Linked Life Data

12929915

Source:http://linkedlifedata.com/resource/pubmed/id/12929915

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
1-2
pubmed:dateCreated
2003-8-21
pubmed:abstractText
The temporal patterning of neuronal activity may play a substantial role in the representation of sensory stimuli. One particular hypothesis suggests that visual stimuli are represented by the temporal evolution of the instantaneous firing rate averaged over a whole population of neurons. Using an implementation in a cortical type network with lateral interactions, we could previously show that this scheme can be successfully applied to a pattern recognition task. Here, we use a large set of artificially generated stimuli to investigate the coding properties of the network in detail. The temporal population code generated by the network is intrinsically invariant to stimulus translations. We show that the encoding is invariant to small deformations of the stimuli and robust with respect to static and dynamic variations in synaptic strength of the lateral connections in the network. Furthermore, we present several measures which indicate that the encoding maps the stimuli into a high-dimensional space. These results show that a temporal population code is a promising approach for the encoding of relevant stimulus properties while simultaneously discarding the irrelevant information.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:issn
0334-1763
pubmed:author
pubmed:issnType
Print
pubmed:volume
14
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
21-33
pubmed:dateRevised
2007-11-15
pubmed:meshHeading
pubmed:year
2003
pubmed:articleTitle
Properties of a temporal population code.
pubmed:affiliation
Institute of Neuroinformatics, University/ETH Zürich, Switzerland. rwyss@ini.unizh.ch
pubmed:publicationType
Journal Article, Research Support, Non-U.S. Gov't