Linked Life Data

17023650

Source:http://linkedlifedata.com/resource/pubmed/id/17023650

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
5796
pubmed:dateCreated
2006-10-6
pubmed:abstractText
Neuronal networks in vivo are characterized by considerable spontaneous activity, which is highly complex and intrinsically generated by a combination of single-cell electrophysiological properties and recurrent circuits. As seen, for example, during waking compared with being asleep or under anesthesia, neuronal responsiveness differs, concomitant with the pattern of spontaneous brain activity. This pattern, which defines the state of the network, has a dramatic influence on how local networks are engaged by inputs and, therefore, on how information is represented. We review here experimental and theoretical evidence of the decisive role played by stochastic network states in sensory responsiveness with emphasis on activated states such as waking. From single cells to networks, experiments and computational models have addressed the relation between neuronal responsiveness and the complex spatiotemporal patterns of network activity. The understanding of the relation between network state dynamics and information representation is a major challenge that will require developing, in conjunction, specific experimental paradigms and theoretical frameworks.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:month
Oct
pubmed:issn
1095-9203
pubmed:author
pubmed:issnType
Electronic
pubmed:day
6
pubmed:volume
314
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
85-90
pubmed:dateRevised
2007-3-19
pubmed:meshHeading
pubmed:year
2006
pubmed:articleTitle
Neuronal computations with stochastic network states.
pubmed:affiliation
Integrative and Computational Neuroscience Unit (UNIC), CNRS, Gif sur Yvette, France. Destexhe@iaf.cnrs-gif.fr
pubmed:publicationType
Journal Article, Review, Research Support, Non-U.S. Gov't, Research Support, N.I.H., Extramural