Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
8
pubmed:dateCreated
2008-8-26
pubmed:abstractText
The reasons for using natural stimuli to study sensory function are quickly mounting, as recent studies have revealed important differences in neural responses to natural and artificial stimuli. However, natural stimuli typically contain strong correlations and are spherically asymmetric (i.e. stimulus intensities are not symmetrically distributed around the mean), and these statistical complexities can bias receptive field (RF) estimates when standard techniques such as spike-triggered averaging or reverse correlation are used. While a number of approaches have been developed to explicitly correct the bias due to stimulus correlations, there is no complementary technique to correct the bias due to stimulus asymmetries. Here, we develop a method for RF estimation that corrects reverse correlation RF estimates for the spherical asymmetries present in natural stimuli. Using simulated neural responses, we demonstrate how stimulus asymmetries can bias reverse-correlation RF estimates (even for uncorrelated stimuli) and illustrate how this bias can be removed by explicit correction. We demonstrate the utility of the asymmetry correction method under experimental conditions by estimating RFs from the responses of retinal ganglion cells to natural stimuli and using these RFs to predict responses to novel stimuli.
pubmed:commentsCorrections
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pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:chemical
pubmed:status
MEDLINE
pubmed:issn
1932-6203
pubmed:author
pubmed:issnType
Electronic
pubmed:volume
3
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
e3060
pubmed:dateRevised
2010-9-22
pubmed:meshHeading
pubmed:year
2008
pubmed:articleTitle
Estimating receptive fields from responses to natural stimuli with asymmetric intensity distributions.
pubmed:affiliation
RIKEN Brain Science Institute, Wako-shi, Saitama, Japan. lesica@zi.biologie.uni-muenchen.de
pubmed:publicationType
Journal Article, Research Support, Non-U.S. Gov't