Literature DB >> 21792610

An introductory review of information theory in the context of computational neuroscience.

Mark D McDonnell1, Shiro Ikeda, Jonathan H Manton.   

Abstract

This article introduces several fundamental concepts in information theory from the perspective of their origins in engineering. Understanding such concepts is important in neuroscience for two reasons. Simply applying formulae from information theory without understanding the assumptions behind their definitions can lead to erroneous results and conclusions. Furthermore, this century will see a convergence of information theory and neuroscience; information theory will expand its foundations to incorporate more comprehensively biological processes thereby helping reveal how neuronal networks achieve their remarkable information processing abilities.

Mesh:

Year:  2011        PMID: 21792610     DOI: 10.1007/s00422-011-0451-9

Source DB:  PubMed          Journal:  Biol Cybern        ISSN: 0340-1200            Impact factor:   2.086


  9 in total

1.  Neural encoding schemes of tactile information in afferent activity of the vibrissal system.

Authors:  Fernando D Farfán; Ana L Albarracín; Carmelo J Felice
Journal:  J Comput Neurosci       Date:  2012-06-22       Impact factor: 1.621

Review 2.  The Cognitive Lens: a primer on conceptual tools for analysing information processing in developmental and regenerative morphogenesis.

Authors:  Santosh Manicka; Michael Levin
Journal:  Philos Trans R Soc Lond B Biol Sci       Date:  2019-06-10       Impact factor: 6.237

3.  Understanding Design Features of Music and Language: The Choric/Dialogic Distinction.

Authors:  Felix Haiduk; W Tecumseh Fitch
Journal:  Front Psychol       Date:  2022-04-22

4.  Optimum neural tuning curves for information efficiency with rate coding and finite-time window.

Authors:  Fang Han; Zhijie Wang; Hong Fan; Xiaojuan Sun
Journal:  Front Comput Neurosci       Date:  2015-06-03       Impact factor: 2.380

5.  A consensus layer V pyramidal neuron can sustain interpulse-interval coding.

Authors:  Chandan Singh; William B Levy
Journal:  PLoS One       Date:  2017-07-13       Impact factor: 3.240

6.  Determine Neuronal Tuning Curves by Exploring Optimum Firing Rate Distribution for Information Efficiency.

Authors:  Fang Han; Zhijie Wang; Hong Fan
Journal:  Front Comput Neurosci       Date:  2017-02-21       Impact factor: 2.380

7.  High-Frequency Synchronization Improves Firing Rate Contrast and Information Transmission Efficiency in E/I Neuronal Networks.

Authors:  Fang Han; Zhijie Wang; Hong Fan; Yaopeng Zhang
Journal:  Neural Plast       Date:  2020-11-09       Impact factor: 3.599

8.  Robust cone-mediated signaling persists late into rod photoreceptor degeneration.

Authors:  Miranda L Scalabrino; Mishek Thapa; Lindsey A Chew; Esther Zhang; Jason Xu; Alapakkam P Sampath; Jeannie Chen; Greg D Field
Journal:  Elife       Date:  2022-08-30       Impact factor: 8.713

9.  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

  9 in total

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