Estimating receptive fields from responses to natural stimuli with asymmetric intensity distributions.
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. stimu...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Public Library of Science (PLoS)
2008-08-01
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| Series: | PLoS ONE |
| Online Access: | http://europepmc.org/articles/PMC2518112?pdf=render |
| _version_ | 1828520078938734592 |
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| author | Nicholas A Lesica Toshiyuki Ishii Garrett B Stanley Toshihiko Hosoya |
| author_facet | Nicholas A Lesica Toshiyuki Ishii Garrett B Stanley Toshihiko Hosoya |
| author_sort | Nicholas A Lesica |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-12-11T19:23:20Z |
| format | Article |
| id | doaj.art-996e8a1c08ac4e399567179691b1be91 |
| institution | Directory Open Access Journal |
| issn | 1932-6203 |
| language | English |
| last_indexed | 2024-12-11T19:23:20Z |
| publishDate | 2008-08-01 |
| publisher | Public Library of Science (PLoS) |
| record_format | Article |
| series | PLoS ONE |
| spelling | doaj.art-996e8a1c08ac4e399567179691b1be912022-12-22T00:53:27ZengPublic Library of Science (PLoS)PLoS ONE1932-62032008-08-0138e306010.1371/journal.pone.0003060Estimating receptive fields from responses to natural stimuli with asymmetric intensity distributions.Nicholas A LesicaToshiyuki IshiiGarrett B StanleyToshihiko HosoyaThe 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.http://europepmc.org/articles/PMC2518112?pdf=render |
| spellingShingle | Nicholas A Lesica Toshiyuki Ishii Garrett B Stanley Toshihiko Hosoya Estimating receptive fields from responses to natural stimuli with asymmetric intensity distributions. PLoS ONE |
| title | Estimating receptive fields from responses to natural stimuli with asymmetric intensity distributions. |
| title_full | Estimating receptive fields from responses to natural stimuli with asymmetric intensity distributions. |
| title_fullStr | Estimating receptive fields from responses to natural stimuli with asymmetric intensity distributions. |
| title_full_unstemmed | Estimating receptive fields from responses to natural stimuli with asymmetric intensity distributions. |
| title_short | Estimating receptive fields from responses to natural stimuli with asymmetric intensity distributions. |
| title_sort | estimating receptive fields from responses to natural stimuli with asymmetric intensity distributions |
| url | http://europepmc.org/articles/PMC2518112?pdf=render |
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