Linked Life Data

7670670

Source:http://linkedlifedata.com/resource/pubmed/id/7670670

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
1
pubmed:dateCreated
1995-10-17
pubmed:abstractText
Spontaneous neuronal activity and synaptic noise are well-known phenomena, but their biological significance has not yet been assessed. Using a computer model of the olfactory cortex we show that such activity, expressed as temporal noise in the model, can reduce recall time in associative memory tasks. We investigate both additive and multiplicative noise, and find optimal noise levels for which the recall time reaches a minimum. In addition, we demonstrate that noise can induce state transitions, such that the system is pushed from one attractor state to another. For high enough noise levels the dynamics can change dramatically and, for example, switch from an oscillatory to a chaos-like behavior. We discuss these findings in light of their significance for neural information processing.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:month
Mar
pubmed:issn
0129-0657
pubmed:author
pubmed:issnType
Print
pubmed:volume
6
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
19-29
pubmed:dateRevised
2006-11-15
pubmed:meshHeading
pubmed:year
1995
pubmed:articleTitle
Noise-enhanced performance in a cortical associative memory model.
pubmed:affiliation
Department of Numerical Analysis and Computing Science, Royal Institute of Technology, Stockholm, Sweden.
pubmed:publicationType
Journal Article, Research Support, Non-U.S. Gov't