Literature DB >> 19056423

sigTOOL: A MATLAB-based environment for sharing laboratory-developed software to analyze biological signals.

Malcolm Lidierth1.   

Abstract

This paper describes a software package, named sigTOOL, for processing biological signals. The package runs in the MATLAB programming environment and has been designed to promote the sharing of laboratory-developed software across the worldwide web. As proof-of-concept of the design of the system, sigTOOL has been used to build an analysis application for dealing with neuroscience data complete with a user-friendly graphical user interface which implements a range of waveform and spike-train analysis functions. The interface allows many commonly used neuroscience data file formats to be loaded (including those of Alpha Omega, Cambridge Electronic Design, Cyberkinetics Inc., Molecular Devices, Nex Technologies and Plexon Instruments). Waveform analysis functions selectable from the interface support waveform averaging (mean and median), auto- and cross-correlation, power spectral analysis, coherence estimation, digital filtering (feedback and feedforward) and resampling. Spike-train analyses include interspike interval distributions, Poincaré plots, event auto- and cross-correlations, spike-triggered averaging, stimulus driven and phase-related peri-event time histograms and rasters as well as frequencygrams. User-developed additions to sigTOOL that are archived and distributed electronically will be added to the sigTOOL interface on-the-fly, without the need to modify the core sigTOOL code. Full sigTOOL functionality will be provided to support the user-developed code, including the ability to record a user action history for batch processing of files and support for exporting the results of analyses to external graphics editing software and spreadsheet-based data processing packages.

Mesh:

Year:  2008        PMID: 19056423     DOI: 10.1016/j.jneumeth.2008.11.004

Source DB:  PubMed          Journal:  J Neurosci Methods        ISSN: 0165-0270            Impact factor:   2.390


  28 in total

1.  Spike train analysis toolkit: enabling wider application of information-theoretic techniques to neurophysiology.

Authors:  David H Goldberg; Jonathan D Victor; Esther P Gardner; Daniel Gardner
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2.  MEAnalyzer - a Spike Train Analysis Tool for Multi Electrode Arrays.

Authors:  Raha M Dastgheyb; Seung-Wan Yoo; Norman J Haughey
Journal:  Neuroinformatics       Date:  2020-01

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Journal:  Eur J Neurosci       Date:  2019-04-01       Impact factor: 3.386

4.  Effect of CB1 receptor blockade on food-reinforced responding and associated nucleus accumbens neuronal activity in rats.

Authors:  Giovanni Hernandez; Joseph F Cheer
Journal:  J Neurosci       Date:  2012-08-15       Impact factor: 6.167

5.  Presynaptic Mitochondria Volume and Abundance Increase during Development of a High-Fidelity Synapse.

Authors:  Connon I Thomas; Christian Keine; Satoko Okayama; Rachel Satterfield; Morgan Musgrove; Debbie Guerrero-Given; Naomi Kamasawa; Samuel M Young
Journal:  J Neurosci       Date:  2019-08-27       Impact factor: 6.167

6.  Information processing bottlenecks in macaque posterior parietal cortex: an attentional blink?

Authors:  Ryan T Maloney; Jaikishan Jayakumar; Ekaterina V Levichkina; Ivan N Pigarev; Trichur R Vidyasagar
Journal:  Exp Brain Res       Date:  2013-05-29       Impact factor: 1.972

7.  Visual acuity development and plasticity in the absence of sensory experience.

Authors:  Erin Kang; Severine Durand; Jocelyn J LeBlanc; Takao K Hensch; Chinfei Chen; Michela Fagiolini
Journal:  J Neurosci       Date:  2013-11-06       Impact factor: 6.167

8.  A microfluidic microelectrode array for simultaneous electrophysiology, chemical stimulation, and imaging of brain slices.

Authors:  Adina Scott; Keiko Weir; Curtis Easton; Wilson Huynh; William J Moody; Albert Folch
Journal:  Lab Chip       Date:  2013-02-21       Impact factor: 6.799

9.  Multichannel brain recordings in behaving Drosophila reveal oscillatory activity and local coherence in response to sensory stimulation and circuit activation.

Authors:  Angelique C Paulk; Yanqiong Zhou; Peter Stratton; Li Liu; Bruno van Swinderen
Journal:  J Neurophysiol       Date:  2013-07-17       Impact factor: 2.714

10.  Cortical Feedback Regulates Feedforward Retinogeniculate Refinement.

Authors:  Andrew D Thompson; Nathalie Picard; Lia Min; Michela Fagiolini; Chinfei Chen
Journal:  Neuron       Date:  2016-08-18       Impact factor: 17.173

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