Document Detail

Synaptic information transfer in computer models of neocortical columns.
MedLine Citation:
PMID:  20556639     Owner:  NLM     Status:  MEDLINE    
Understanding the direction and quantity of information flowing in neuronal networks is a fundamental problem in neuroscience. Brains and neuronal networks must at the same time store information about the world and react to information in the world. We sought to measure how the activity of the network alters information flow from inputs to output patterns. Using neocortical column neuronal network simulations, we demonstrated that networks with greater internal connectivity reduced input/output correlations from excitatory synapses and decreased negative correlations from inhibitory synapses, measured by Kendall's τ correlation. Both of these changes were associated with reduction in information flow, measured by normalized transfer entropy (nTE). Information handling by the network reflected the degree of internal connectivity. With no internal connectivity, the feedforward network transformed inputs through nonlinear summation and thresholding. With greater connectivity strength, the recurrent network translated activity and information due to contribution of activity from intrinsic network dynamics. This dynamic contribution amounts to added information drawn from that stored in the network. At still higher internal synaptic strength, the network corrupted the external information, producing a state where little external information came through. The association of increased information retrieved from the network with increased gamma power supports the notion of gamma oscillations playing a role in information processing.
Samuel A Neymotin; Kimberle M Jacobs; André A Fenton; William W Lytton
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Publication Detail:
Type:  Journal Article; Research Support, N.I.H., Extramural; Research Support, U.S. Gov't, Non-P.H.S.     Date:  2010-06-17
Journal Detail:
Title:  Journal of computational neuroscience     Volume:  30     ISSN:  1573-6873     ISO Abbreviation:  J Comput Neurosci     Publication Date:  2011 Feb 
Date Detail:
Created Date:  2011-02-17     Completed Date:  2011-06-03     Revised Date:  2014-09-21    
Medline Journal Info:
Nlm Unique ID:  9439510     Medline TA:  J Comput Neurosci     Country:  United States    
Other Details:
Languages:  eng     Pagination:  69-84     Citation Subset:  IM    
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MeSH Terms
Action Potentials / physiology
Brain / anatomy & histology,  physiology
Computer Simulation*
Information Theory*
Models, Neurological*
Neocortex / physiology*
Nerve Net / cytology,  physiology
Neurons / classification,  physiology*
Spectrum Analysis
Synapses / physiology*
Time Factors
alpha-Amino-3-hydroxy-5-methyl-4-isoxazolepropionic Acid / metabolism
gamma-Aminobutyric Acid / metabolism
Grant Support
MH057068/MH/NIMH NIH HHS; MH082417/MH/NIMH NIH HHS; R01 MH057068/MH/NIMH NIH HHS; R01 MH057068-10/MH/NIMH NIH HHS; R01 MH084038/MH/NIMH NIH HHS; R21 MH082417/MH/NIMH NIH HHS; R21 MH082417-01A1/MH/NIMH NIH HHS
Reg. No./Substance:
56-12-2/gamma-Aminobutyric Acid; 77521-29-0/alpha-Amino-3-hydroxy-5-methyl-4-isoxazolepropionic Acid

From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine

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