Literature DB >> 25689988

Cortical Specializations Underlying Fast Computations.

Maxim Volgushev1.   

Abstract

The time course of behaviorally relevant environmental events sets temporal constraints on neuronal processing. How does the mammalian brain make use of the increasingly complex networks of the neocortex, while making decisions and executing behavioral reactions within a reasonable time? The key parameter determining the speed of computations in neuronal networks is a time interval that neuronal ensembles need to process changes at their input and communicate results of this processing to downstream neurons. Theoretical analysis identified basic requirements for fast processing: use of neuronal populations for encoding, background activity, and fast onset dynamics of action potentials in neurons. Experimental evidence shows that populations of neocortical neurons fulfil these requirements. Indeed, they can change firing rate in response to input perturbations very quickly, within 1 to 3 ms, and encode high-frequency components of the input by phase-locking their spiking to frequencies up to 300 to 1000 Hz. This implies that time unit of computations by cortical ensembles is only few, 1 to 3 ms, which is considerably faster than the membrane time constant of individual neurons. The ability of cortical neuronal ensembles to communicate on a millisecond time scale allows for complex, multiple-step processing and precise coordination of neuronal activity in parallel processing streams, while keeping the speed of behavioral reactions within environmentally set temporal constraints.
© The Author(s) 2015.

Entities:  

Keywords:  action potential; cortical ensembles; cortical processing; firing rate; frequency response; neocortex; pyramidal neurons; spike encoding

Mesh:

Year:  2015        PMID: 25689988      PMCID: PMC4924811          DOI: 10.1177/1073858415571539

Source DB:  PubMed          Journal:  Neuroscientist        ISSN: 1073-8584            Impact factor:   7.519


  97 in total

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4.  Dynamics of the instantaneous firing rate in response to changes in input statistics.

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Authors:  G Baranauskas; A Mukovskiy; F Wolf; M Volgushev
Journal:  Neuroscience       Date:  2010-03-06       Impact factor: 3.590

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Authors:  Thomas Klausberger; Peter J Magill; László F Márton; J David B Roberts; Philip M Cobden; György Buzsáki; Peter Somogyi
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Authors:  Yuguo Yu; Yousheng Shu; David A McCormick
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