Literature DB >> 34354118

Neural burst codes disguised as rate codes.

Ezekiel Williams1, Alexandre Payeur2, Albert Gidon3, Richard Naud4,5.   

Abstract

The burst coding hypothesis posits that the occurrence of sudden high-frequency patterns of action potentials constitutes a salient syllable of the neural code. Many neurons, however, do not produce clearly demarcated bursts, an observation invoked to rule out the pervasiveness of this coding scheme across brain areas and cell types. Here we ask how detrimental ambiguous spike patterns, those that are neither clearly bursts nor isolated spikes, are for neuronal information transfer. We addressed this question using information theory and computational simulations. By quantifying how information transmission depends on firing statistics, we found that the information transmitted is not strongly influenced by the presence of clearly demarcated modes in the interspike interval distribution, a feature often used to identify the presence of burst coding. Instead, we found that neurons having unimodal interval distributions were still able to ascribe different meanings to bursts and isolated spikes. In this regime, information transmission depends on dynamical properties of the synapses as well as the length and relative frequency of bursts. Furthermore, we found that common metrics used to quantify burstiness were unable to predict the degree with which bursts could be used to carry information. Our results provide guiding principles for the implementation of coding strategies based on spike-timing patterns, and show that even unimodal firing statistics can be consistent with a bivariate neural code.
© 2021. The Author(s).

Entities:  

Year:  2021        PMID: 34354118     DOI: 10.1038/s41598-021-95037-z

Source DB:  PubMed          Journal:  Sci Rep        ISSN: 2045-2322            Impact factor:   4.379


  49 in total

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Journal:  Nat Rev Neurosci       Date:  2004-01       Impact factor: 34.870

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Journal:  J Physiol       Date:  2008-05-15       Impact factor: 5.182

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Authors:  David J Herzfeld; Pavan A Vaswani; Mollie K Marko; Reza Shadmehr
Journal:  Science       Date:  2014-08-14       Impact factor: 47.728

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Authors:  Guy Doron; Moritz von Heimendahl; Peter Schlattmann; Arthur R Houweling; Michael Brecht
Journal:  Neuron       Date:  2014-02-05       Impact factor: 17.173

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Journal:  Exp Brain Res       Date:  1971-06-29       Impact factor: 1.972

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Journal:  J Neurosci       Date:  1994-05       Impact factor: 6.167

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Authors:  D Contreras; R Curró Dossi; M Steriade
Journal:  J Physiol       Date:  1993-10       Impact factor: 5.182

9.  Perirhinal input to neocortical layer 1 controls learning.

Authors:  Guy Doron; Jiyun N Shin; Naoya Takahashi; Moritz Drüke; Christina Bocklisch; Salina Skenderi; Lisa de Mont; Maria Toumazou; Julia Ledderose; Michael Brecht; Richard Naud; Matthew E Larkum
Journal:  Science       Date:  2020-12-18       Impact factor: 47.728

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Authors:  Janina Kowalski; Jian Gan; Peter Jonas; Alejandro J Pernía-Andrade
Journal:  Hippocampus       Date:  2015-12-14       Impact factor: 3.899

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  1 in total

1.  Noise-induced network bursts and coherence in a calcium-mediated neural network.

Authors:  Na Yu; Gurpreet Jagdev; Michelle Morgovsky
Journal:  Heliyon       Date:  2021-12-20
  1 in total

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