactions at the microscale using CMOS microelectrode arrays

Precise control of pH values at electrode interfaces enables the systematic investigation of pH-dependent processes by electrochemical means. In this work, we employed high-density complementary metal-oxide-semiconductor (CMOS) microelectrode arrays (MEAs) as miniaturized systems to induce and confine electrochemical reactions in areas corresponding to the pitch of single electrodes (17.5 μm). First, we present a strategy for generating localized pH patterns on the surface of the CMOS MEA with unprecedented spatial resolution. Leveraging the versatile routing capabilities of the switch matrix beneath the CMOS MEA, we created arbitrary combinations of anodic and cathodic electrodes and hence pH patterns. Moreover, we utilized the system to produce polymeric surface patterns by additive and subtractive methods. For additive patterning, we controlled the in situ formation of polydopamine at the microelectrode surface through oxidation of free dopamine above a threshold pH > 8.5. For subtractive patterning, we removed cell-adhesive poly-L-lysine from the electrode surface and backfilled the voids with antifouling polymers. Such polymers were chosen to provide a proof-of-concept application of controlling neuronal growth via electrochemically-induced patterns on the CMOS MEA surface. Importantly, our platform is compatible with commercially available high-density MEAs and requires no custom equipment, rendering the findings generalizable and accessible.

Investigation of the input-output relationship of engineered neural networks using high-density microelectrode arrays

Bottom-up neuroscience utilizes small, engineered biological neural networks to study neuronal activity in systems of reduced complexity. We present a platform that establishes up to six independent networks formed by primary rat neurons on planar complementary metal-oxide-semiconductor (CMOS) microelectrode arrays (MEAs). We introduce an approach that allows repetitive stimulation and recording of network activity at any of the over 700 electrodes underlying a network. We demonstrate that the continuous application of a repetitive super-threshold stimulus yields a reproducible network answer within a 15 ms post-stimulus window. This response can be tracked with high spatiotemporal resolution across the whole extent of the network. Moreover, we show that the location of the stimulation plays a significant role in the networks' early response to the stimulus. By applying a stimulation pattern to all network-underlying electrodes in sequence, the sensitivity of the whole network to the stimulus can be visualized. We demonstrate that microchannels reduce the voltage stimulation threshold and induce the strongest network response. By varying the stimulation amplitude and frequency we reveal discrete network transition points. Finally, we introduce vector fields to follow stimulation-induced spike propagation pathways within the network. Overall we show that our defined neural networks on CMOS MEAs enable us to elicit highly reproducible activity patterns that can be precisely modulated by stimulation amplitude, stimulation frequency and the site of stimulation.

Validation of transparent and flexible neural implants for simultaneous electrophysiology, functional imaging, and optogenetics

The combination of electrophysiology and neuroimaging methods allows the simultaneous measurement of electrical activity signals with calcium dynamics from single neurons to neuronal networks across distinct brain regions in vivo. While traditional electrophysiological techniques are limited by photo-induced artefacts and optical occlusion for neuroimaging, different types of transparent neural implants have been proposed to resolve these issues. However, reproducing proposed solutions is often challenging and it remains unclear which approach offers the best properties for long-term chronic multimodal recordings. We therefore created a streamlined fabrication process to produce, and directly compare, two types of transparent surface micro-electrocorticography (μECoG) implants: nano-mesh gold structures (m-μECoGs) versus a combination of solid gold interconnects and PEDOT:PSS-based electrodes (pp-μECoGs). Both implants allowed simultaneous multimodal recordings but pp-μECoGs offered the best overall electrical, electrochemical, and optical properties with negligible photo-induced artefacts to light wavelengths of interest. Showing functional chronic stability for up to four months, pp-μECoGs also allowed the simultaneous functional mapping of electrical and calcium neural signals upon visual and tactile stimuli during widefield imaging. Moreover, recordings during two-photon imaging showed no visible signal attenuation and enabled the correlation of network dynamics across brain regions to individual neurons located directly below the transparent electrical contacts.

Verification of the seizure liability of compounds based on their in vitro functional activity in cultured rat cortical neurons and co-cultured human iPSC-derived neurons with astrocytes and in vivo extrapolation to cerebrospinal fluid concentration

Methodical screening of safe and efficient drug candidate compounds is crucial for drug development. A high-throughput and accurate compound evaluation method targeting the central nervous system can be developed using in vitro neural networks. In particular, an evaluation system based on a human-derived neural network that can act as an alternative to animal experiments is desirable to avoid interspecific differences. A microelectrode array (MEA) is one such evaluation system, and can measure in vitro neural activity; however, studies on compound evaluation criteria and in vitro to in vivo extrapolation are scarce. In this study, we identified the parameters that can eliminate the effects of solvents from neural activity data obtained using MEA allow for accurate compound evaluation. Additionally, we resolved the issue associated with compound evaluation criteria during MEA using principal component analysis by considering the neuronal activity exceeding standard deviation (SD) of the solvent as indicator of seizurogenic potential. Overall, 10 seizurogenic compounds and three negative controls were assessed using MEA-based co-cultured human-induced pluripotent stem cell-derived neurons and astrocytes, and primary rat cortical neurons. In addition, we determined rat cerebrospinal fluid (CSF) concentrations during tremor and convulsion in response to exposure to test compounds. To characterize the in vitro to in vivo extrapolation and species differences, we compared the concentrations at which neuronal activity exceeding the SD range of the solvent was detectable using the MEA system and rat CSF concentration.

Combining PEDOT:PSS Polymer Coating with Metallic 3D Nanowires Electrodes to Achieve High Electrochemical Performances for Neuronal Interfacing Applications

This study presents a novel approach to improve the performance of microelectrode arrays (MEAs) used for electrophysiological studies of neuronal networks. The integration of 3D nanowires (NWs) with MEAs increases the surface-to-volume ratio, which enables subcellular interactions and high-resolution neuronal signal recording. However, these devices suffer from high initial interface impedance and limited charge transfer capacity due to their small effective area. To overcome these limitations, the integration of conductive polymer coatings, poly(3,4-ethylenedioxythiophene)-poly(styrenesulfonate) (PEDOT:PSS) is investigated as a mean of improving the charge transfer capacity and biocompatibility of MEAs. The study combines platinum silicide-based metallic 3D nanowires electrodes with electrodeposited PEDOT:PSS coatings to deposit ultra-thin (<50 nm) layers of conductive polymer onto metallic electrodes with very high selectivity. The polymer-coated electrodes were fully characterized electrochemically and morphologically to establish a direct relationship between synthesis conditions, morphology, and conductive features. Results show that PEDOT-coated electrodes exhibit thickness-dependent improved stimulation and recording performances, offering new perspectives for neuronal interfacing with optimal cell engulfment to enable the study of neuronal activity with acute spatial and signal resolution at the sub-cellular level.

Simultaneous Presentation of Dexamethasone and Nerve Growth Factor via Layered Carbon Nanotubes and Polypyrrole to Interface Neural Cells

The implantation of neural electrodes usually induces acute and chronic inflammation, which can result in the formation of glial scars encapsulating the implanted electrodes and the loss of neurons near the active electrode sites. Local presentation of anti-inflammatory drugs or neural protective factors has been evidenced as an effective strategy to modulate inflammatory responses and promote electrode-neuron integration. Here, a novel delivery system for the simultaneous presentation of both anti-inflammatory drugs (dexamethasone, Dex) and nerve-growth-promoting factors (nerve growth factor, NGF) from the electrode sites was developed via layer-structured carbon nanotubes and conductive polymers. The modified electrodes exhibited higher charge storage capacitance and lower electrochemical impedance compared to unmodified electrodes and electrodes coated with polypyrrole/Dex. Dex released from the functional coating under controlled electrochemical stimulation was able to inhibit the lipopolysaccharide-induced secretion or mRNA transcription of inflammatory cytokines, including nitric oxide, TNF-α, and IL-6 in RAW264.7 cells, and control the activation of cultured astrocytes. In addition, the functional coatings did not show a toxic effect on PC12 cells and primary neural cells but exhibited promoted activities on the adhesion, growth, and neurite extension of neural cells.

Bioadhesive polymer semiconductors and transistors for intimate biointerfaces

The use of bioelectronic devices relies on direct contact with soft biotissues. For transistor-type bioelectronic devices, the semiconductors that need to have direct interfacing with biotissues for effective signal transduction do not adhere well with wet tissues, thereby limiting the stability and conformability at the interface. We report a bioadhesive polymer semiconductor through a double-network structure formed by a bioadhesive brush polymer and a redox-active semiconducting polymer. The resulting semiconducting film can form rapid and strong adhesion with wet tissue surfaces together with high charge-carrier mobility of ~1 square centimeter per volt per second, high stretchability, and good biocompatibility. Further fabrication of a fully bioadhesive transistor sensor enabled us to produce high-quality and stable electrophysiological recordings on an isolated rat heart and in vivo rat muscles.

Protruding cantilever microelectrode array to monitor the inner electrical activity of cerebral organoids

Stem cell-derived cerebral organoids are artificially grown miniature organ-like structures mimicking embryonic brain architecture. They are composed of multiple neural cell types with 3D cell layer organization exhibiting local field potential. Measuring the extracellular electrical activity by means of conventional planar microelectrode arrays is particularly challenging due to the 3D architecture of organoids. In order to monitor the intra-organoid electrical activity of thick spheroid-shaped samples, we developed long protruding microelectrode arrays able to penetrate the inner regions of cerebral organoids to measure the local potential of neurons within the organoids. A new microfabrication process has been developed which, thanks to the relaxation of internal stresses of a stack of materials deposited over a sacrificial layer, allows one to build a protruding cantilever microelectrode array placed at the apex of beams which rise vertically, over two hundred microns. These slender beams inserted deeply into the organoids give access to the recording of local field potential from neurons buried inside the organoid. This novel device shall provide valuable tools to study neural functions in greater detail.

Revealing Low Amplitude Signals of Neuroendocrine Cells through Disordered Silicon Nanowires-Based Microelectrode Array

Today, the key methodology to study in vitro or in vivo electrical activity in a population of electrogenic cells, under physiological or pathological conditions, is by using microelectrode array (MEA). While significant efforts have been devoted to develop nanostructured MEAs for improving the electrophysiological investigation in neurons and cardiomyocytes, data on the recording of the electrical activity from neuroendocrine cells with MEA technology are scarce owing to their weaker electrical signals. Disordered silicon nanowires (SiNWs) for developing a MEA that, combined with a customized acquisition board, successfully capture the electrical signals generated by the corticotrope AtT-20 cells as a function of the extracellular calcium (Ca2+ ) concentration are reported. The recorded signals show a shape that clearly resembles the action potential waveform by suggesting a natural membrane penetration of the SiNWs. Additionally, the generation of synchronous signals observed under high Ca2+ content indicates the occurrence of a collective behavior in the AtT-20 cell population. This study extends the usefulness of MEA technology to the investigation of the electrical communication in cells of the pituitary gland, crucial in controlling several essential human functions, and provides new perspectives in recording with MEA the electrical activity of excitable cells.

Aerosol Jet-Printed High-Aspect Ratio Micro-Needle Electrode Arrays Applied for Human Cerebral Organoids and 3D Neurospheroid Networks

The human brain is a complex and poorly accessible organ. Thus, new tools are required for studying the neural function in a controllable environment that preserves multicellular interaction and neuronal wiring. In particular, high-throughput methods that alleviate the need for animal experiments are essential for future studies. Recent developments of induced pluripotent stem cell technologies have enabled in vitro modeling of the human brain by creating three-dimensional brain tissue mimic structures. To leverage these new technologies, a systematic and versatile approach for evaluating neuronal activity at larger tissue depths within the regime of tens to hundreds of micrometers is required. Here, we present an aerosol-jet- and inkjet-printing-based method to fabricate microelectrode arrays, equipped with high-aspect ratio μ-needle electrodes that penetrate 3D neural network assemblies. The arrays have been successfully applied for electrophysiological recordings on interconnected neurospheroids formed on an engineered substrate and on cerebral organoids, both derived from human induced pluripotent stem cells.

The Use of Intraoperative Neuromonitoring for Cervical Spine Surgery: Indications, Challenges, and Advances

Intraoperative neuromonitoring (IONM) has become an indispensable surgical adjunct in cervical spine procedures to minimize surgical complications. Understanding the historical development of IONM, indications for use, associated pitfalls, and recent developments will allow the surgeon to better utilize this important technology. While IONM has shown great promise in procedures for cervical deformity, intradural tumors, or myelopathy, routine use in all cervical spine cases with moderate pathology remains controversial. Pitfalls that need to be addressed include human error, a lack of efficient communication, variable alarm warning criteria, and a non-standardized checklist protocol. As the techniques associated with IONM technology become more robust moving forward, IONM emerges as a crucial solution to updating patient safety protocols.

Cultured Vagal Afferent Neurons as Sensors for Intestinal Effector Molecules

The gut-brain axis embodies the bi-directional communication between the gastrointestinal tract and the central nervous system (CNS), where vagal afferent neurons (VANs) serve as sensors for a variety of gut-derived signals. The gut is colonized by a large and diverse population of microorganisms that communicate via small (effector) molecules, which also act on the VAN terminals situated in the gut viscera and consequently influence many CNS processes. However, the convoluted in vivo environment makes it difficult to study the causative impact of the effector molecules on VAN activation or desensitization. Here, we report on a VAN culture and its proof-of-principle demonstration as a cell-based sensor to monitor the influence of gastrointestinal effector molecules on neuronal behavior. We initially compared the effect of surface coatings (poly-L-lysine vs. Matrigel) and culture media composition (serum vs. growth factor supplement) on neurite growth as a surrogate of VAN regeneration following tissue harvesting, where the Matrigel coating, but not the media composition, played a significant role in the increased neurite growth. We then used both live-cell calcium imaging and extracellular electrophysiological recordings to show that the VANs responded to classical effector molecules of endogenous and exogenous origin (cholecystokinin serotonin and capsaicin) in a complex fashion. We expect this study to enable platforms for screening various effector molecules and their influence on VAN activity, assessed by their information-rich electrophysiological fingerprints.

An organ-on-chip device with integrated charge sensors and recording microelectrodes

Continuous monitoring of tissue microphysiology is a key enabling feature of the organ-on-chip (OoC) approach for in vitro drug screening and disease modeling. Integrated sensing units are particularly convenient for microenvironmental monitoring. However, sensitive in vitro and real-time measurements are challenging due to the inherently small size of OoC devices, the characteristics of commonly used materials, and external hardware setups required to support the sensing units. Here we propose a silicon-polymer hybrid OoC device that encompasses transparency and biocompatibility of polymers at the sensing area, and has the inherently superior electrical characteristics and ability to house active electronics of silicon. This multi-modal device includes two sensing units. The first unit consists of a floating-gate field-effect transistor (FG-FET), which is used to monitor changes in pH in the sensing area. The threshold voltage of the FG-FET is regulated by a capacitively-coupled gate and by the changes in charge concentration in close proximity to the extension of the floating gate, which functions as the sensing electrode. The second unit uses the extension of the FG as microelectrode, in order to monitor the action potential of electrically active cells. The layout of the chip and its packaging are compatible with multi-electrode array measurement setups, which are commonly used in electrophysiology labs. The multi-functional sensing is demonstrated by monitoring the growth of induced pluripotent stem cell-derived cortical neurons. Our multi-modal sensor is a milestone in combined monitoring of different, physiologically-relevant parameters on the same device for future OoC platforms.

Large-Area Field Potential Imaging Having Single Neuron Resolution Using 236 880 Electrodes CMOS-MEA Technology

The electrophysiological technology having a high spatiotemporal resolution at the single-cell level and noninvasive measurements of large areas provide insights on underlying neuronal function. Here, a complementary metal-oxide semiconductor (CMOS)-microelectrode array (MEA) is used that uses 236 880 electrodes each with an electrode size of 11.22 × 11.22 µm and 236 880 covering a wide area of 5.5 × 5.9 mm in presenting a detailed and single-cell-level neural activity analysis platform for brain slices, human iPS cell-derived cortical networks, peripheral neurons, and human brain organoids. Propagation pattern characteristics between brain regions changes the synaptic propagation into compounds based on single-cell time-series patterns, classification based on single DRG neuron firing patterns and compound responses, axonal conduction characteristics and changes to anticancer drugs, and network activities and transition to compounds in brain organoids are extracted. This detailed analysis of neural activity at the single-cell level using the CMOS-MEA provides a new understanding of the basic mechanisms of brain circuits in vitro and ex vivo, on human neurological diseases for drug discovery, and compound toxicity assessment.

Fast Reconfigurable Electrode Array Based on Titanium Oxide for Localized Stimulation of Cultured Neural Network

Planar microelectrode arrays have become standard tools for in vitro neural-network analysis. However, these predefined micropatterned devices lack adaptability to target-specific cells within a cultured network. Herein, we fabricated a reconfigurable TiO₂ electrode array with an anatase-brookite bicrystalline polymorphous mesoporous layer. Because of its selective absorption of ultraviolet (UV) light and corresponding photoconductivity, TiO₂ electrode array was identified as a promising tool for high-resolution light-addressing. The TiO₂ film was used as a semitransparent semiconductor with a high R_off/R_on ratio of 10⁵ and a fast response time of 400 ms. In addition, the effect of UV radiation on the resistance of the TiO₂ film over 30 d in an aqueous environment was analyzed, with the film exhibiting high stability. An arbitrary UV pattern was applied to a reconfigurable TiO₂ electrode using a digital micromirror device (DMD), affording highly localized neural stimulation at the single-cell level. The reconfigurable TiO₂ electrode with a patterned indium tin oxide (ITO) substrate enabled the independent connection of up to 60 points with external stimulators and signal recorders. We believe this technique would be helpful for electrophysiological research requiring the analysis of cell and neural-network features using a highly localized neural interface.