scholarly journals meaRtools: an R Package for the Analysis of Neuronal Networks Recorded on Microelectrode Arrays

2018 ◽  
Author(s):  
Sahar Gelfman ◽  
Quanli Wang ◽  
Yi-Fan Lu ◽  
Diana Hall ◽  
Christopher D. Bostick ◽  
...  
Keyword(s):  
Spike Train ◽  
Neuronal Networks ◽  
Microelectrode Arrays ◽  
R Package ◽  
Network Activity ◽  
Neuronal Cultures ◽  
Mixed Cell ◽  
Spike Train Analysis ◽  
Neuronal Network Activity

AbstractHere we present an open-source R package ‘meaRtools’ that provides a platform for analyzing neuronal networks recorded on Microelectrode Arrays (MEAs). Cultured neuronal networks monitored with MEAs are now being widely used to characterize in vitro models of neurological disorders and to evaluate pharmaceutical compounds. meaRtools provides core algorithms for MEA spike train analysis, feature extraction, statistical analysis and plotting of multiple MEA recordings with multiple genotypes and treatments. meaRtools functionality covers novel solutions for spike train analysis, including algorithms to assess electrode cross-correlation using the spike train tiling coefficient (STTC), mutual information, synchronized bursts and entropy within cultured wells. Also integrated is a solution to account for bursts variability originating from mixed-cell neuronal cultures. The package provides a statistical platform built specifically for MEA data that can combine multiple MEA recordings and compare extracted features between different genetic models or treatments. We demonstrate the utilization of meaRtools to successfully identify epilepsy-like phenotypes in neuronal networks from Celf4 knockout mice. The package is freely available under the GPL license (GPL>=3) and is updated frequently on the CRAN web-server repository. The package, along with full documentation can be downloaded from: https://cran.r-project.org/web/packages/meaRtools/.Author summaryCultured neuronal networks are widely used to study and characterize neuronal network activity. Among the many uses of neuronal cultures are the capabilities to evaluate neurotoxicity and the effects of pharmacological compounds on cellular physiology. Multi-well microelectrode arrays (MEAs) can collect high-throughput data from multiple neuronal cultures simultaneously, and thereby make possible hypotheses-driven inquiries into neurobiology and neuropharmacology. The analysis of MEA-derived information presents many computational challenges. High frequency data recorded simultaneously from hundreds of electrodes can be difficult to handle. The need to compare network activity across various drug treatments or genotypes recorded on the same plate from experiments lasting several weeks presents another challenge. These challenges inspired us to develop meaRtools; an MEA data analysis package that contains new methods to characterize network activity patterns, which are illustrated here using examples from a genetic mouse model of epilepsy. Among the highlights of meaRtools are novel algorithms designed to characterize neuronal activity dynamics and network properties such as bursting and synchronization, options to combine multiple recordings and use a robust statistical framework to draw appropriate statistical inferences, and finally data visualizations and plots. In summary, meaRtools provides a platform for the analyses of singular and longitudinal MEA experiments.

scholarly journals Human neuronal networks on micro-electrode arrays are a highly robust tool to study disease-specific genotype-phenotype correlations in vitro

2021 ◽  
Author(s):  
B. Mossink ◽  
A.H.A. Verboven ◽  
E.J.H. van Hugte ◽  
T.M. Klein Gunnewiek ◽  
G. Parodi ◽  
...  
Keyword(s):  
Experimental Design ◽  
Neuronal Network ◽  
Neuronal Networks ◽  
Network Activity ◽  
Full Potential ◽  
Electrode Arrays ◽  
Neuronal Network Activity ◽  
Micro Electrode Arrays ◽  
Disease Specific

AbstractMicro-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 and sensitivity of MEA-derived neuronal activity patterns derived from ten healthy individual control lines. We provide recommendations on experimental design and analysis to achieve standardization. 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 towards the use of MEAs for disease-phenotyping and drug discovery.

scholarly journals Early prediction of developing spontaneous activity in cultured neuronal networks

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
David Cabrera-Garcia ◽  
Davide Warm ◽  
Pablo de la Fuente ◽  
M. Teresa Fernández-Sánchez ◽  
Antonello Novelli ◽  
...  
Keyword(s):  
Machine Learning ◽  
Spontaneous Activity ◽  
Early Development ◽  
Neuronal Network ◽  
Multivariate Adaptive Regression Splines ◽  
Network Activity ◽  
Support Vector ◽  
Neuronal Cultures ◽  
Neuronal Network Activity

AbstractSynchronization and bursting activity are intrinsic electrophysiological properties of in vivo and in vitro neural networks. During early development, cortical cultures exhibit a wide repertoire of synchronous bursting dynamics whose characterization may help to understand the parameters governing the transition from immature to mature networks. Here we used machine learning techniques to characterize and predict the developing spontaneous activity in mouse cortical neurons on microelectrode arrays (MEAs) during the first three weeks in vitro. Network activity at three stages of early development was defined by 18 electrophysiological features of spikes, bursts, synchrony, and connectivity. The variability of neuronal network activity during early development was investigated by applying k-means and self-organizing map (SOM) clustering analysis to features of bursts and synchrony. These electrophysiological features were predicted at the third week in vitro with high accuracy from those at earlier times using three machine learning models: Multivariate Adaptive Regression Splines, Support Vector Machines, and Random Forest. Our results indicate that initial patterns of electrical activity during the first week in vitro may already predetermine the final development of the neuronal network activity. The methodological approach used here may be applied to explore the biological mechanisms underlying the complex dynamics of spontaneous activity in developing neuronal cultures.

scholarly journals Extracellular matrix supports excitation-inhibition balance in neuronal networks by stabilizing inhibitory synapses

2020 ◽  
Author(s):  
Egor Dzyubenko ◽  
Michael Fleischer ◽  
Daniel Manrique-Castano ◽  
Mina Borbor ◽  
Christoph Kleinschnitz ◽  
...  
Keyword(s):  
Extracellular Matrix ◽  
Neuronal Network ◽  
Neuronal Plasticity ◽  
Neuronal Networks ◽  
Network Activity ◽  
Inhibitory Synapses ◽  
Neuronal Network Activity ◽  
The Brain

AbstractMaintaining the balance between excitation and inhibition is essential for the appropriate control of neuronal network activity. Sustained excitation-inhibition (E-I) balance relies on the orchestrated adjustment of synaptic strength, neuronal activity and network circuitry. While growing evidence indicates that extracellular matrix (ECM) of the brain is a crucial regulator of neuronal excitability and synaptic plasticity, it remains unclear whether and how ECM contributes to neuronal circuit stability. Here we demonstrate that the integrity of ECM supports the maintenance of E-I balance by retaining inhibitory connectivity. Depletion of ECM in mature neuronal networks preferentially decreases the density of inhibitory synapses and the size of individual inhibitory postsynaptic scaffolds. After ECM depletion, inhibitory synapse strength homeostatically increases via the reduction of presynaptic GABAB receptors. However, the inhibitory connectivity reduces to an extent that inhibitory synapse scaling is no longer efficient in controlling neuronal network activity. Our results indicate that the brain ECM preserves the balanced network state by stabilizing inhibitory synapses.Significance statementThe question how the brain’s extracellular matrix (ECM) controls neuronal plasticity and network activity is key for an appropriate understanding of brain functioning. In this study, we demonstrate that ECM depletion much more strongly affects the integrity of inhibitory than excitatory synapses in vitro and in vivo. We revealed that by retaining inhibitory connectivity, ECM ensures the efficiency of inhibitory control over neuronal network activity. Our work significantly expands our current state of knowledge about the mechanisms of neuronal network activity regulation. Our findings are similarly relevant for researchers working on the physiological regulation of neuronal plasticity in vitro and in vivo and for researchers studying the remodeling of neuronal networks upon brain injury, where prominent ECM alterations occur.

scholarly journals Quantitation of Chronic and Acute Treatment Effects on Neuronal Network Activity Using Image and Signal Analysis

2013 ◽  
Vol 18 (7) ◽  
pp. 807-819 ◽  
Author(s):  
Frans Cornelissen ◽  
Peter Verstraelen ◽  
Tobias Verbeke ◽  
Isabel Pintelon ◽  
Jean-Pierre Timmermans ◽  
...  
Keyword(s):  
Neuronal Cell ◽  
Network Activity ◽  
Cell Segmentation ◽  
Neuronal Cultures ◽  
Nuclear Staining ◽  
Primary Neuronal Cultures ◽  
Independent Manner ◽  
Neuronal Network Activity ◽  
Decay Times

Upon maturation, primary neuronal cultures form an interconnected network based on neurite outgrowth and synaptogenesis in which spontaneous electrical activity arises. Measurement of network activity allows quantification of neuronal health and maturation. A fluorescent indicator was used to monitor secondary calcium influxes after the occurrence of action potentials, allowing us to examine activity of hippocampal cultures via confocal live cell imaging. Subsequently, nuclear staining with DAPI allows accurate cell segmentation. To analyze the calcium recording in a robust, observer-independent manner, we implemented an automated image- and signal-processing algorithm and validated it against a visual, interactive procedure. Both methods yielded similar results on the emergence of synchronized activity and allowed robust quantitative measurement of acute and chronic modulation of drugs on network activity. Both the number of days in vitro (DIV) and neutralization of nerve growth factor (NGF) have a significant effect on synchronous burst frequency and correlation. Acute effects are demonstrated using 5-HT (serotonin) and ethylene glycol tetra-acetic acid. Automated analysis allowed measuring additional features, such as peak decay times and bursting frequency of individual neurons. Based on neuronal cell cultures in 96-well plates and accurate calcium recordings, the analysis method allows development of an integrated high-content screening assay. Because molecular biological techniques can be applied to assess the influence of genes on network activity, it is applicable for neurotoxicity or neurotrophics screening as well as development of in vitro disease models via, for example, pharmacologic manipulation or RNAi.

Dementia with Lewy bodies—associated ß-synuclein mutations V70M and P123H cause mutation-specific neuropathological lesions

2021 ◽  
Author(s):  
Maryna Psol ◽  
Sofia Guerin Darvas ◽  
Kristian Leite ◽  
Sameehan U Mahajani ◽  
Mathias Bähr ◽  
...  
Keyword(s):  
Neuronal Network ◽  
Dementia With Lewy Bodies ◽  
Lewy Bodies ◽  
Sporadic Case ◽  
Network Activity ◽  
Proteinase K ◽  
Neuronal Network Activity ◽  
Distinct Disease

Abstract ß-Synuclein (ß-Syn) has long been considered to be an attenuator for the neuropathological effects caused by the Parkinson’s disease-related α-Synuclein (α-Syn) protein. However, recent studies demonstrated that overabundant ß-Syn can form aggregates and induce neurodegeneration in CNS neurons in vitro and in vivo, albeit at a slower pace as compared to α-Syn. Here we demonstrate that ß-Syn mutants V70M, detected in a sporadic case of Dementia with Lewy Bodies (DLB), and P123H, detected in a familial case of DLB, robustly aggravate the neurotoxic potential of ß-Syn. Intriguingly, the two mutations trigger mutually exclusive pathways. ß-Syn V70M enhances morphological mitochondrial deterioration and degeneration of dopaminergic and non-dopaminergic neurons, but has no influence on neuronal network activity. Conversely, ß-Syn P123H silences neuronal network activity, but does not aggravate neurodegeneration. ß-Syn WT, V70M and P123H formed proteinase K (PK) resistant intracellular fibrils within neurons, albeit with less stable C-termini as compared to α-Syn. Under cell free conditions, ß-Syn V70M demonstrated a much slower pace of fibril formation as compared to WT ß-Syn, and P123H fibrils present with a unique phenotype characterized by large numbers of short, truncated fibrils. Thus, it is possible that V70M and P123H cause structural alterations in ß-Syn, that are linked to their distinct neuropathological profiles. The extent of the lesions caused by these neuropathological profiles is almost identical to that of overabundant α-Syn, and thus likely to be directly involved into etiology of DLB. Over all, this study provides insights into distinct disease mechanisms caused by mutations of ß-Syn.

scholarly journals Cell–cell coupling and DNA methylation abnormal phenotypes in the after-hours mice

2021 ◽  
Vol 14 (1) ◽  
Author(s):  
Federico Tinarelli ◽  
Elena Ivanova ◽  
Ilaria Colombi ◽  
Erica Barini ◽  
Edoardo Balzani ◽  
...  
Keyword(s):  
Gene Expression ◽  
Dna Methylation ◽  
Neuronal Networks ◽  
Molecular Mechanisms ◽  
Ex Vivo ◽  
Neuronal Cultures ◽  
Functional Impairments ◽  
After Hours ◽  
The Impact

Abstract Background DNA methylation has emerged as an important epigenetic regulator of brain processes, including circadian rhythms. However, how DNA methylation intervenes between environmental signals, such as light entrainment, and the transcriptional and translational molecular mechanisms of the cellular clock is currently unknown. Here, we studied the after-hours mice, which have a point mutation in the Fbxl3 gene and a lengthened circadian period. Methods In this study, we used a combination of in vivo, ex vivo and in vitro approaches. We measured retinal responses in Afh animals and we have run reduced representation bisulphite sequencing (RRBS), pyrosequencing and gene expression analysis in a variety of brain tissues ex vivo. In vitro, we used primary neuronal cultures combined to micro electrode array (MEA) technology and gene expression. Results We observed functional impairments in mutant neuronal networks, and a reduction in the retinal responses to light-dependent stimuli. We detected abnormalities in the expression of photoreceptive melanopsin (OPN4). Furthermore, we identified alterations in the DNA methylation pathways throughout the retinohypothalamic tract terminals and links between the transcription factor Rev-Erbα and Fbxl3. Conclusions The results of this study, primarily represent a contribution towards an understanding of electrophysiological and molecular phenotypic responses to external stimuli in the Afh model. Moreover, as DNA methylation has recently emerged as a new regulator of neuronal networks with important consequences for circadian behaviour, we discuss the impact of the Afh mutation on the epigenetic landscape of circadian biology.

Influence of albumin dialysis (MARS) on neuronal network activity in vitro

2001 ◽  
Vol 39 ◽  
pp. 40-40
Author(s):  
J Loock ◽  
J Stange ◽  
S Mitzner ◽  
R Schmidt ◽  
E W Keefer ◽  
...  
Keyword(s):  
Neuronal Network ◽  
Network Activity ◽  
Albumin Dialysis ◽  
Neuronal Network Activity

scholarly journals meaRtools: An R package for the analysis of neuronal networks recorded on microelectrode arrays

2018 ◽  
Vol 14 (10) ◽  
pp. e1006506 ◽  
Author(s):  
Sahar Gelfman ◽  
Quanli Wang ◽  
Yi-Fan Lu ◽  
Diana Hall ◽  
Christopher D. Bostick ◽  
...  
Keyword(s):  
Neuronal Networks ◽  
Microelectrode Arrays ◽  
R Package
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