Exact distinction of excitatory and inhibitory neurons in neural networks: a study with GFP-GAD67 neurons optically and electrophysiologically recognized on multielectrode arrays

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.

Neuronal functional connectivity is impaired in a layer dependent manner near chronically implanted intracortical microelectrodes in C57BL6 wildtype mice

Objective.This study aims to reveal longitudinal changes in functional network connectivity within and across different brain structures near chronically implanted microelectrodes. While it is well established that the foreign-body response (FBR) contributes to the gradual decline of the signals recorded from brain implants over time, how the FBR affects the functional stability of neural circuits near implanted brain-computer interfaces (BCIs) remains unknown. This research aims to illuminate how the chronic FBR can alter local neural circuit function and the implications for BCI decoders.Approach.This study utilized single-shank, 16-channel,100µm site-spacing Michigan-style microelectrodes (3 mm length, 703µm2 site area) that span all cortical layers and the hippocampal CA1 region. Sex balanced C57BL6 wildtype mice (11-13 weeks old) received perpendicularly implanted microelectrode in left primary visual cortex. Electrophysiological recordings were performed during both spontaneous activity and visual sensory stimulation. Alterations in neuronal activity near the microelectrode were tested assessing cross-frequency synchronization of local field potential (LFP) and spike entrainment to LFP oscillatory activity throughout 16 weeks after microelectrode implantation.Main results. The study found that cortical layer 4, the input-receiving layer, maintained activity over the implantation time. However, layers 2/3 rapidly experienced severe impairment, leading to a loss of proper intralaminar connectivity in the downstream output layers 5/6. Furthermore, the impairment of interlaminar connectivity near the microelectrode was unidirectional, showing decreased connectivity from Layers 2/3 to Layers 5/6 but not the reverse direction. In the hippocampus, CA1 neurons gradually became unable to properly entrain to the surrounding LFP oscillations.Significance. This study provides a detailed characterization of network connectivity dysfunction over long-term microelectrode implantation periods. This new knowledge could contribute to the development of targeted therapeutic strategies aimed at improving the health of the tissue surrounding brain implants and potentially inform engineering of adaptive decoders as the FBR progresses. Our study's understanding of the dynamic changes in the functional network over time opens the door to developing interventions for improving the long-term stability and performance of intracortical microelectrodes.

Optimal decoding of neural dynamics occurs at mesoscale spatial and temporal resolutions

Introduction

Understanding the neural code has been one of the central aims of neuroscience research for decades. Spikes are commonly referred to as the units of information transfer, but multi-unit activity (MUA) recordings are routinely analyzed in aggregate forms such as binned spike counts, peri-stimulus time histograms, firing rates, or population codes. Various forms of averaging also occur in the brain, from the spatial averaging of spikes within dendritic trees to their temporal averaging through synaptic dynamics. However, how these forms of averaging are related to each other or to the spatial and temporal units of information representation within the neural code has remained poorly understood.

Materials and methods

In this work we developed NeuroPixelHD, a symbolic hyperdimensional model of MUA, and used it to decode the spatial location and identity of static images shown to n = 9 mice in the Allen Institute Visual Coding-NeuroPixels dataset from large-scale MUA recordings. We parametrically varied the spatial and temporal resolutions of the MUA data provided to the model, and compared its resulting decoding accuracy.

Results

For almost all subjects, we found 125ms temporal resolution to maximize decoding accuracy for both the spatial location of Gabor patches (81 classes for patches presented over a 9×9 grid) as well as the identity of natural images (118 classes corresponding to 118 images) across the whole brain. This optimal temporal resolution nevertheless varied greatly between different regions, followed a sensory-associate hierarchy, and was significantly modulated by the central frequency of theta-band oscillations across different regions. Spatially, the optimal resolution was at either of two mesoscale levels for almost all mice: the area level, where the spiking activity of all neurons within each brain area are combined, and the population level, where neuronal spikes within each area are combined across fast spiking (putatively inhibitory) and regular spiking (putatively excitatory) neurons, respectively. We also observed an expected interplay between optimal spatial and temporal resolutions, whereby increasing the amount of averaging across one dimension (space or time) decreases the amount of averaging that is optimal across the other dimension, and vice versa.

Discussion

Our findings corroborate existing empirical practices of spatiotemporal binning and averaging in MUA data analysis, and provide a rigorous computational framework for optimizing the level of such aggregations. Our findings can also synthesize these empirical practices with existing knowledge of the various sources of biological averaging in the brain into a new theory of neural information processing in which the unit of information varies dynamically based on neuronal signal and noise correlations across space and time.

Neuronal functional connectivity is impaired in a layer dependent manner near the chronically implanted microelectrodes

Objective

This study aims to reveal longitudinal changes in functional network connectivity within and across different brain structures near the chronically implanted microelectrode. While it is well established that the foreign-body response (FBR) contributes to the gradual decline of the signals recorded from brain implants over time, how does the FBR impact affect the functional stability of neural circuits near implanted Brain-Computer Interfaces (BCIs) remains unknown. This research aims to illuminate how the chronic FBR can alter local neural circuit function and the implications for BCI decoders.

Approach

This study utilized multisite Michigan-style microelectrodes that span all cortical layers and the hippocampal CA1 region to collect spontaneous and visually-evoked electrophysiological activity. Alterations in neuronal activity near the microelectrode were tested assessing cross-frequency synchronization of LFP and spike entrainment to LFP oscillatory activity throughout 16 weeks after microelectrode implantation.

Main Results

The study found that cortical layer 4, the input-receiving layer, maintained activity over the implantation time. However, layers 2/3 rapidly experienced severe impairment, leading to a loss of proper intralaminar connectivity in the downstream output layers 5/6. Furthermore, the impairment of interlaminar connectivity near the microelectrode was unidirectional, showing decreased connectivity from Layers 2/3 to Layers 5/6 but not the reverse direction. In the hippocampus, CA1 neurons gradually became unable to properly entrain to the surrounding LFP oscillations.

Significance

This study provides a detailed characterization of network connectivity dysfunction over long-term microelectrode implantation periods. This new knowledge could contribute to the development of targeted therapeutic strategies aimed at improving the health of the tissue surrounding brain implants and potentially inform engineering of adaptive decoders as the FBR progresses. Our study's understanding of the dynamic changes in the functional network over time opens the door to developing interventions for improving the long-term stability and performance of intracortical microelectrodes.

Transcranial Ultrasound Stimulation of the Anterior Cingulate Cortex Reduces Neuropathic Pain in Mice

Focused ultrasound (FUS) is a potential tool for treating chronic pain by modulating the central nervous system. Herein, we aimed to determine whether transcranial FUS stimulation of the anterior cingulate cortex (ACC) effectively improved chronic pain in the chronic compress injury mice model at different stages of neuropathic pain. The mechanical threshold of pain was recorded in the nociceptive tests. We found FUS stimulation elevated the mechanical threshold of pain in both short-term (p < 0.01) and long-term (p < 0.05) experiments. Furthermore, we determined protein expression differences in ACC between the control group, the intervention group, and the Sham group to analyze the underlying mechanism of FUS stimulation in improving neuropathic pain. Additionally, the results showed FUS stimulation led to alterations in differential proteins in long-term experiments, including cellular processes, cellular signaling, and information storage and processing. Our findings indicate FUS may effectively alleviate mechanical neuropathic pain via the ACC's stimulation, especially in the chronic state.

MEA-ToolBox: an Open Source Toolbox for Standardized Analysis of Multi-Electrode Array Data

Functional assessment of in vitro neuronal networks-of relevance for disease modelling and drug testing-can be performed using multi-electrode array (MEA) technology. However, the handling and processing of the large amount of data typically generated in MEA experiments remains a huge hurdle for researchers. Various software packages have been developed to tackle this issue, but to date, most are either not accessible through the links provided by the authors or only tackle parts of the analysis. Here, we present ''MEA-ToolBox'', a free open-source general MEA analytical toolbox that uses a variety of literature-based algorithms to process the data, detect spikes from raw recordings, and extract information at both the single-channel and array-wide network level. MEA-ToolBox extracts information about spike trains, burst-related analysis and connectivity metrics without the need of manual intervention. MEA-ToolBox is tailored for comparing different sets of measurements and will analyze data from multiple recorded files placed in the same folder sequentially, thus considerably streamlining the analysis pipeline. MEA-ToolBox is available with a graphic user interface (GUI) thus eliminating the need for any coding expertise while offering functionality to inspect, explore and post-process the data. As proof-of-concept, MEA-ToolBox was tested on earlier-published MEA recordings from neuronal networks derived from human induced pluripotent stem cells (hiPSCs) obtained from healthy subjects and patients with neurodevelopmental disorders. Neuronal networks derived from patient's hiPSCs showed a clear phenotype compared to those from healthy subjects, demonstrating that the toolbox could extract useful parameters and assess differences between normal and diseased profiles.

The Flow of Axonal Information Among Hippocampal Subregions: 1. Feed-Forward and Feedback Network Spatial Dynamics Underpinning Emergent Information Processing

The tri-synaptic pathway in the mammalian hippocampus enables cognitive learning and memory. Despite decades of reports on anatomy and physiology, the functional architecture of the hippocampal network remains poorly understood in terms of the dynamics of axonal information transfer between subregions. Information inputs largely flow from the entorhinal cortex (EC) to the dentate gyrus (DG), and then are processed further in the CA3 and CA1 before returning to the EC. Here, we reconstructed elements of the rat hippocampus in a novel device over an electrode array that allowed for monitoring the directionality of individual axons between the subregions. The direction of spike propagation was determined by the transmission delay of the axons recorded between two electrodes in microfluidic tunnels. The majority of axons from the EC to the DG operated in the feed-forward direction, with other regions developing unexpectedly large proportions of feedback axons to balance excitation. Spike timing in axons between each region followed single exponential log-log distributions over two orders of magnitude from 0.01 to 1 s, indicating that conventional descriptors of mean firing rates are misleading assumptions. Most of the spiking occurred in bursts that required two exponentials to fit the distribution of inter-burst intervals. This suggested the presence of up-states and down-states in every region, with the least up-states in the DG to CA3 feed-forward axons and the CA3 subregion. The peaks of the log-normal distributions of intra-burst spike rates were similar in axons between regions with modes around 95 Hz distributed over an order of magnitude. Burst durations were also log-normally distributed around a peak of 88 ms over two orders of magnitude. Despite the diversity of these spike distributions, spike rates from individual axons were often linearly correlated to subregions. These linear relationships enabled the generation of structural connectivity graphs, not possible previously without the directional flow of axonal information. The rich axonal spike dynamics between subregions of the hippocampus reveal both constraints and broad emergent dynamics of hippocampal architecture. Knowledge of this network architecture may enable more efficient computational artificial intelligence (AI) networks, neuromorphic hardware, and stimulation and decoding from cognitive implants.

Impaired flickering of the permeability transition pore causes SPG7 spastic paraplegia

Background

Mutations of the mitochondrial protein paraplegin cause hereditary spastic paraplegia type 7 (SPG7), a so-far untreatable degenerative disease of the upper motoneuron with still undefined pathomechanism.

The intermittent mitochondrial permeability transition pore (mPTP) opening, called flickering, is an essential process that operates to maintain mitochondrial homeostasis by reducing intra-matrix Ca²⁺ and reactive oxygen species (ROS) concentration, and is critical for efficient synaptic function.

Methods

We use a fluorescence-based approach to measure mPTP flickering in living cells and biochemical and molecular biology techniques to dissect the pathogenic mechanism of SPG7. In the SPG7 animal model we evaluate the potential improvement of the motor defect, neuroinflammation and neurodegeneration by means of an mPTP inducer, the benzodiazepine Bz-423.

Findings

We demonstrate that paraplegin is required for efficient transient opening of the mPTP, that is impaired in both SPG7 patients-derived fibroblasts and primary neurons from Spg7^−/− mice. We show that dysregulation of mPTP opening at the pre-synaptic terminal impairs neurotransmitter release leading to ineffective synaptic transmission. Lack of paraplegin impairs mPTP flickering by a mechanism involving increased expression and activity of sirtuin3, which promotes deacetylation of cyclophilin D, thus hampering mPTP opening. Pharmacological treatment with Bz-423, which bypasses the activity of CypD, normalizes synaptic transmission and rescues the motor impairment of the SPG7 mouse model.

Interpretation

mPTP targeting opens a new avenue for the potential therapy of this form of spastic paraplegia.

Funding

Telethon Foundation grant (TGMGCSBX16TT); Dept. of Defense, US Army, grant W81XWH-18–1–0001

Low-Impedance 3D PEDOT:PSS Ultramicroelectrodes

The technology for producing microelectrode arrays (MEAs) has been developing since the 1970s and extracellular electrophysiological recordings have become well established in neuroscience, drug screening and cardiology. MEAs allow monitoring of long-term spiking activity of large ensembles of excitable cells noninvasively with high temporal resolution and mapping its spatial features. However, their inability to register subthreshold potentials, such as intrinsic membrane oscillations and synaptic potentials, has inspired a number of laboratories to search for alternatives to bypass the restrictions and/or increase the sensitivity of microelectrodes. In this study, we present the fabrication and in vitro experimental validation of arrays of PEDOT:PSS-coated 3D ultramicroelectrodes, with the best-reported combination of small size and low electrochemical impedance. We observed that this type of microelectrode does not alter neuronal network biological properties, improves the signal quality of extracellular recordings and exhibits higher selectivity toward single unit recordings. With fabrication processes simpler than those reported in the literature for similar electrodes, our technology is a promising tool for study of neuronal networks.

Niosomal Formulation of a Lipoyl-Carnosine Derivative Targeting TRPA1 Channels in Brain

The transient receptor potential akyrin type-1 (TRPA1) is a non-selective cation channel playing a pivotal role in pain sensation and neurogenic inflammation. TRPA1 channels expressed in the central nervous system (CNS) have a critical role in the modulation of cortical spreading depression (CSD), which is a key pathophysiological basis of migraine pain. ADM_09 is a recently developed lipoic acid-based TRPA1 antagonist that is able to revert oxaliplatin-induced neuropathic pain and inflammatory trigeminal allodynia. In this context, aiming at developing drugs that are able to target TRPA1 channels in the CNS and promote an antioxidant effect, permeability across the blood-brain barrier (BBB) represents a central issue. Niosomes are nanovesicles that can be functionalized with specific ligands selectively recognized by transporters expressed on the BBB. In this work, the activity of ADM_09 on neocortex cultures was studied, and an efficient formulation to cross the BBB was developed with the aim of increasing the concentration of ADM_09 into the brain and selectively delivering it to the CNS rapidly after parenteral administration.

Overexpression of cypin alters dendrite morphology, single neuron activity, and network properties via distinct mechanisms

OBJECTIVE

This study investigates the effect that overexpression of cytosolic PSD-95 interactor (cypin), a regulator of synaptic PSD-95 protein localization and a core regulator of dendrite branching, exerts on the electrical activity of rat hippocampal neurons and networks.

APPROACH

We cultured rat hippocampal neurons and used lipid-mediated transfection and lentiviral gene transfer to achieve high levels of cypin or cypin mutant (cypinΔPDZ; PSD-95 non-binding) expression cellularly and network-wide, respectively.

MAIN RESULTS

Our analysis revealed that although overexpression of cypin and cypinΔPDZ increase dendrite numbers and decrease spine density, cypin and cypinΔPDZ distinctly regulate neuronal activity. At the single cell level, cypin promotes decreases in bursting activity while cypinΔPDZ reduces sEPSC frequency and further decreases bursting compared to cypin. At the network level, by using the Fano factor as a measure of spike count variability, cypin overexpression results in an increase in variability of spike count, and this effect is abolished when cypin cannot bind PSD-95. This variability is also dependent on baseline activity levels and on mean spike rate over time. Finally, our spike sorting data show that overexpression of cypin results in a more complex distribution of spike waveforms and that binding to PSD-95 is essential for this complexity.

SIGNIFICANCE

Our data suggest that dendrite morphology does not play a major role in cypin action on electrical activity.

SpikeDeeptector: a deep-learning based method for detection of neural spiking activity

OBJECTIVE

In electrophysiology, microelectrodes are the primary source for recording neural data (single unit activity). These microelectrodes can be implanted individually or in the form of arrays containing dozens to hundreds of channels. Recordings of some channels contain neural activity, which are often contaminated with noise. Another fraction of channels does not record any neural data, but only noise. By noise, we mean physiological activities unrelated to spiking, including technical artifacts and neural activities of neurons that are too far away from the electrode to be usefully processed. For further analysis, an automatic identification and continuous tracking of channels containing neural data is of great significance for many applications, e.g. automated selection of neural channels during online and offline spike sorting. Automated spike detection and sorting is also critical for online decoding in brain-computer interface (BCI) applications, in which only simple threshold crossing events are often considered for feature extraction. To our knowledge, there is no method that can universally and automatically identify channels containing neural data. In this study, we aim to identify and track channels containing neural data from implanted electrodes, automatically and more importantly universally. By universally, we mean across different recording technologies, different subjects and different brain areas.

APPROACH

We propose a novel algorithm based on a new way of feature vector extraction and a deep learning method, which we call SpikeDeeptector. SpikeDeeptector considers a batch of waveforms to construct a single feature vector and enables contextual learning. The feature vectors are then fed to a deep learning method, which learns contextualized, temporal and spatial patterns, and classifies them as channels containing neural spike data or only noise.

MAIN RESULTS

We trained the model of SpikeDeeptector on data recorded from a single tetraplegic patient with two Utah arrays implanted in different areas of the brain. The trained model was then evaluated on data collected from six epileptic patients implanted with depth electrodes, unseen data from the tetraplegic patient and data from another tetraplegic patient implanted with two Utah arrays. The cumulative evaluation accuracy was 97.20% on 1.56 million hand labeled test inputs.

SIGNIFICANCE

The results demonstrate that SpikeDeeptector generalizes not only to the new data, but also to different brain areas, subjects, and electrode types not used for training.

CLINICAL TRIAL REGISTRATION NUMBER

The clinical trial registration number for patients implanted with the Utah array is NCT01849822. For the epilepsy patients, approval from the local ethics committee at the Ruhr-University Bochum, Germany, was obtained prior to implantation.

Differential responsivity of neurons in perirhinal cortex, lateral entorhinal cortex, and dentate gyrus during time-bridging learning

Many studies have focused on the function of hippocampal region CA1 as a critical site for associative memory, but much less is known about changes in the afferents to CA1. Here we report the activity of multiple single neurons from perirhinal and entorhinal cortex and from dentate gyrus during trace eyeblink conditioning as well as consolidated recall, and in pseudo-conditioned control rabbits. We also report an analysis of theta activity filtered from the local field potential (LFP). Our results show early associative changes in single-neuron firing rate as well as theta oscillations in lateral entorhinal cortex (EC) and dentate gyrus (DG), and increases in the number of responsive neurons in perirhinal cortex. In both EC and DG, a subset of neurons from conditioned animals exhibited an elevated baseline firing rate and large responses to the conditioned stimulus and trace period. A similar population of cells has been seen in DG and in medial, but not lateral, EC during spatial tasks, suggesting that lateral EC contains cells responsive to a temporal associative task. In contrast to recent studies in our laboratory that found significant CA1 contributions to long-term memory, the activity profiles of neurons within EC and DG were similar for conditioned and pseudoconditioned rabbits during post-consolidation sessions. Collectively these results demonstrate that individual subregions of medial temporal lobe differentially support new and remotely acquired memories. Neuron firing profiles were similar on training trials when conditioned responses were and were not exhibited, demonstrating that these temporal lobe regions represent the CS-US association and do not control the behavioral response. The analysis of theta activity revealed that theta power was modulated by the conditioning stimuli in both the conditioned and pseudoconditioned groups and that although both groups exhibited a resetting of phase to the corneal airpuff, only the conditioned group exhibited a resetting of phase to the whisker conditioned stimulus.

Reconstruction of Functional Connectivity from Multielectrode Recordings and Calcium Imaging

In the last two decades, increasing research efforts in neuroscience have been focused on determining both structural and functional connectivity of brain circuits, with the main goal of relating the wiring diagram of neuronal systems to their emerging properties, from the microscale to the macroscale. While combining multisite parallel recordings with structural circuits' reconstruction in vivo is still very challenging, the reductionist in vitro approach based on neuronal cultures offers lower technical difficulties and is much more stable under control conditions. In this chapter, we present different approaches to infer the connectivity of cultured neuronal networks using multielectrode array or calcium imaging recordings. We first formally introduce the used methods, and then we will describe into details how those methods were applied in case studies. Since multielectrode array and calcium imaging recordings provide distinct and complementary spatiotemporal features of neuronal activity, in this chapter we present the strategies implemented with the two different methodologies in distinct sections.

Electrophysiological Profiling of Neocortical Neural Subtypes: A Semi-Supervised Method Applied to in vivo Whole-Cell Patch-Clamp Data

A lot of efforts have been made to understand the structure and function of neocortical circuits. In fact, a promising way to understand the functions of cortical circuits is the classification of the neural types, based on their different properties. Recent studies focused on applying modern computational methods to classify neurons based on molecular, morphological, physiological, or mixed of these criteria. Although there are studies in the literature on in vitro/vivo extracellular or in vitro intracellular recordings, a study on the classification of neuronal types using in vivo whole-cell patch-clamp recordings is still lacking. We thus proposed a novel semi-supervised classification method based on waveform shape of neurons' spikes using in vivo whole-cell patch-clamp recordings. We, first, detected spike candidates. Then discriminative features were extracted from the time samples of the spikes using discrete cosine transform. We then extracted the center of clusters using fuzzy c-mean clustering and finally, the neurons were classified using the minimum distance classifier. We distinguished three types of neurons: excitatory pyramidal cells (Pyr) and two types of inhibitory neurons: GABAergic- parvalbumin positive (PV), and somatostatin positive (SST) non-pyramidal cells in layer II/III of the mice primary visual cortex. We used 10-fold cross validation in our study. The classification accuracy for PV, Pyr, and SST was 91.59 ± 1.69, 97.47 ± 0.67, and 89.06 ± 1.99, respectively. Overall, the algorithm correctly classified 92.67 ± 0.54% of the cells, confirming the relative robustness of the discriminant functions. The performance of the method was further assessed on in vitro recordings by using a pool of 50 neurons from Allen institute Cell Types Database (5 major subtypes of neurons: Pyr, PV, SST, 5HT3a, and vasoactive intestinal peptide (VIP) cells). Its overall accuracy was 84.13 ± 0.81% on this data set using cross validation framework. The proposed algorithm is thus a promising new tool in recognizing cell's type with high accuracy in laboratories using in vivo/vitro whole-cell patch-clamp recording technique. The developed programs and the entire dataset are available online to interested readers.

Dichotomous Dopaminergic Control of Ventral Pallidum Neurons

The ventral pallidum (VP) is crucially involved in reward processing. Dopaminergic afferents reach the VP from the ventral tegmental area (VTA). Recent in vivo studies suggest dopamine application increase the firing in the VP. However, little is known about the cellular effects of dopamine within the VP. We aimed to address this paucity of data using brain slices containing the VP and multi-electrode array recordings. Dopamine significantly affected firing in 86% of spontaneously active VP neurons. Among the affected neurons, 84% were excited, while 16% were inhibited. The selective D1-like receptor agonist SKF81297 also had modulatory effects on the majority of VP neurons, but its effects were universally excitatory. On the other hand, the D2-like receptor agonist quinpirole had modulatory effects on 87% of VP neurons studied. It caused significant inhibitory effects in 33% of the cases and excitatory effects in the remaining 67%. The effects of D1-like receptor activation were presynaptic as blocking synaptic transmission with low Ca²⁺ abolished the effects of SKF81297 application. Furthermore, SKF81297 effects were abolished by blocking ionotropic glutamate receptors, suggesting that D1-like receptors boost glutamate release, which in turn excites VP neurons through postsynaptic glutamate receptors. Effects caused by D2-like receptor activation were found to involve pre and postsynaptic mechanisms, as low Ca²⁺ abolished the excitatory effects of quinpirole but not the inhibitory ones. Increases in firing frequency (ff) to quinpirole application were abolished by a group 2/3 mGluR antagonist, suggesting that D2-like receptors cause presynaptic inhibition of glutamate release, resulting in reduced postsynaptic activation of inhibitory mGluRs. Conversely, the inhibitory effects of quinpirole persisted in low Ca²⁺ and therefore can be attributed to postsynaptic D2-like receptor activation. VP neurons excited by dopamine had shorter spike half-widths and are excited by D1-like receptors (presynaptically) and by D2-like receptors (postsynaptically). VP neurons inhibited by dopamine have longer spike half-widths and while D1-like receptor activation has a presynaptic excitatory influence on them, D2-like receptor activation has a postsynaptic inhibitory effect that prevails, on balance. These data provide novel insights into the cellular mechanisms by which dopamine controls information processing within the VP.

Network analysis of hippocampal neurons by microelectrode array in the presence of HIV-1 Tat and cocaine

HIV-associated neurocognitive disorders affecting greater than 30% of patients are caused by HIV-1 infection of the CNS, and in part, include neurotoxic effects of the viral transactivator of transcription, Tat protein. In addition to increasing the risk for becoming HIV infected, cocaine abuse enhances the neuropathogenic impacts of HIV-1. To investigate the outcome of Tat and cocaine interference in the hippocampal neuronal network, cross-rank-corrlation was employed to develop a systematic framework to assess hippocampal neurons behavior cultured on multielectrode arrays. Tat and cocaine differentially disturbed neuronal spiking rates, amplitude, synchronous activity, and oscillations within the hippocampal neuronal network via potentiation of inhibitory neurotransmission. The Tat-mediated impairment of neuronal spiking was reversible by removal of Tat, which restored neuronal activity. The presence of astrocytes co-cultured with neuronal networks diminished the effects of Tat and cocaine on neuron function suggesting a role for astrocytes in stabilizing neuronal behavior and increasing neuronal spontaneous activities such as bursting amplitude, frequency, and wave propagation rate. Taken together, our studies indicate that the HIV protein Tat and cocaine impair hippocampal neuronal network functioning and that the presence of astrocytes alleviates network dysfunction pointing to a newly discovered pathway through which ionic homeostasis is maintained by neuron-glial crosstalk in the CNS.

Technical feasibility study for production of tailored multielectrode arrays and patterning of arranged neuronal networks

In this manuscript, we first reveal a simple ultra violet laser lithographic method to design and produce plain tailored multielectrode arrays. Secondly, we use the same lithographic setup for surface patterning to enable controlled attachment of primary neuronal cells and help neurite guidance. For multielectrode array production, we used flat borosilicate glass directly structured with the laser lithography system. The multi layered electrode system consists of a layer of titanium coated with a layer of di-titanium nitride. Finally, these electrodes are covered with silicon nitride for insulation. The quality of the custom made multielectrode arrays was investigated by light microscopy, electron microscopy and X-ray diffraction. The performance was verified by the detection of action potentials of primary neurons. The electrical noise of the custom-made MEA was equal to commercially available multielectrode arrays. Additionally, we demonstrated that structured coating with poly lysine, obtained with the aid of the same lithographic system, could be used to attach and guide neurons to designed structures. The process of neuron attachment and neurite guidance was investigated by light microscopy and charged particle microscopy. Importantly, the utilization of the same lithographic system for MEA fabrication and poly lysine structuring will make it easy to align the architecture of the neuronal network to the arrangement of the MEA electrode.. In future studies, this will lead to multielectrode arrays, which are able to specifically attach neuronal cell bodies to their chemically defined electrodes and guide their neurites, gaining a controlled connectivity in the neuronal network. This type of multielectrode array would be able to precisely assign a signal to a certain neuron resulting in an efficient way for analyzing the maturation of the neuronal connectivity in small neuronal networks.

The antipsychotic drugs olanzapine and haloperidol modify network connectivity and spontaneous activity of neural networks in vitro

Impaired neural synchronization is a hallmark of psychotic conditions such as schizophrenia. It has been proposed that schizophrenia-related cognitive deficits are caused by an unbalance of reciprocal inhibitory and stimulatory signaling. This supposedly leads to decreased power of induced gamma oscillations during the performance of cognitive tasks. In light of this hypothesis an efficient antipsychotic treatment should modify the connectivity and synchronization of local neural circuits. To address this issue, we investigated a model of hippocampal neuronal networks in vitro. Inhibitory and excitatory innervation of GABAergic and glutamatergic neurons was quantified using immunocytochemical markers and an automated routine to estimate network connectivity. The first generation (FGA) and second generation (SGA) antipsychotic drugs haloperidol and olanzapine, respectively, differentially modified the density of synaptic inputs. Based on the observed synapse density modifications, we developed a computational model that reliably predicted distinct changes in network activity patterns. The results of computational modeling were confirmed by spontaneous network activity measurements using the multiple electrode array (MEA) technique. When the cultures were treated with olanzapine, overall activity and synchronization were increased, whereas haloperidol had the opposite effect. We conclude that FGAs and SGAs differentially affect the balance between inhibition and excitation in hippocampal networks.

Plant Polyphenols and Exendin-4 Prevent Hyperactivity and TNF-α Release in LPS-Treated In vitro Neuron/Astrocyte/Microglial Networks

Increasing evidence supports a decisive role for neuroinflammation in the neurodegenerative process of several central nervous system (CNS) disorders. Microglia are essential mediators of neuroinflammation and can regulate a broad spectrum of cellular responses by releasing reactive oxygen intermediates, nitric oxide, proteases, excitatory amino acids, and cytokines. We have recently shown that also in ex-vivo cortical networks of neurons, astrocytes and microglia, an increased level of tumor necrosis factor-alpha (TNF-α) was detected a few hours after exposure to the bacterial endotoxin lipopolysaccharide (LPS). Simultaneously, an atypical “seizure-like” neuronal network activity was recorded by multi-electrode array (MEA) electrophysiology. These effects were prevented by minocycline, an established anti-inflammatory antibiotic. We show here that the same inhibitory effect against LPS-induced neuroinflammation is exerted also by natural plant compounds, polyphenols, such as curcumin (CU, curcuma longa), crocin (CR, saffron), and resveratrol (RE, grape), as well as by the glucagon like peptide-1 receptor (GLP-1R) agonist exendin-4 (EX-4). The drugs tested also caused per-se early transient (variable) changes of network activity. Since it has been reported that LPS-induced neuroinflammation causes rearrangements of glutamate transporters in astrocytes and microglia, we suggest that neural activity could be putatively increased by an imbalance of glial glutamate transporter activity, leading to prolonged synaptic glutamatergic dysregulation.

Mesoporous silica nanoparticles trigger mitophagy in endothelial cells and perturb neuronal network activity in a size- and time-dependent manner

Purpose

Mesoporous silica nanoparticles (MSNPs) are excellent candidates for biomedical applications and drug delivery to different human body areas, the brain included. Although toxicity at cellular level has been investigated, we are still far from using MSNPs in the clinic, because the mechanisms involved in the cellular responses activated by MSNPs have not yet been elucidated.

Materials and methods

This study used an in vitro multiparametric approach to clarify relationships among size, dose, and time of exposure of MSNPs (0.05–1 mg/mL dose range), and cellular responses by analyzing the morphology, viability, and functionality of human vascular endothelial cells and neurons.

Results

The results showed that 24 hours of exposure of endothelial cells to 250 nm MSNPs exerted higher toxicity in terms of mitochondrial activity and membrane integrity than 30 nm MSN at the same dose. This was due to induced cell autophagy (in particular mitophagy), probably consequent to MSNP cellular uptake (>20%). Interestingly, after 24 hours of treatment with 30 nm MSNPs, very low MSNP uptake (<1%) and an increase in nitric oxide production (30%, P<0.01) were measured. This suggests that MSNPs were able to affect endothelial functionality from outside the cells. These differences could be attributed to the different protein-corona composition of the MSNPs used, as suggested by sodium dodecyl sulfate polyacrylamide-gel electrophoresis analysis of the plasma proteins covering the MSNP surface. Moreover, doses of MSNPs up to 0.25 mg/mL perturbed network activity by increasing excitability, as detected by multielectrode-array technology, without affecting neuronal cell viability.

Conclusion

These results suggest that MSNPs may be low-risk if prepared with a diameter <30 nm and if they reach human tissues at doses <0.25 mg/mL. These important advances could help the rational design of NPs intended for biomedical uses, demonstrating that careful toxicity evaluation is necessary before using MSNPs in patients.

Stochastic modeling of spontaneous bursting activity to simulate neural responses of in-vitro networks on multielectrode arrays

The study of neuronal bursting activity, observed in cell-culture, is physiologically important because is correlated with synaptic transmission, plasticity, and information processing. However, besides strong ethical issues related to the use of animal models, there are many limitations due to experimental setup and neural signaling acquisition. In this study, we propose a stochastic modeling approach to simulate neural dynamics observed in networks of neocortical neurons from an ex vivo normal mouse. Specifically, we devised a stochastic version of the Izhichevich's model of cortical neurons, and simulated a network of excitatory and inhibitory neurons also accounting for cell signaling delays. No specific learning rules were used throughout the simulation time. Results show spontaneous bursting activity while mimicking balanced and hyper-excitable networks through modulation of the inhibitory synaptic weights. Furthermore, we validate our findings comparing the simulated cumulative probability functions of the firing spike histograms with the ones obtained in cultured networks of dissociated cortical neurons from ex vivo mice.

Neuron-glia cross talk revealed in reverberating networks by simultaneous extracellular recording of spikes and astrocytes' glutamate transporter and K+ currents

In neocortex networks, we simultaneously captured spikes and the slower astrocytes' K⁺and glutamate transporter (GluT) currents with the use of individual MEA electrodes. Inward and outward K⁺currents in different regions of the glial syncytium suggested that spatial buffering was operant. Moreover, in organotypic slices from ventral tegmental area and prefrontal cortex, the large GluT current amplitudes allowed to measure transporter currents with a single electrode. Our method allows direct study of the dynamic interplay of different cell types in excitable and nonexcitable tissue.

Astrocytes uptake synaptically released glutamate with electrogenic transporters (GluT) and buffer the spike-dependent extracellular K⁺ excess with background K⁺ channels. We studied neuronal spikes and the slower astrocytic signals on reverberating neocortical cultures and organotypic slices from mouse brains. Spike trains and glial responses were simultaneously captured from individual sites of multielectrode arrays (MEA) by splitting the recorded traces into appropriate filters and reconstructing the original signal by deconvolution. GluT currents were identified by using dl-threo-β-benzyloxyaspartate (TBOA). K⁺ currents were blocked by 30 μM Ba²⁺, suggesting a major contribution of inwardly rectifying K⁺ currents. Both types of current were tightly correlated with the spike rate, and their astrocytic origin was tested in primary cultures by blocking glial proliferation with cytosine β-d-arabinofuranoside (AraC). The spike-related, time-locked inward and outward K⁺ currents in different regions of the astrocyte syncytium were consistent with the assumptions of the spatial K⁺ buffering model. In organotypic slices from ventral tegmental area and prefrontal cortex, the GluT current amplitudes exceeded those observed in primary cultures by several orders of magnitude, which allowed to directly measure transporter currents with a single electrode. Simultaneously measuring cell signals displaying widely different amplitudes and kinetics will help clarify the neuron-glia interplay and make it possible to follow the cross talk between different cell types in excitable as well as nonexcitable tissue.

Electrophysiological characterization of Nsc-34 cell line using Microelectrode Array

Neurons communicate with each other through intricate network to evolve higher brain functions. The electrical activity of the neurons plays a crucial role in shaping the connectivity. With motor neurons being vulnerable to neurodegenerative diseases, understanding the electrophysiological properties of motor neurons is the need of the hour, in order to comprehend the impairment of connectivity in these diseases. NSC-34 cell line serves as an excellent model to study the properties of motor neurons as they express Choline acetyltransferase (ChAT). Although NSC-34 cell lines have been used to study the effect of various toxicological, neurotrophic and neuroprotective agents, the electrical activity of these cells has not been elucidated. In the current study, we have characterized the electrophysiological properties of NSC-34 cell lines using Micro-Electrode Array (MEA) as a tool. Based on the spike waveform, firing frequency, auto- and cross-correlogram analysis, we demonstrate that NSC-34 cell culture has >2 distinct types of neuronal population: principal excitatory neurons, putative interneurons and unclassified neurons. The presence of interneurons in the NSC-34 culture was characterized by increased expression of GAD-67 markers. Thus, finding an understanding of the electrophysiological properties of different population of neurons in NSC-34 cell line, will have multiple applications in the treatment of neurological disorders.

Extracellularly Recorded Somatic and Neuritic Signal Shapes and Classification Algorithms for High-Density Microelectrode Array Electrophysiology

High-density microelectrode arrays (HDMEA) have been recently introduced to study principles of neural function at high spatial resolution. However, the exact nature of the experimentally observed extracellular action potentials (EAPs) is still incompletely understood. The soma, axon and dendrites of a neuron can all exhibit regenerative action potentials that could be sensed with HDMEA electrodes. Here, we investigate the contribution of distinct neuronal sources of activity in HDMEA recordings from low-density neuronal cultures. We recorded EAPs with HDMEAs having 11,011 electrodes and then fixed and immunostained the cultures with β3-tubulin for high-resolution fluorescence imaging. Immunofluorescence images overlaid with the activity maps showed EAPs both at neuronal somata and distal neurites. Neuritic EAPs had mostly narrow triphasic shapes, consisting of a positive, a pronounced negative peak and a second positive peak. EAPs near somata had wide monophasic or biphasic shapes with a main negative peak, and following optional positive peak. We show that about 86% of EAP recordings consist of somatic spikes, while the remaining 14% represent neuritic spikes. Furthermore, the adaptation of the waveform shape during bursts of these neuritic spikes suggested that they originate from axons, rather than from dendrites. Our study improves the understanding of HDMEA signals and can aid in the identification of the source of EAPs.

Progression of Neuronal Damage in an In Vitro Model of the Ischemic Penumbra

Improvement of neuronal recovery in the ischemic penumbra around a brain infarct has a large potential to advance clinical recovery of patients with acute ischemic stroke. However, pathophysiological mechanisms leading to either recovery or secondary damage in the penumbra are not completely understood. We studied neuronal dynamics in a model system of the penumbra consisting of networks of cultured cortical neurons exposed to controlled levels and durations of hypoxia. Short periods of hypoxia (pO₂≈20mmHg) reduced spontaneous activity, due to impeded synaptic function. After ≈6 hours, activity and connectivity partially recovered, even during continuing hypoxia. If the oxygen supply was restored within 12 hours, changes in network connectivity were completely reversible. For longer periods of hypoxia (12–30 h), activity levels initially increased, but eventually decreased and connectivity changes became partially irreversible. After ≈30 hours, all functional connections disappeared and no activity remained. Since this complete silence seemed unrelated to hypoxic depths, but always followed an extended period of low activity, we speculate that irreversible damage (at least partly) results from insufficient neuronal activation. This opens avenues for therapies to improve recovery by neuronal activation.

Shaping Neuronal Network Activity by Presynaptic Mechanisms

Neuronal microcircuits generate oscillatory activity, which has been linked to basic functions such as sleep, learning and sensorimotor gating. Although synaptic release processes are well known for their ability to shape the interaction between neurons in microcircuits, most computational models do not simulate the synaptic transmission process directly and hence cannot explain how changes in synaptic parameters alter neuronal network activity. In this paper, we present a novel neuronal network model that incorporates presynaptic release mechanisms, such as vesicle pool dynamics and calcium-dependent release probability, to model the spontaneous activity of neuronal networks. The model, which is based on modified leaky integrate-and-fire neurons, generates spontaneous network activity patterns, which are similar to experimental data and robust under changes in the model's primary gain parameters such as excitatory postsynaptic potential and connectivity ratio. Furthermore, it reliably recreates experimental findings and provides mechanistic explanations for data obtained from microelectrode array recordings, such as network burst termination and the effects of pharmacological and genetic manipulations. The model demonstrates how elevated asynchronous release, but not spontaneous release, synchronizes neuronal network activity and reveals that asynchronous release enhances utilization of the recycling vesicle pool to induce the network effect. The model further predicts a positive correlation between vesicle priming at the single-neuron level and burst frequency at the network level; this prediction is supported by experimental findings. Thus, the model is utilized to reveal how synaptic release processes at the neuronal level govern activity patterns and synchronization at the network level.

The activity of neuronal networks underlies basic neural functions such as sleep, learning and sensorimotor gating. Computational models of neuronal networks have been developed to capture the complexity of the network activity and predict how neuronal networks generate spontaneous activity. However, most computational models do not simulate the intricate synaptic release process that governs the interaction between neurons and has been shown to significantly impact neuronal network activity and animal behavior, learning and memory. Our paper demonstrates the importance of simulating the elaborate synaptic release process to understand how neuronal networks generate spontaneous activity and respond to manipulations of the release process. The model provides mechanistic explanations and predictions for experimental pharmacological and genetic manipulations. Thus, the model presents a novel computational platform to understand how mechanistic changes in the synaptic release process modulate network oscillatory activity that might impact basic neural functions.

The different effects of high-frequency stimulation of the nucleus accumbens shell and core on food consumption are possibly associated with different neural responses in the lateral hypothalamic area

Obesity may result from dysfunction of the reward system, especially in the nucleus accumbens (Acb). Based on this hypothesis, many researchers have tested the effect of high-frequency stimulation (HFS) of the Acb shell (Acb-Sh) and/or core (Acb-Co) on ingestive behaviors, but few studies have explored the possible mechanisms involved in the differences between the Acb-Sh and Acb-Co. The present study tested effects of HFS of the Acb-Sh and Acb-Co on high-fat food (HFF) consumption in rats after 24h of food deprivation. Microdialysis and electrophysiological experiments were carried out in awake rats to explore potential mechanisms. The results showed that the Acb-Sh decreased HFF consumption after food deprivation both during and post-HFS. However, HFS of the Acb-Co did not induce similar changes in food consumption. HFS of the Acb-Sh (Sh-HFS) induced an increase in GABA level in the lateral hypothalamic area (LHA) during both phases, whereas HFS of the Acb-Co (Co-HFS) did not exhibit similar effects. The electrophysiological experiment showed that nearly all the LHA neurons were inhibited by Sh-HFS, and the mean firing rate decreased significantly both during and post-HFS. In contrast, the mean firing rate of the LHA neurons did not exhibit clear changes during Co-HFS, although some individual neurons appeared to exhibit responses to Co-HFS. Considering all the data, we postulated that Sh-HFS, rather than Co-HFS, might inhibit palatable food consumption after food deprivation by decreasing the reward value of that food, which suggested that it might also disturb the process of developing obesity. The mechanisms involved in the different effects of Sh-HFS and Co-HFS on food consumption may be associated with different neural responses in the LHA. The Acb-Sh has abundant GABAergic projections to the LHA, whereas the Acb-Co has few or no GABAergic innervations to the LHA. Thus, neural activity in the LHA exhibits different responses to Sh-HFS and Co-HFS.

Accelerated intoxication of GABAergic synapses by botulinum neurotoxin A disinhibits stem cell-derived neuron networks prior to network silencing

Botulinum neurotoxins (BoNTs) are extremely potent toxins that specifically cleave SNARE proteins in peripheral synapses, preventing neurotransmitter release. Neuronal responses to BoNT intoxication are traditionally studied by quantifying SNARE protein cleavage in vitro or monitoring physiological paralysis in vivo. Consequently, the dynamic effects of intoxication on synaptic behaviors are not well-understood. We have reported that mouse embryonic stem cell-derived neurons (ESNs) are highly sensitive to BoNT based on molecular readouts of intoxication. Here we study the time-dependent changes in synapse- and network-level behaviors following addition of BoNT/A to spontaneously active networks of glutamatergic and GABAergic ESNs. Whole-cell patch-clamp recordings indicated that BoNT/A rapidly blocked synaptic neurotransmission, confirming that ESNs replicate the functional pathophysiology responsible for clinical botulism. Quantitation of spontaneous neurotransmission in pharmacologically isolated synapses revealed accelerated silencing of GABAergic synapses compared to glutamatergic synapses, which was consistent with the selective accumulation of cleaved SNAP-25 at GAD1⁺ pre-synaptic terminals at early timepoints. Different latencies of intoxication resulted in complex network responses to BoNT/A addition, involving rapid disinhibition of stochastic firing followed by network silencing. Synaptic activity was found to be highly sensitive to SNAP-25 cleavage, reflecting the functional consequences of the localized cleavage of the small subpopulation of SNAP-25 that is engaged in neurotransmitter release in the nerve terminal. Collectively these findings illustrate that use of synaptic function assays in networked neurons cultures offers a novel and highly sensitive approach for mechanistic studies of toxin:neuron interactions and synaptic responses to BoNT.

Comparison of spike parameters from optically identified GABAergic and glutamatergic neurons in sparse cortical cultures

Primary neuronal cultures share many typical features with the in vivo situation, including similarities in distinct electrical activity patterns and synaptic network interactions. Here, we use multi-electrode array (MEA) recordings from spontaneously active cultures of wildtype and glutamic acid decarboxylase 67 (GAD67)-green fluorescent protein (GFP) transgenic mice to evaluate which spike parameters differ between GABAergic interneurons and principal, putatively glutamatergic neurons. To analyze this question we combine MEA recordings with optical imaging in sparse cortical cultures to assign individual spikes to visually-identified single neurons. In our culture system, excitatory and inhibitory neurons are present at a similar ratio as described in vivo, and spike waveform characteristics and firing patterns are fully developed after 2 weeks in vitro. Spike amplitude, but not other spike waveform parameters, correlated with the distance between the recording electrode and the location of the assigned neuron’s soma. Cluster analysis of spike waveform properties revealed no particular cell population that may be assigned to putative inhibitory or excitatory neurons. Moreover, experiments in primary cultures from transgenic GAD67-GFP mice, which allow optical identification of GABAergic interneurons and thus unambiguous assignment of extracellular signals, did not reveal any significant difference in spike timing and spike waveform parameters between inhibitory and excitatory neurons. Despite of our detailed characterization of spike waveform and temporal spiking properties we could not identify an unequivocal electrical parameter to discriminate between individual excitatory and inhibitory neurons in vitro. Our data suggest that under in vitro conditions cellular classifications of single neurons on the basis of their extracellular firing properties should be treated with caution.

Functional connectivity estimation over large networks at cellular resolution based on electrophysiological recordings and structural prior

Despite many structural and functional aspects of the brain organization have been extensively studied in neuroscience, we are still far from a clear understanding of the intricate structure-function interactions occurring in the multi-layered brain architecture, where billions of different neurons are involved. Although structure and function can individually convey a large amount of information, only a combined study of these two aspects can probably shade light on how brain circuits develop and operate at the cellular scale. Here, we propose a novel approach for refining functional connectivity estimates within neuronal networks using the structural connectivity as prior. This is done at the mesoscale, dealing with thousands of neurons while reaching, at the microscale, an unprecedented cellular resolution. The High-Density Micro Electrode Array (HD-MEA) technology, combined with fluorescence microscopy, offers the unique opportunity to acquire structural and functional data from large neuronal cultures approaching the granularity of the single cell. In this work, an advanced method based on probabilistic directional features and heat propagation is introduced to estimate the structural connectivity from the fluorescence image while functional connectivity graphs are obtained from the cross-correlation analysis of the spiking activity. Structural and functional information are then integrated by reweighting the functional connectivity graph based on the structural prior. Results show that the resulting functional connectivity estimates are more coherent with the network topology, as compared to standard measures purely based on cross-correlations and spatio-temporal filters. We finally use the obtained results to gain some insights on which features of the functional activity are more relevant to characterize actual neuronal interactions.

Atypical "seizure-like" activity in cortical reverberating networks in vitro can be caused by LPS-induced inflammation: a multi-electrode array study from a hundred neurons

We show here that a mild sterile inflammation induced by the endotoxin lipopolysaccharide (LPS), in a neuron/astrocyte/microglial cortical network, modulates neuronal excitability and can initiate long-duration burst events resembling epileptiform seizures, a recognized feature of various central nervous neurodegenerative, neurological and acute systemic diseases associated with neuroinflammation. To study this action, we simultaneously analyzed the reverberating bursting activity of a hundred neurons by using in vitro multi-electrode array methods. ∼5 h after LPS application, we observed a net increase in the average number of spikes elicited in engaged cells and within each burst, but no changes neither in spike waveforms nor in burst rate. This effect was characterized by a slow, twofold exponential increase of the burst duration and the appearance of rarely occurring long burst events that were never seen during control recordings. These changes and the time-course of microglia-released proinflammatory cytokine, tumor necrosis factor-alpha (TNF-α), were blocked by pre-treatment with 50 nM minocycline, an established anti-inflammatory agent which was inactive when applied alone. Assay experiments also revealed that application of 60 pM exogenous TNF-α after 12–15 h, produced non-washable changes of neuronal excitability, completely different from those induced by LPS, suggesting that TNF-α release alone was not responsible for our observed findings. Our results indicate that the link between neuroinflammation and hyperexcitability can be unveiled by studying the long-term activity of in vitro neuronal/astrocyte/microglial networks.

Multi-electrode array study of neuronal cultures expressing nicotinic β2-V287L subunits, linked to autosomal dominant nocturnal frontal lobe epilepsy. An in vitro model of spontaneous epilepsy

Autosomal dominant nocturnal frontal lobe epilepsy (ADNFLE) is a partial sleep-related epilepsy which can be caused by mutant neuronal nicotinic acetylcholine receptors (nAChR). We applied multi-electrode array (MEA) recording methods to study the spontaneous firing activity of neocortical cultures obtained from mice expressing or not (WT) an ADNFLE-linked nAChR subunit (β2-V287L). More than 100,000 up-states were recorded during experiments sampling from several thousand neurons. Data were analyzed by using a fast sliding-window procedure which computes histograms of the up-state durations. Differently from the WT, cultures expressing β2-V287L displayed long (10–32 s) synaptic-induced up-state firing events. The occurrence of such long up-states was prevented by both negative (gabazine, penicillin G) and positive (benzodiazepines) modulators of GABA_A receptors. Carbamazepine (CBZ), a drug of choice in ADNFLE patients, also inhibited the long up-states at micromolar concentrations. In cultures expressing β2-V287L, no significant effect was observed on the action potential waveform either in the absence or in the presence of pharmacological treatment. Our results show that some aspects of the spontaneous hyperexcitability displayed by a murine model of a human channelopathy can be reproduced in neuronal cultures. In particular, our cultures represent an in vitro chronic model of spontaneous epileptiform activity, i.e., not requiring pre-treatment with convulsants. This opens the way to the study in vitro of the role of β2-V287L on synaptic formation. Moreover, our neocortical cultures on MEA platforms allow to determine the effects of prolonged pharmacological treatment on spontaneous network hyperexcitability (which is impossible in the short-living brain slices). Methods such as the one we illustrate in the present paper should also considerably facilitate the preliminary screening of antiepileptic drugs (AEDs), thereby reducing the number of in vivo experiments.

Intrinsically active and pacemaker neurons in pluripotent stem cell-derived neuronal populations

Neurons generated from pluripotent stem cells (PSCs) self-organize into functional neuronal assemblies in vitro, generating synchronous network activities. Intriguingly, PSC-derived neuronal assemblies develop spontaneous activities that are independent of external stimulation, suggesting the presence of thus far undetected intrinsically active neurons (IANs). Here, by using mouse embryonic stem cells, we provide evidence for the existence of IANs in PSC-neuronal networks based on extracellular multielectrode array and intracellular patch-clamp recordings. IANs remain active after pharmacological inhibition of fast synaptic communication and possess intrinsic mechanisms required for autonomous neuronal activity. PSC-derived IANs are functionally integrated in PSC-neuronal populations, contribute to synchronous network bursting, and exhibit pacemaker properties. The intrinsic activity and pacemaker properties of the neuronal subpopulation identified herein may be particularly relevant for interventions involving transplantation of neural tissues. IANs may be a key element in the regulation of the functional activity of grafted as well as preexisting host neuronal networks.

•

PSC-neuronal assemblies harbor intrinsically active neurons (IANs)

•

IANs remain active after inhibition of fast glutamatergic synaptic transmission

•

Autonomous activities of PSC IANs depend on persistent active sodium currents

•

PSC IANs contribute to concerted network activity and have pacemaker properties

Results on a binding neuron model and their implications for modified hourglass model for neuronal network

The classical models of single neuron like Hodgkin-Huxley point neuron or leaky integrate and fire neuron assume the influence of postsynaptic potentials to last till the neuron fires. Vidybida (2008) in a refreshing departure has proposed models for binding neurons in which the trace of an input is remembered only for a finite fixed period of time after which it is forgotten. The binding neurons conform to the behaviour of real neurons and are applicable in constructing fast recurrent networks for computer modeling. This paper develops explicitly several useful results for a binding neuron like the firing time distribution and other statistical characteristics. We also discuss the applicability of the developed results in constructing a modified hourglass network model in which there are interconnected neurons with excitatory as well as inhibitory inputs. Limited simulation results of the hourglass network are presented.

Differential effects of cholinergic and noradrenergic neuromodulation on spontaneous cortical network dynamics

Cholinergic and noradrenergic neuromodulation play a key role in determining overall behavioral state by shaping the underlying cortical network dynamics. The effects of these systems on synaptic and intrinsic cellular targets are quite diverse and a comprehensive understanding of how these neuromodulators regulate (spontaneous) cortical network activity has remained elusive. Here, we used multielectrode electrophysiology in vitro to investigate the effect of these neuromodulators on spontaneous network dynamics in acute slices of mouse visual cortex. We found that application of Carbachol (CCh) and Norepinephrine (NE) both enhanced the spontaneous network dynamics by increasing (1) the activity levels, (2) the temporal complexity of the network activity, and (3) the spatial complexity by decorrelating the network activity over a wide range of neuromodulator concentrations (1 μM, 10 μM, 50 μM, and 100 μM). Interestingly, we found that cholinergic neuromodulation was limited to the presence of CCh in the bath whereas the effects of NE, in particular for higher concentrations, induced plasticity that caused outlasting effects most prominently in the deep cortical layers. Together, these results provide a comprehensive network-level understanding of the similarities and differences of cholinergic and noradrenergic modulation of spontaneous network dynamics.

DOC2B and Munc13-1 differentially regulate neuronal network activity

Alterations in the levels of synaptic proteins affect synaptic transmission and synaptic plasticity. However, the precise effects on neuronal network activity are still enigmatic. Here, we utilized microelectrode array (MEA) to elucidate how manipulation of the presynaptic release process affects the activity of neuronal networks. By combining pharmacological tools and genetic manipulation of synaptic proteins, we show that overexpression of DOC2B and Munc13-1, proteins known to promote vesicular maturation and release, elicits opposite effects on the activity of the neuronal network. Although both cause an increase in the overall number of spikes, the distribution of spikes is different. While DOC2B enhances, Munc13-1 reduces the firing rate within bursts of spikes throughout the network; however, Munc13-1 increases the rate of network bursts. DOC2B's effects were mimicked by Strontium that elevates asynchronous release but not by a DOC2B mutant that enhances spontaneous release rate. This suggests for the first time that increased asynchronous release on the single-neuron level promotes bursting activity in the network level. This innovative study demonstrates the complementary role of the network level in explaining the physiological relevance of the cellular activity of presynaptic proteins and the transformation of synaptic release manipulation from the neuron to the network level.

Impact of network topology on inference of synaptic connectivity from multi-neuronal spike data simulated by a large-scale cortical network model

Many mechanisms of neural processing rely critically upon the synaptic connectivity between neurons. As our ability to simultaneously record from large populations of neurons expands, the ability to infer network connectivity from this data has become a major goal of computational neuroscience. To address this issue, we employed several different methods to infer synaptic connections from simulated spike data from a realistic local cortical network model. This approach allowed us to directly compare the accuracy of different methods in predicting synaptic connectivity. We compared the performance of model-free (coherence measure and transfer entropy) and model-based (coupled escape rate model) methods of connectivity inference, applying those methods to the simulated spike data from the model networks with different network topologies. Our results indicate that the accuracy of the inferred connectivity was higher for highly clustered, near regular, or small-world networks, while accuracy was lower for random networks, irrespective of which analysis method was employed. Among the employed methods, the model-based method performed best. This model performed with higher accuracy, was less sensitive to threshold changes, and required less data to make an accurate assessment of connectivity. Given that cortical connectivity tends to be highly clustered, our results outline a powerful analytical tool for inferring local synaptic connectivity from observations of spontaneous activity.

Novel modulatory effects of neurosteroids and benzodiazepines on excitatory and inhibitory neurons excitability: a multi-electrode array recording study

The balance between glutamate- and GABA-mediated neurotransmission in the brain is fundamental in the nervous system, but it is regulated by the “tonic” release of a variety of endogenous factors. One such important group of molecules are the neurosteroids (NSs) which, similarly to benzodiazepines (BDZs), enhance GABAergic neurotransmission. The purpose of our work was to investigate, at in vivo physiologically relevant concentrations, the effects of NSs and BDZs as GABA modulators on dissociated neocortical neuron networks grown in long-term culture. We used a multi-electrode array (MEA) recording technique and a novel analysis that was able to both identify the action potentials of engaged excitatory and inhibitory neurons and to detect drug-induced network up-states (burst). We found that the NSs tetrahydrodeoxycorticosterone (THDOC) and allopregnanolone (ALLO) applied at low nanomolar concentrations, produced different modulatory effects on the two neuronal clusters. Conversely, at high concentrations (1 μM), both NSs, decreased excitatory and inhibitory neuron cluster excitability; however, even several hours after wash-out, the excitability of inhibitory neurons continued to be depressed, leading to a network long-term depression (LTD). The BDZs clonazepam (CLZ) and midazolam (MDZ) also decreased the network excitability, but only MDZ caused LTD of inhibitory neuron cluster. To investigate the origin of the LTD after MDZ application, we tested finasteride (FIN), an inhibitor of endogenous NSs synthesis. FIN did not prevent the LTD induced by MDZ, but surprisingly induced it after application of CLZ. The significance and possible mechanisms underlying these LTD effects of NSs and BDZs are discussed. Taken together, our results not only demonstrate that ex vivo networks show a sensitivity to NSs and BDZs comparable to that expressed in vivo, but also provide a new global in vitro description that can help in understanding their activity in more complex systems.