Literature DB >> 17296260

Quantifying the information transmitted in a single stimulus.

Michele Bezzi1.   

Abstract

Information theory - in particular mutual information- has been widely used to investigate neural processing in various brain areas. Shannon mutual information quantifies how much information is, on average, contained in a set of neural activities about a set of stimuli. To extend a similar approach to single stimulus encoding, we need to introduce a quantity specific for a single stimulus. This quantity has been defined in literature by four different measures, but none of them satisfies the same intuitive properties (non-negativity, additivity), that characterize mutual information. We present here a detailed analysis of the different meanings and properties of these four definitions. We show that all these measures satisfy, at least, a weaker additivity condition, i.e. limited to the response set. This allows us to use them for analysing correlated coding, as we illustrate in a toy-example from hippocampal place cells.

Mesh:

Year:  2006        PMID: 17296260     DOI: 10.1016/j.biosystems.2006.04.009

Source DB:  PubMed          Journal:  Biosystems        ISSN: 0303-2647            Impact factor:   1.973


  3 in total

1.  Synergy from silence in a combinatorial neural code.

Authors:  Elad Schneidman; Jason L Puchalla; Ronen Segev; Robert A Harris; William Bialek; Michael J Berry
Journal:  J Neurosci       Date:  2011-11-02       Impact factor: 6.167

2.  The concepts of representation and information in explanatory theories of human behavior.

Authors:  Renato T Ramos
Journal:  Front Psychol       Date:  2014-09-16

3.  The effect of inhibition on rate code efficiency indicators.

Authors:  Tomas Barta; Lubomir Kostal
Journal:  PLoS Comput Biol       Date:  2019-12-02       Impact factor: 4.475

  3 in total

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