Open source tools for the information theoretic analysis of neural data

Ince, R. A.A. , Mazzoni, A., Petersen, R. S. and Panzeri, S. (2010) Open source tools for the information theoretic analysis of neural data. Frontiers in Neuroscience, 4(1), pp. 62-70. (doi: 10.3389/neuro.01.011.2010)

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The recent and rapid development of open source software tools for the analysis of neurophysiological datasets consisting of simultaneous multiple recordings of spikes, field potentials and other neural signals holds the promise for a significant advance in the standardization, transparency, quality, reproducibility and variety of techniques used to analyze neurophysiological data and for the integration of information obtained at different spatial and temporal scales. In this review we focus on recent advances in open source toolboxes for the information theoretic analysis of neural responses. We also present examples of their use to investigate the role of spike timing precision, correlations across neurons, and field potential fluctuations in the encoding of sensory information. These information toolboxes, available both in MATLAB and Python programming environments, hold the potential to enlarge the domain of application of information theory to neuroscience and to lead to new discoveries about how neurons encode and transmit information.

Item Type:Articles
Glasgow Author(s) Enlighten ID:Panzeri, Professor Stefano and Ince, Dr Robin
Authors: Ince, R. A.A., Mazzoni, A., Petersen, R. S., and Panzeri, S.
College/School:College of Medical Veterinary and Life Sciences > School of Psychology & Neuroscience
College of Science and Engineering > School of Psychology
Journal Name:Frontiers in Neuroscience
Publisher:Frontiers Research Foundation
ISSN (Online):1662-4548
Copyright Holders:Copyright © 2010 The Authors
First Published:First published in Frontiers in Neuroscience 4(1):62-70
Publisher Policy:Reproduced in accordance with the copyright policy of the publisher

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