Literature DB >> 12435922

Noise, not stimulus entropy, determines neural information rate.

Alexander Borst1.   

Abstract

In the quest for deciphering the neural code, theoretical advances were made which allow for the determination of the information rate inherent in the spike trains of nerve cells. However, up to now, the dependence of the information rate on stimulus parameters has not been studied in any neuron in a systematic way. Here, I investigate the information carried by the spike trains of H1, a motion-sensitive visual interneuron of the blowfly (Calliphora vicina) using a moving grating as a stimulus. Stimulus parameters fall in two classes: those that have only a minor effect on the information rate like increasing the frequency bandwidth or the maximum amplitude of the stimulus velocity, and those which dramatically affect the neural information rate, like varying the spatial size or the contrast of the visual pattern being moved. It appears that, for a broad range of complex stimuli, the neuron covers the stimulus with its whole response repertoire regardless of the stimulus entropy, with the information rate being limited by the noise of the stimulus and the neural hardware.

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Mesh:

Year:  2003        PMID: 12435922     DOI: 10.1023/a:1021172200868

Source DB:  PubMed          Journal:  J Comput Neurosci        ISSN: 0929-5313            Impact factor:   1.621


  13 in total

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Authors:  W Bair
Journal:  Curr Opin Neurobiol       Date:  1999-08       Impact factor: 6.627

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Authors:  A Borst; F E Theunissen
Journal:  Nat Neurosci       Date:  1999-11       Impact factor: 24.884

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Authors:  A K Warzecha; J Kretzberg; M Egelhaaf
Journal:  J Neurosci       Date:  2000-12-01       Impact factor: 6.167

4.  Effects of mean firing on neural information rate.

Authors:  A Borst; J Haag
Journal:  J Comput Neurosci       Date:  2001 Mar-Apr       Impact factor: 1.621

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Authors:  W Bair; C Koch
Journal:  Neural Comput       Date:  1996-08-15       Impact factor: 2.026

6.  Light adaptation and reliability in blowfly photoreceptors.

Authors:  R R de Ruyter van Steveninck; S B Laughlin
Journal:  Int J Neural Syst       Date:  1996-09       Impact factor: 5.866

7.  Reproducibility and variability in neural spike trains.

Authors:  R R de Ruyter van Steveninck; G D Lewen; S P Strong; R Koberle; W Bialek
Journal:  Science       Date:  1997-03-21       Impact factor: 47.728

8.  Effects of adaptation on neural coding by primary sensory interneurons in the cricket cercal system.

Authors:  H Clague; F Theunissen; J P Miller
Journal:  J Neurophysiol       Date:  1997-01       Impact factor: 2.714

9.  Reliability of spike timing in neocortical neurons.

Authors:  Z F Mainen; T J Sejnowski
Journal:  Science       Date:  1995-06-09       Impact factor: 47.728

10.  Adaptation and the temporal delay filter of fly motion detectors.

Authors:  R A Harris; D C O'Carroll; S B Laughlin
Journal:  Vision Res       Date:  1999-08       Impact factor: 1.886

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  8 in total

1.  Naturalistic auditory contrast improves spectrotemporal coding in the cat inferior colliculus.

Authors:  Monty A Escabí; Lee M Miller; Heather L Read; Christoph E Schreiner
Journal:  J Neurosci       Date:  2003-12-17       Impact factor: 6.167

2.  Adaptation without parameter change: Dynamic gain control in motion detection.

Authors:  Alexander Borst; Virginia L Flanagin; Haim Sompolinsky
Journal:  Proc Natl Acad Sci U S A       Date:  2005-04-15       Impact factor: 11.205

3.  Propagation of photon noise and information transfer in visual motion detection.

Authors:  Lei Shi; Alexander Borst
Journal:  J Comput Neurosci       Date:  2006-04-22       Impact factor: 1.621

4.  Correlation versus gradient type motion detectors: the pros and cons.

Authors:  Alexander Borst
Journal:  Philos Trans R Soc Lond B Biol Sci       Date:  2007-03-29       Impact factor: 6.237

5.  Coding efficiency of fly motion processing is set by firing rate, not firing precision.

Authors:  Deusdedit Lineu Spavieri; Hubert Eichner; Alexander Borst
Journal:  PLoS Comput Biol       Date:  2010-07-22       Impact factor: 4.475

6.  Closed-loop response properties of a visual interneuron involved in fly optomotor control.

Authors:  Naveed Ejaz; Holger G Krapp; Reiko J Tanaka
Journal:  Front Neural Circuits       Date:  2013-03-27       Impact factor: 3.492

7.  The natural variation of a neural code.

Authors:  Yoav Kfir; Ittai Renan; Elad Schneidman; Ronen Segev
Journal:  PLoS One       Date:  2012-03-12       Impact factor: 3.240

8.  Spatial vision in insects is facilitated by shaping the dynamics of visual input through behavioral action.

Authors:  Martin Egelhaaf; Norbert Boeddeker; Roland Kern; Rafael Kurtz; Jens P Lindemann
Journal:  Front Neural Circuits       Date:  2012-12-20       Impact factor: 3.492

  8 in total

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