Linked Life Data

11308875

Source:http://linkedlifedata.com/resource/pubmed/id/11308875

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
4 Pt 1
pubmed:dateCreated
2001-4-19
pubmed:abstractText
Neural networks with asymmetric synaptic connections (w(ij) not equal to w(ji)) display a broad range of dynamical behavior including fixed point, periodic, and "chaotic" trajectories. Previous work has shown that such networks undergo an order-chaos phase transition as various network parameters, such as the connectivity or the degree of asymmetry, are changed. Here, using an information theoretic approach, we present results which suggest that neurons are able to communicate information to each other most effectively in networks that are near the order-chaos transition. We then extend the model to incorporate some biologically relevant features.
pubmed:grant
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:month
Apr
pubmed:issn
1539-3755
pubmed:author
pubmed:issnType
Print
pubmed:volume
63
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
041905
pubmed:dateRevised
2007-11-14
pubmed:meshHeading
pubmed:year
2001
pubmed:articleTitle
Mutual information in a dilute, asymmetric neural network model.
pubmed:affiliation
Department of Physics, University of California at Berkeley, Berkeley, CA 94720, USA.
pubmed:publicationType
Journal Article, Research Support, U.S. Gov't, P.H.S.