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Introduction: The human brain is an intricate structure composed of interconnected modular networks, whose organization is known to balance the principles of segregation and integration, enabling rapid information exchange and the generation of coherent brain states. Segregation involves the specialization of brain regions for specific tasks, while integration facilitates communication among these regions, allowing for efficient information flow. Several factors influence this balance, including maturation, aging, and the insurgence of neurological disorders like epilepsy, stroke, or cancer. To gain insights into information processing and connectivity recovery, we devised a controllable in vitro model to mimic and investigate the effects of different segregation and integration ratios over time. Methods: We designed a cross-shaped polymeric mask to initially establish four independent sub-populations of cortical neurons and analyzed how the timing of its removal affected network development. We evaluated the morphological and functional features of the networks from 11 to 18 days in vitro (DIVs) with immunofluorescence techniques and micro-electrode arrays (MEAs). Results: The removal of the mask at different developmental stages of the network lead to strong variations in the degree of intercommunication among the four assemblies (altering the segregation/integration balance), impacting firing and bursting parameters. Early removal (after 5 DIVs) resulted in networks with a level of integration similar to homogeneous controls (without physical constraints). In contrast, late removal (after 15 DIVs) hindered the formation of strong inter-compartment connectivity, leading to more clustered and segregated assemblies. Discussion: A critical balance between segregation and integration was observed when the mask was removed at DIV 10, allowing for the formation of a strong connectivity among the still-separated compartments, thus demonstrating the existence of a time window in network development in which it is possible to achieve a balance between segregation and integration. [ABSTRACT FROM AUTHOR]

IntroductionThe human brain is an intricate structure composed of interconnected modular networks, whose organization is known to balance the principles of segregation and integration, enabling rapid information exchange and the generation of coherent brain states. Segregation involves the specialization of brain regions for specific tasks, while integration facilitates communication among these regions, allowing for efficient information flow. Several factors influence this balance, including maturation, aging, and the insurgence of neurological disorders like epilepsy, stroke, or cancer. To gain insights into information processing and connectivity recovery, we devised a controllable in vitro model to mimic and investigate the effects of different segregation and integration ratios over time.MethodsWe designed a cross-shaped polymeric mask to initially establish four independent sub-populations of cortical neurons and analyzed how the timing of its removal affected network development. We evaluated the morphological and functional features of the networks from 11 to 18 days in vitro (DIVs) with immunofluorescence techniques and micro-electrode arrays (MEAs).ResultsThe removal of the mask at different developmental stages of the network lead to strong variations in the degree of intercommunication among the four assemblies (altering the segregation/integration balance), impacting firing and bursting parameters. Early removal (after 5 DIVs) resulted in networks with a level of integration similar to homogeneous controls (without physical constraints). In contrast, late removal (after 15 DIVs) hindered the formation of strong inter-compartment connectivity, leading to more clustered and segregated assemblies.DiscussionA critical balance between segregation and integration was observed when the mask was removed at DIV 10, allowing for the formation of a strong connectivity among the still-separated compartments, thus demonstrating the existence of a time window in network development in which it is possible to achieve a balance between segregation and integration.

Abstract Background Acquired brain injuries, such as stroke, are a major cause of long-term disability worldwide. Intracortical microstimulation (ICMS) can be used successfully to assist in guiding appropriate connections to restore lost sensorimotor integration. Activity-Dependent Stimulation (ADS) is a specific type of closed-loop ICMS that aims at coupling the activity of two different brain regions by stimulating one in response to activity in the other. Recently, ADS was used to effectively promote behavioral recovery in rodent models following a unilateral traumatic brain injury in the primary motor cortex. While behavioral benefits have been described, the neurophysiological changes in spared areas in response to this type of stimulation have not been fully characterized. Here we explored how single-unit spiking activity is impacted by a focal ischemic lesion and, subsequently, by an ADS treatment. Methods Intracortical microelectrode arrays were implanted in the ipsilesional rostral forelimb area (RFA) to record spike activity and to trigger intracortical microstimulation in the primary somatosensory area (S1) of anaesthetized Long Evans rats. An ischemic injury was induced in the caudal forelimb area through microinjections of Endothelin-1. Activity from both RFA and S1 was recorded and analyzed off-line by evaluating possible changes, either induced by the lesion in the Control group or by stimulation in the ADS group. Results We found that the ischemic lesion in the motor area led to an overall increase in spike activity within RFA and a decrease in S1 with respect to the baseline condition. Subsequent treatment with ADS increased the firing rate in both RFA and S1. Post-stimulation spiking activity was significantly higher compared to pre-stimulation activity in the ADS animals versus non-stimulated controls. Moreover, stimulation promoted the generation of highly synchronized bursting patterns in both RFA and S1 only in the ADS group. Conclusions This study describes the impact on single-unit activity in ipsilesional areas immediately following a cortical infarct and demonstrates that application of ADS is effective in altering this activity.

Activity dependent stimulation (ADS) is a closed loop stimulation technique whose neurophysiological effects have not been deeply investigated. Here we explored how Local field Potentials (LFP) are impacted by a focal ischemic lesion and, subsequently, by ADS treatment. Intracortical microelectrode arrays were implanted in the rostral forelimb area (RFA) and in the primary somatosensory area (S1) of anaesthetized rats. An ischemic injury was induced in the caudal forelimb area through microinjections of Endothelin-1. The lesion induced an acute depressive trend in LFP power in RFA (evaluated in 6 bands of interest: Delta (1–4Hz), Theta (4–8Hz), Alpha (8-11Hz), Beta (11–30Hz), LowGamma (30–55Hz) and HighGamma (55-80)) followed by a noticeable significant rebound in both areas. Applying ADS induced an overall decrease of power. The lesion impacted the connectivity in a frequency specific manner, resulting in widespread increase in connectivity in Delta both between and within areas. Two hours after the lesion, without stimulation, correlated activity between areas increased in Beta and Gamma. After stimulation, inter-area connectivity increased in Delta, Theta and Alpha, while considerably dropping within RFA in highGamma. By computing phase-amplitude coupling, we found that the lesion produced an incremental increase in the coupling between (Theta) Alpha phase and (lowGamma) highGamma amplitude within RFA, while S1 had a more generalized increase. Likewise, coupling between Theta phase and lowGamma/highGamma amplitudes increased between areas after lesion. ADS induced a similar increase, but greater in magnitude both within and between RFA and S1. These results have important implications on the emerging field of closed-loop adaptive stimulation promoting ADS as an innovative tool for the treatment of neurological disorders.

The delivery of electrical stimuli is crucial to shape the electrophysiological activity of neuronal populations and to appreciate the response of the different brain circuits involved. In the present work, we used dissociated cortical and hippocampal networks coupled to Micro-Electrode Arrays (MEAs) to investigate the features of their evoked response when a low-frequency (0.2 Hz) electrical stimulation protocol is delivered. In particular, cortical and hippocampal neurons were topologically organized to recreate interconnected sub-populations with a polydimethylsiloxane (PDMS) mask, which guaranteed the segregation of the cell bodies and the connections among the sub-regions through microchannels. We found that cortical assemblies were more reactive than hippocampal ones. Despite both configurations exhibiting a fast (<35 ms) response, this did not uniformly distribute over the MEA in the hippocampal networks. Moreover, the propagation of the stimuli-evoked activity within the networks showed a late (35–500 ms) response only in the cortical assemblies. The achieved results suggest the importance of the neuronal target when electrical stimulation experiments are performed. Not all neuronal types display the same response, and in light of transferring stimulation protocols to in vivo applications, it becomes fundamental to design realistic in vitro brain-on-a-chip devices to investigate the dynamical properties of complex neuronal circuits. [ABSTRACT FROM AUTHOR]

Activity dependent stimulation (ADS) is a closed loop stimulation technique whose neurophysiological effects have not been deeply investigated. Here we explored how Local field Potentials (LFP) are impacted by a focal ischemic lesion and, subsequently, by ADS treatment. Intracortical microelectrode arrays were implanted in the rostral forelimb area (RFA) and in the primary somatosensory area (S1) of anaesthetized rats. An ischemic injury was induced in the caudal forelimb area through microinjections of Endothelin-1. The lesion induced an acute depressive trend in LFP power in RFA (evaluated in 6 bands of interest: Delta (1–4Hz), Theta (4–8Hz), Alpha (8-11Hz), Beta (11–30Hz), LowGamma (30–55Hz) and HighGamma (55-80)) followed by a noticeable significant rebound in both areas. Applying ADS induced an overall decrease of power. The lesion impacted the connectivity in a frequency specific manner, resulting in widespread increase in connectivity in Delta both between and within areas. Two hours after the lesion, without stimulation, correlated activity between areas increased in Beta and Gamma. After stimulation, inter-area connectivity increased in Delta, Theta and Alpha, while considerably dropping within RFA in highGamma. By computing phase-amplitude coupling, we found that the lesion produced an incremental increase in the coupling between (Theta) Alpha phase and (lowGamma) highGamma amplitude within RFA, while S1 had a more generalized increase. Likewise, coupling between Theta phase and lowGamma/highGamma amplitudes increased between areas after lesion. ADS induced a similar increase, but greater in magnitude both within and between RFA and S1. These results have important implications on the emerging field of closed-loop adaptive stimulation promoting ADS as an innovative tool for the treatment of neurological disorders. [ABSTRACT FROM AUTHOR]

Self-organized criticality theory proved that information transmission and computational performances of neural networks are optimal in critical state. By using recordings of the spontaneous activity originated by dissociated neuronal assemblies coupled to Micro-Electrode Arrays (MEAs), we tested this hypothesis using Approximate Entropy (ApEn) as a measure of complexity and information transfer. We analysed 60 min of electrophysiological activity of three neuronal cultures exhibiting either sub-critical, critical or super-critical behaviour. The firing patterns on each electrode was studied in terms of the inter-spike interval (ISI), whose complexity was quantified using ApEn. We assessed that in critical state the local complexity (measured in terms of ApEn) is larger than in sub- and super-critical conditions (mean ± std, ApEn about 0.93 ± 0.09, 0.66 ± 0.18, 0.49 ± 0.27, for the cultures in critical, sub-critical and super-critical state, respectively—differences statistically significant). Our estimations were stable when considering epochs as short as 5 min (pairwise cross-correlation of spatial distribution of mean ApEn of 94 ± 5%). These preliminary results indicate that ApEn has the potential of being a reliable and stable index to monitor local information transmission in a neuronal network during maturation. Thus, ApEn applied on ISI time series appears to be potentially useful to reflect the overall complex behaviour of the neural network, even monitoring a single specific location. [ABSTRACT FROM AUTHOR]

The delivery of electrical stimuli is crucial to shape the electrophysiological activity of neuronal populations and to appreciate the response of the different brain circuits involved. In the present work, we used dissociated cortical and hippocampal networks coupled to Micro-Electrode Arrays (MEAs) to investigate the features of their evoked response when a low-frequency (0.2 Hz) electrical stimulation protocol is delivered. In particular, cortical and hippocampal neurons were topologically organized to recreate interconnected sub-populations with a polydimethylsiloxane (PDMS) mask, which guaranteed the segregation of the cell bodies and the connections among the sub-regions through microchannels. We found that cortical assemblies were more reactive than hippocampal ones. Despite both configurations exhibiting a fast (

Nicotinic acetylcholine receptors (nAChRs) are known to play a role in cognitive functions of the hippocampus, such as memory consolidation. Given that they conduct Ca2+ and are capable of regulating the release of glutamate and γ‐aminobutyric acid (GABA) within the hippocampus, thereby shifting the excitatory‐inhibitory ratio, we hypothesized that the activation of nAChRs will result in the potentiation of hippocampal networks and alter synchronization. We used nicotine as a tool to investigate the impact of activation of nAChRs on neuronal network dynamics in primary embryonic rat hippocampal cultures prepared from timed‐pregnant Sprague‐Dawley rats. We perturbed cultured hippocampal networks with increasing concentrations of bath‐applied nicotine and performed network extracellular recordings of action potentials using a microelectrode array. We found that nicotine modulated network dynamics in a concentration‐dependent manner; it enhanced firing of action potentials as well as facilitated bursting activity. In addition, we used pharmacological agents to determine the contributions of discrete nAChR subtypes to the observed network dynamics. We found that β4‐containing nAChRs are necessary for the observed increases in spiking, bursting, and synchrony, while the activation of α7 nAChRs augments nicotine‐mediated network potentiation but is not necessary for its manifestation. We also observed that antagonists of N‐methyl‐D‐aspartate receptors (NMDARs) and group I metabotropic glutamate receptors (mGluRs) partially blocked the effects of nicotine. Furthermore, nicotine exposure promoted autophosphorylation of Ca2+/calmodulin‐dependent kinase II (CaMKII) and serine 831 phosphorylation of the α‐amino‐3‐hydroxy‐5‐methyl‐4‐isoxazolepropionic acid receptor (AMPAR) subunit GluA1. These results suggest that nicotinic receptors induce potentiation and synchronization of hippocampal networks and glutamatergic synaptic transmission. Findings from this work highlight the impact of cholinergic signaling in generating network‐wide potentiation in the form of enhanced spiking and bursting dynamics that coincide with molecular correlates of memory such as increased phosphorylation of CaMKII and GluA1. Open science badges: This article has received a badge for *Open Materials* because it provided all relevant information to reproduce the study in the manuscript. More information about the Open Practices badges can be found at https://cos.io/our-services/open-science-badges/ [ABSTRACT FROM AUTHOR]

On-line and real-time analysis of micro-organ activity permits to use the endogenous analytical power of cellular signal transduction algorithms as biosensors. We have developed here such a sensor using only a few pancreatic endocrine islets and the avoidance of transgenes or chemical probes reduces bias and procures general usage. Nutrient and hormone-induced changes in islet ion fluxes through channels provide the first integrative read-out of micro-organ activity. Using extracellular electrodes we captured this read-out non-invasively as slow potentials which reflect glucose concentration-dependent (3–15 mM) micro-organ activation and coupling. Custom-made PDMS-based microfluidics with platinum black micro-electrode arrays required only some tens of islets and functioned at flow rates of 1–10 µl/min which are compatible with microdialysis. We developed hardware solutions for on-line real-time analysis on a reconfigurable Field-Programmable Gate Array (FPGA) that offered resource-efficient architecture and storage of intermediary processing stages. Moreover, real-time adaptive and reconfigurable algorithms accounted for signal disparities and noise distribution. Based on islet slow potentials, this integrated set-up allowed within less than 40 μs the discrimination and precise automatic ranking of small increases (2 mM steps) of glucose concentrations in real time and within the physiological glucose range. This approach shall permit further development in continuous monitoring of the demand for insulin in type 1 diabetes as well as monitoring of organs-on-chip or maturation of stem-cell derived islets. [ABSTRACT FROM AUTHOR]

Severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2) caused a large-scale global pandemic between 2020 and 2022. Despite efforts to understand its biological and pathogenic mechanisms, the viral impact on the neurological systems remains unclear. The main goal of this study was to quantify the neurological phenotypes induced by the SARS-CoV-2 spike protein in neurons, as measured by in-vitro multiwell micro-electrode arrays (MEAs)., Materials and Methods: The authors extracted the whole-brain neurons from the newborn P1 mice and plated them on multiwell MEAs and administered purified recombinant spike proteins (both S1 and S2 subunits) from the SARS-CoV-2 virus. The signals from the MEAs were transmitted from an amplifier to a high-performance computer for recording and analysis using an in-house developed algorithm to quantify neuronal phenotypes., Results: Primary among the phenotypic features analyzed, we discovered that neuronal treatment with spike 1 protein (S1) protein from SARS-CoV-2 decreased the mean burst numbers observed on each electrode, an effect that could be rescued with an anti-S1 antibody. Conversely, this mean burst number decrease was not observed with spike 2 protein (S2) treatment. Finally, our data strongly suggest that the receptor binding domain of S1 is responsible for the reduction in neuronal burst activity., Conclusion: Overall, our results strongly indicate that spike proteins may play an important role in altering neuronal phenotypes, specifically the burst patterns, when neurons are exposed during early development., Competing Interests: The authors declare no conflicts of interest., (Copyright © 2023 The Author(s). Published by Wolters Kluwer Health, Inc.)

Nowadays, the use of in vitro reduced models of neuronal networks to investigate the interplay between structural-functional connectivity and the emerging collective dynamics is a widely accepted approach. In this respect, a relevant advance for this kind of studies has been given by the recent introduction of high-density large-scale Micro-Electrode Arrays (MEAs) which have favored the mapping of functional connections and the recordings of the neuronal electrical activity. Although several toolboxes have been implemented to characterize network dynamics and derive functional links, no specifically dedicated software for the management of huge amount of data and direct estimation of functional connectivity maps has been developed. TOOLCONNECT offers the implementation of up to date algorithms and a user-friendly Graphical User Interface (GUI) to analyze recorded data from large scale networks. It has been specifically conceived as a computationally efficient open-source software tailored to infer functional connectivity by analyzing the spike trains acquired from in vitro networks coupled to MEAs. In the current version, TOOLCONNECT implements correlation- (cross-correlation, partial-correlation) and information theory (joint entropy, transfer entropy) based core algorithms, as well as useful and practical add-ons to visualize functional connectivity graphs and extract some topological features. In this work, we present the software, its main features and capabilities together with some demonstrative applications on hippocampal recordings.

Complex network topologies represent the necessary substrate to support complex brain functions. In this work, we reviewed in vitro neuronal networks coupled to Micro-Electrode Arrays (MEAs) as biological substrate. Networks of dissociated neurons developing in vitro and coupled to MEAs, represent a valid experimental model for studying the mechanisms governing the formation, organization and conservation of neuronal cell assemblies. In this review, we present some examples of the use of statistical Cluster Coefficients and Small World indices to infer topological rules underlying the dynamics exhibited by homogeneous and engineered neuronal networks.

Nowadays, the use of in vitro reduced models of neuronal networks to investigate the interplay between structural-functional connectivity and the emerging collective dynamics is a widely accepted approach. In this respect, a relevant advance for this kind of studies has been given by the recent introduction of high-density large-scale Micro-Electrode Arrays (MEAs) which have favored the mapping of functional connections and the recordings of the neuronal electrical activity. Although, several toolboxes have been implemented to characterize network dynamics and derive functional links, no specifically dedicated software for the management of huge amount of data and direct estimation of functional connectivity maps has been developed. TOOLCONNECT offers the implementation of up to date algorithms and a user-friendly Graphical User Interface (GUI) to analyze recorded data from large scale networks. It has been specifically conceived as a computationally efficient open-source software tailored to infer functional connectivity by analyzing the spike trains acquired from in vitro networks coupled to MEAs. In the current version, TOOLCONNECT implements correlation- (cross-correlation, partial-correlation) and information theory (joint entropy, transfer entropy) based core algorithms, as well as useful and practical add-ons to visualize functional connectivity graphs and extract some topological features. In this work, we present the software, its main features and capabilities together with some demonstrative applications on hippocampal recordings. [ABSTRACT FROM AUTHOR]

Complex network topologies represent the necessary substrate to support complex brain functions. In this work, we reviewed in vitro neuronal networks coupled to Micro-Electrode Arrays (MEAs) as biological substrate. Networks of dissociated neurons developing in vitro and coupled to MEAs, represent a valid experimental model for studying the mechanisms governing the formation, organization and conservation of neuronal cell assemblies. In this review, we present some examples of the use of statistical Cluster Coefficients and SmallWorld indices to infer topological rules underlying the dynamics exhibited by homogeneous and engineered neuronal networks. [ABSTRACT FROM AUTHOR]

Advantages and disadvantages of voltammetric vs. potentiometric sensing of dopamine are discussed. The study is focused on the measurements in small sample volumes, rather than on the selectivity to dopamine. For the potentiometric sensing, a novel flow-through tubular unit is developed. For voltammetric measurements with bare gold and platinum electrodes, miniature cylinder cells with the volume of 200 μl are developed. The CV and impedance data suggest that the dopamine diffusion to the electrode surface is the limiting stage of the whole electrode process which hinders measurements without stirring. It is shown that use of micro electrode arrays allows overpassing this limitation. [ABSTRACT FROM AUTHOR]

Background: A large number of invertebrate models, including the snail Helix, emerged as particularly suitable tools for investigating the formation of synapses and the specificity of neuronal connectivity. Helix neurons can be individually identified and isolated in cell culture, showing well-conserved size, position, biophysical properties, synaptic connections, and physiological functions. Although we previously showed the potential usefulness of Helix polysynaptic circuits, a full characterization of synaptic connectivity and its dynamics during network development has not been performed. Results: In this paper, we systematically investigated the in vitro formation of polysynaptic circuits, among Helix B2 and the serotonergic C1 neurons, from a morphological and functional point of view. Since these cells are generally silent in culture, networks were chemically stimulated with either high extracellular potassium concentrations or, alternatively, serotonin. Potassium induced a transient depolarization of all neurons. On the other hand, we found prolonged firing activity, selectively maintained following the first serotonin application. Statistical analysis revealed no significant changes in neuronal dynamics during network development. Moreover, we demonstrated that the cell-selective effect of serotonin was also responsible for short-lasting alterations in C1 excitability, without long-term rebounds. Estimation of the functional connections by means of cross-correlation analysis revealed that networks under elevated KCl concentrations exhibited strongly correlated signals with short latencies (about 5 ms), typical of electrically coupled cells. Conversely, neurons treated with serotonin were weakly connected with longer latencies (exceeding 20 ms) between the interacting neurons. Finally, we clearly demonstrated that these two types of correlations (in terms of strength/latency) were effectively related to the presence of electrical or chemical connections, by comparing Micro- Electrode Array (MEA) signal traces with intracellularly recorded cell pairs. Conclusions: Networks treated with either potassium or serotonin were predominantly interconnected through electrical or chemical connections, respectively. Furthermore, B2 response and short-term increase in C1 excitability induced by serotonin is sufficient to trigger spontaneous activity with chemical connections, an important requisite for long-term maintenance of firing activity. [ABSTRACT FROM AUTHOR]

Abstract: In this article, a comprehensive overview of the most recent developments in the field of stripping voltammetry at regular micro-interfaces (both solid–liquid and liquid–liquid interfaces) is presented. This review will report on the most conventional arrays of metallic micro-electrodes but also on the rapidly growing field of electrochemistry at arrays of micro-interfaces between two immiscible electrolyte solutions (μITIES). The main fabrication methods, together with some design considerations and diffusion phenomena at such interfaces are discussed. Main applications of micro-interface arrays are presented including heavy metals detection at micro-electrode arrays and detection of organic molecules (amino acids, vitamins, peptides and drugs) at the μITIES. Stripping analysis at micro-interface arrays is suitable for the detection of analytes in several real media including water, soil extracts and biological fluids (blood and saliva) with high specificity, sensitivity (detection limits of nM, ppb level) and reliability. Stripping analysis at μITIES and micro-electrode arrays are two complementary approaches that have the advantages of being cost effective, simple to use and easily adaptable to field measurement. [Copyright &y& Elsevier]

In this paper we present a new experimental set-up which combines the surface characterization capabilities of atomic force microscopy at the sub-micrometer scale with non-invasive electrophysiological measurements obtained by using planar micro-electrode arrays. In order to show the potential of the combined measurements we studied the changes in cell topography and elastic properties of cardiac muscle cells as during the contraction-relaxation cycle. The onset of each beating cycle was precisely identified by the use of the extracellular potential signal, allowing us to combine nanomechanical measurements from multiple cardiomyocyte contractions in order to analyze the time-dependent variation of cell morphology and elasticity. Moreover, by estimating the elastic modulus at different indentation depths in a single location on the cell membrane, we observed a dynamic mechanical behavior that could be related to the underlying myofibrillar structure dynamics. [ABSTRACT FROM AUTHOR]

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Dissociated networks of neurons typically exhibit bursting behavior, whose features are strongly influenced by the age of the culture, by chemical/electrical stimulation or by environmental conditions. To help the experimenter in identifying the changes possibly induced by specific protocols, we developed a self-adapting method for detecting both bursts and network bursts from electrophysiological activity recorded by means of micro-electrode arrays. The algorithm is based on the computation of the logarithmic inter-spike interval histogram and automatically detects the best threshold to distinguish between inter- and intra-burst inter-spike intervals for each recording channel of the array. An analogous procedure is followed for the detection of network bursts, looking for sequences of closely spaced single-channel bursts. We tested our algorithm on recordings of spontaneous as well as chemically stimulated activity, comparing its performance to other methods available in the literature. [ABSTRACT FROM AUTHOR]

Abstract: This paper reports the design and the experimental results of a fully integrated, low-noise, low-power standard CMOS preamplifier circuit used to record the extracellular electrophysiological activity of in vitro biological neuronal cultures. Our goal is to use the preamplifier in a fully integrated, multi-channel, bi-directional neuro-electronic interface. Among others, two main requirements must be addressed when designing such kind of integrated recording systems: noise performance and very low frequency disturbance rejection. These two requirements need to be satisfied together with a small silicon area design, to be able to integrate a large number of recording channels (i.e. up to thousands) onto a single die. A prototype preamplifier circuit has been designed and implemented; in this paper we report the experimental results. While satisfying the above requirements, our circuit offers state-of-the-art smallest area occupation (0.13mm2) and consumes 4.5μW. Sub-threshold-biased lateral pnp transistors, used to implement very high resistance value integrated resistors, have been characterized to determine the resistance spread. The fabricated prototype, coupled with a commercial Micro-Electrode Array (MEA), has been successfully employed to record the extracellular electrophysiological spontaneous activity, both of muscular cardiac cells (cardiomyocytes) and of spinal cord neurons from murines. [Copyright &y& Elsevier]

Abstract: The spike represents the fundamental bit of information transmitted by the neurons within a network in order to communicate. Then, given the importance of the spike rate as well as the spike time for coding the activity generated at the level of a cell assembly, a relevant issue in extracellular electrophysiology is the correct identification of the spike in multisite recordings from brain areas or neuronal networks. In this paper, we present a novel spike detection algorithm, named Precise Timing Spike Detection (PTSD), aimed at (i) reducing the number of false positives and false negatives, in order to optimize the rate code, and (ii) improving the time precision of the identified spike, in order to optimize the spike timing. The PTSD algorithm considers consecutive portions of the signal and looks for the Relative Maximum/Minimum whose peak-to-peak amplitude is above a defined differential threshold and responds to specific requirements. To validate the algorithm, the presented spike detection has been compared with other methods either commercially available or proposed in the literature by using two benchmarking procedures: (i) visual inspection by a group of experts of a portion of signal recorded from a rat cortical culture and (ii) detection of the spikes generated by a realistic neuronal network model. In both cases our algorithm produced the best performances in terms of efficiency and precision. The ROC curve analysis further proved that the best results are reached by the application of the PTSD. [Copyright &y& Elsevier]

Abstract: Impedimetric analysis on adherently growing cells by micro-electrodes provides information related to cell number, cell adhesion and cellular morphology. In this study, cell-based biosensor with micro-electrode arrays (MEAs) was used to monitor the culture behavior of mammalian cancer cells and evaluate the chemosensitivity of anti-cancer drugs using electrochemical impedance spectroscopy. The platinum electrode arrays were fabricated by semiconductor technology to a 10×10 pattern, with diameter of 80μm of each electrode. The human oesophageal cancer cell lines (KYSE 30) were cultured on the surface of the electrodes with the pre-coated fibronectin, the connecting protein for tumor cells metastasis and adhesion in extracellular matrix. Morphology changes during cells adhesion, spreading, and proliferation can be detected by impedimetric analysis in a real time and non-invasive way. Cisplatin was added to cells for potential drug screening applications. The experimental results show that this well-known anti-cancer drug has characteristic chemosensitivity effects on KYSE 30 cells which can be detected by MEA. Thus, this cell-based chip provides a useful analytical method for cancer research. [Copyright &y& Elsevier]

Abstract: Dissociated cortical neurons from rat embryos cultured onto micro-electrode arrays exhibit characteristic patterns of electrophysiological activity, ranging from isolated spikes in the first days of development to highly synchronized bursts after 3–4 weeks in vitro. In this work we analyzed these features by considering the approach proposed by the self-organized criticality theory: we found that networks of dissociated cortical neurons also generate spontaneous events of spreading activity, previously observed in cortical slices, in the form of neuronal avalanches. Choosing an appropriate time scale of observation to detect such neuronal avalanches, we studied the dynamics by considering the spontaneous activity during acute recordings in mature cultures and following the development of the network. We observed different behaviors, i.e. sub-critical, critical or super-critical distributions of avalanche sizes and durations, depending on both the age and the development of cultures. In order to clarify this variability, neuronal avalanches were correlated with other statistical parameters describing the global activity of the network. Criticality was found in correspondence to medium synchronization among bursts and high ratio between bursting and spiking activity. Then, the action of specific drugs affecting global bursting dynamics (i.e. acetylcholine and bicuculline) was investigated to confirm the correlation between criticality and regulated balance between synchronization and variability in the bursting activity. Finally, a computational model of neuronal network was developed in order to interpret the experimental results and understand which parameters (e.g. connectivity, excitability) influence the distribution of avalanches. In summary, cortical neurons preserve their capability to self-organize in an effective network even when dissociated and cultured in vitro. The distribution of avalanche features seems to be critical in those cultures displaying medium synchronization among bursts and poor random spiking activity, as confirmed by chemical manipulation experiments and modeling studies. [Copyright &y& Elsevier]

Abstract: We report on an experiment in which a population of rat cortical neurons, cultured on a micro-electrode array, was connected bi-directionally to a mobile robot. Bi-directional communication between a neural population and an external device requires to translate time-varying signals into spatio-temporal patterns of neural activity, and back. Here, we describe the experimental setup and the computational modules of the neural interface, and work on characterization of the ‘transfer function’ of the neural preparation, as it emerges from closed-loop experiments, and selection of stimulation and recording sites which are best compatible with a desired behavior. [Copyright &y& Elsevier]

Abstract: This report describes the development of novel sonochemically fabricated, bioengineered acetylcholinesterase and polyaniline carbon/cobalt phthalocyanine biosensors for the ultra-sensitive determination of a number of different pesticides. Arrays of this type typically have population micro-electrode densities of up to ∼2×105cm-2; these represent the highest micro-electrode population densities reported to date by any fabrication means. The enzymatic response of the sensors is inhibited upon incubation with the pesticide, and we have shown that Dichlorvos, Parathion and Azinphos may be determined down to concentrations of ∼1×10-17M, ∼1×10-16M and ∼1×10-16M, respectively. These lower limits of detection are lower than otherwise achievable by any other analytical approach. Measurements were performed within a custom built flow injection system that operates at a constant flow of 1mlmin-1. Sensor stability studies were also performed whereby a stabiliser mixture of sucrose and polygalacturonic acid was added to the immobilised enzyme matrix at the working electrode and left to dry. Sixty-five percent of the initial enzyme activity was found to remain after a period of 92 days to allow storage of these electrodes and facilitating transportation if required. [Copyright &y& Elsevier]

In vitro cultured neurons form a bi-dimensional physical model of the brain. In spite of their simplified level of organization, they provide a useful framework to study information processing in the nervous system. NeuroBIT is an EU-funded project, aimed at developing algorithms and techniques that allow for establishing a bi-directional connection between cultured neurons and external devices (e.g., robots). The main purpose is to enable ‘embodied’ in vitro experiments, in which neural populations are provided with an actual physical body. Embodiment is likely to be crucial in studying the mechanisms of sensorimotor integration, control and adaptation in living systems. Here we present the general objectives of the project, and show the results of preliminary experiments and simulations. [Copyright &y& Elsevier]

The brain is a complex organ composed of billions of neurons connected through excitatory and inhibitory synapses. Its structure reveals a modular topological organization, where neurons are arranged in interconnected assemblies. The generated patterns of electrophysiological activity are shaped by two main factors: network heterogeneity and the topological properties of the underlying connectivity that strongly push the dynamics toward different brain-states. In this work, we exploited an innovative polymeric structure coupled to Micro-Electrode Arrays (MEAs) to recreate in vitro heterogeneous interconnected (modular) neuronal networks made up of cortical and hippocampal neurons. We investigated the propagation of spike sequences between the two interconnected subpopulations during the networks' development, correlating functional and structural connectivity to dynamics. The simultaneous presence of two neuronal types shaped the features of the functional connections (excitation vs. inhibition), orchestrating the emerging patterns of electrophysiological activity. In particular, we found that hippocampal neurons mostly project inhibitory connections toward the cortical counterpart modulating the temporal scale of the population events (network bursts). In contrast, cortical neurons establish a larger amount of intrapopulation connections. Moreover, we proved topological properties such as small-worldness, degree distribution, and modularity of neuronal assemblies were favored by the physical environment where networks developed and matured., (© The Author(s) 2021. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permission@oup.com.)

Mitochondrial encephalomyopathy, lactic acidosis, and stroke-like episodes (MELAS) is often caused by an adenine to guanine variant at m.3243 (m.3243A>G) of the MT-TL1 gene. To understand how this pathogenic variant affects the nervous system, we differentiated human induced pluripotent stem cells (iPSCs) into excitatory neurons with normal (low heteroplasmy) and impaired (high heteroplasmy) mitochondrial function from MELAS patients with the m.3243A>G pathogenic variant. We combined micro-electrode array (MEA) measurements with RNA sequencing (MEA-seq) and found reduced expression of genes involved in mitochondrial respiration and presynaptic function, as well as non-cell autonomous processes in co-cultured astrocytes. Finally, we show that the clinical phase II drug sonlicromanol can improve neuronal network activity when treatment is initiated early in development. This was intricately linked with changes in the neuronal transcriptome. Overall, we provide insight in transcriptomic changes in iPSC-derived neurons with high m.3243A>G heteroplasmy, and show the pathology is partially reversible by sonlicromanol., (Copyright © 2021 The Authors. Published by Elsevier Inc. All rights reserved.)

Micro-electrode arrays (MEAs) are increasingly used to characterize neuronal network activity of human induced pluripotent stem cell (hiPSC)-derived neurons. Despite their gain in popularity, MEA recordings from hiPSC-derived neuronal networks are not always used to their full potential in respect to experimental design, execution, and data analysis. Therefore, we benchmarked the robustness of MEA-derived neuronal activity patterns from ten healthy individual control lines, and uncover comparable network phenotypes. To achieve standardization, we provide recommendations on experimental design and analysis. With such standardization, MEAs can be used as a reliable platform to distinguish (disease-specific) network phenotypes. In conclusion, we show that MEAs are a powerful and robust tool to uncover functional neuronal network phenotypes from hiPSC-derived neuronal networks, and provide an important resource to advance the hiPSC field toward the use of MEAs for disease phenotyping and drug discovery., (Copyright © 2021 The Authors. Published by Elsevier Inc. All rights reserved.)

Pathogenic mutations in either one of the epigenetic modifiers EHMT1 , MBD5 , MLL3 , or SMARCB1 have been identified to be causative for Kleefstra syndrome spectrum (KSS), a neurodevelopmental disorder with clinical features of both intellectual disability (ID) and autism spectrum disorder (ASD). To understand how these variants lead to the phenotypic convergence in KSS, we employ a loss-of-function approach to assess neuronal network development at the molecular, single-cell, and network activity level. KSS-gene-deficient neuronal networks all develop into hyperactive networks with altered network organization and excitatory-inhibitory balance. Interestingly, even though transcriptional data reveal distinct regulatory mechanisms, KSS target genes share similar functions in regulating neuronal excitability and synaptic function, several of which are associated with ID and ASD. Our results show that KSS genes mainly converge at the level of neuronal network communication, providing insights into the pathophysiology of KSS and phenotypically congruent disorders. • KSS gene deficiency leads to hyperactive neuronal network functioning • EHMT1-deficient neurons show altered excitatory-inhibitory balance • KSS gene deficiency leads to increased neuronal excitability • KSS target genes converge on neuronal excitability and synaptic function regulation Frega et al. show that mutations in functionally distinct genes leading to Kleefstra syndrome converge at the molecular, cellular, and neuronal network levels. KSS gene deficiency leads to hyperactive neuronal network communication and altered excitatory-inhibitory balance. Common biological pathways related to ion-channel expression and synaptic communication underlie this functional convergence. [ABSTRACT FROM AUTHOR]