Neural Signal Manager: a collection of classical and innovative tools for multi‐channel spike train analysis

Abstract

SUMMARYRecent developments in the neuroengineering field and the widespread use of the micro electrode arrays (MEAs) for electrophysiological investigations made available new approaches for studying the dynamics of dissociated neuronal networks as well as acute/organotypic slices maintained ex vivo. Importantly, the extraction of relevant parameters from these neural populations is likely to involve long-term measurements, lasting from a few hours to entire days. The processing of huge amounts of electrophysiological data, in terms of computational time and automation of the procedures, is actually one of the major bottlenecks for both in vivo and in vitro recordings. In this paper we present a collection of algorithms implemented within a new software package, named the Neural Signal Manager (NSM), aimed at analyzing a huge quantity of data recorded by means of MEAs in a fast and efficient way. The NSM offers different approaches for both spike and burst analysis, and integrates state-of-the-art statistical algorithms, such as the interspike interval histogram or the post stimulus time histogram, with some recent ones, such as the burst detection and its related statistics. In order to show the potentialities of the software, the application of the developed algorithms to a set of spontaneous activity recordings from dissociated cultures at different ages is presented in the Results section.

Recurrence Quantification Analysis of Spontaneous Electrophysiological Activity during Development: Characterization of In Vitro Neuronal Networks Cultured on Multi Electrode Array Chips

“…During development, neuronal networks change in morphology and express different activity patterns [7,20,30]: activity that ranges from sporadic spiking (when the network presents immature types of synapses and a very low synaptic density) [43,44] to complex synchronous activity packages (when neurons start exploiting "far" connections and the network manifests its collective behavior, i.e., network burst) [4,7,30,45,46]. While spike trains can be accurately extracted from MEA recordings, for example, [21,22], identification, description, and prediction of changes in electrophysiological dynamic are less accessible by means of standard processing techniques for neuronal electrophysiology. The introduction of Recurrence Plot [25] and Recurrence Quantification Analysis [24] has made available innovative tools for investigating in complex dynamic of nonstationary systems.…”

“…The spike trains can be accurately extracted from MEA recordings, for example, [21,22], and thus neuronal activity is translated into time series of discrete events. The ensembles of spike trains simultaneously recorded from many channels represent multidimensional nonstationary pointprocess time series which makes the data analysis highly challenging [23].…”

QSpike tools: a generic framework for parallel batch preprocessing of extracellular neuronal signals recorded by substrate microelectrode arrays

“…However, in terms of data collection, analysis, and interpretation, multi-site extracellular recordings pose some challenges, given the large size of the raw data files acquired and the inherent complexity behind their rapid and accurate interpretation (Buzsaki, 2004 ; Stevenson and Kording, 2011 ). From Neuroinformatics perspectives, several open-source software toolboxes have been developed and released to the community over the years, addressing those issues and ultimately aimed at making electrophysiological data handling and analysis easier, faster, interactive, and more user friendly (Egert et al, 2002 ; Quiroga et al, 2004 ; Vato et al, 2004 ; Bonomini et al, 2005 ; Wagenaar et al, 2005 ; Morup et al, 2007 ; Cui et al, 2008 ; Huang et al, 2008 ; Magri et al, 2009 ; Novellino et al, 2009 ; Bologna et al, 2010 ; Abdoun et al, 2011 ; Kwon et al, 2012 ; Mahmud et al, 2012 ; Just et al, 2013 ). Hardware based techniques have been also made available to the community to perform spike detection and sorting (Yu et al, 2012 ; Hwang et al, 2013 ).…”

SigMate: A Matlab-based automated tool for extracellular neuronal signal processing and analysis

“…There are a number of existing tools developed for academic and commercial purposes (Bokil et al, 2010;Bologna et al, 2010;Bonomini et al, 2005;Cui et al, 2008;Delorme and Makeig 2004;Egert et al, 2002;Goldberg et al, 2009;Gunay et al, 2009;Hazan et al, 2006;Herz et al, 2008;Huang et al, 2008;Kwon et al, 2011;Magri et al, 2009;Morup et al, 2007;Novellino et al,2009;Quiroga et al, 2004;Smith and Mtetwa, 2007;Vargas-Irwin and Donoghue, 2007;Vato et al, 2004;Versace et al, 2008;Wagenaar et al, 2005).…”