A Biological Neural Network of Visual Cell Responses: Static and Motion Processing
Autor(a) principal: | |
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Data de Publicação: | 1997 |
Outros Autores: | , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Journal of the Brazilian Computer Society |
Texto Completo: | http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0104-65001997000200002 |
Resumo: | This paper integrates knowledge from physiology and psychophysics (i.e., visual perception) to propose a biological neural network model of cortical visual cell responses. We attempt to provide a model of how retinal and cortical cell interactions are able to detect static image luminance discontinuities -- such as at edges --, as well as moving luminance discontinuities -- i.e., motion stimuli. We address how important cortical cells known as simple cells combine retinal and thalamic signals to produce an effective contrast detection mechanism. An extension of the static model is then discussed in light of both psychophysical and physiological data on motion processing. The motion extension suggests a role for another important class of cortical cells known as complex cells. The static model is evaluated through a series of computer simulations that probe its capabilities with natural images, synthetic images (to assess noise tolerance), as well as images that allow us to compare the model's behavior with physiological results. The motion processing capabilities of the extended scheme are also evaluated through computer simulations. We suggest that this type of investigation can be used to attempt to advance our understanding of brain function, as well as devise powerful computational schemes that can be incorporated into artificial vision systems |
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Journal of the Brazilian Computer Society |
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spelling |
A Biological Neural Network of Visual Cell Responses: Static and Motion Processingedge detectionmotion detectionneural networksvisionThis paper integrates knowledge from physiology and psychophysics (i.e., visual perception) to propose a biological neural network model of cortical visual cell responses. We attempt to provide a model of how retinal and cortical cell interactions are able to detect static image luminance discontinuities -- such as at edges --, as well as moving luminance discontinuities -- i.e., motion stimuli. We address how important cortical cells known as simple cells combine retinal and thalamic signals to produce an effective contrast detection mechanism. An extension of the static model is then discussed in light of both psychophysical and physiological data on motion processing. The motion extension suggests a role for another important class of cortical cells known as complex cells. The static model is evaluated through a series of computer simulations that probe its capabilities with natural images, synthetic images (to assess noise tolerance), as well as images that allow us to compare the model's behavior with physiological results. The motion processing capabilities of the extended scheme are also evaluated through computer simulations. We suggest that this type of investigation can be used to attempt to advance our understanding of brain function, as well as devise powerful computational schemes that can be incorporated into artificial vision systemsSociedade Brasileira de Computação1997-07-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S0104-65001997000200002Journal of the Brazilian Computer Society v.4 n.1 1997reponame:Journal of the Brazilian Computer Societyinstname:Sociedade Brasileira de Computação (SBC)instacron:UFRGS10.1590/S0104-65001997000200002info:eu-repo/semantics/openAccessPessoa,LuizGrunewald,AlexanderNeumann,HeikoLittmann,Ennoeng1998-10-07T00:00:00Zoai:scielo:S0104-65001997000200002Revistahttps://journal-bcs.springeropen.com/PUBhttps://old.scielo.br/oai/scielo-oai.phpjbcs@icmc.sc.usp.br1678-48040104-6500opendoar:1998-10-07T00:00Journal of the Brazilian Computer Society - Sociedade Brasileira de Computação (SBC)false |
dc.title.none.fl_str_mv |
A Biological Neural Network of Visual Cell Responses: Static and Motion Processing |
title |
A Biological Neural Network of Visual Cell Responses: Static and Motion Processing |
spellingShingle |
A Biological Neural Network of Visual Cell Responses: Static and Motion Processing Pessoa,Luiz edge detection motion detection neural networks vision |
title_short |
A Biological Neural Network of Visual Cell Responses: Static and Motion Processing |
title_full |
A Biological Neural Network of Visual Cell Responses: Static and Motion Processing |
title_fullStr |
A Biological Neural Network of Visual Cell Responses: Static and Motion Processing |
title_full_unstemmed |
A Biological Neural Network of Visual Cell Responses: Static and Motion Processing |
title_sort |
A Biological Neural Network of Visual Cell Responses: Static and Motion Processing |
author |
Pessoa,Luiz |
author_facet |
Pessoa,Luiz Grunewald,Alexander Neumann,Heiko Littmann,Enno |
author_role |
author |
author2 |
Grunewald,Alexander Neumann,Heiko Littmann,Enno |
author2_role |
author author author |
dc.contributor.author.fl_str_mv |
Pessoa,Luiz Grunewald,Alexander Neumann,Heiko Littmann,Enno |
dc.subject.por.fl_str_mv |
edge detection motion detection neural networks vision |
topic |
edge detection motion detection neural networks vision |
description |
This paper integrates knowledge from physiology and psychophysics (i.e., visual perception) to propose a biological neural network model of cortical visual cell responses. We attempt to provide a model of how retinal and cortical cell interactions are able to detect static image luminance discontinuities -- such as at edges --, as well as moving luminance discontinuities -- i.e., motion stimuli. We address how important cortical cells known as simple cells combine retinal and thalamic signals to produce an effective contrast detection mechanism. An extension of the static model is then discussed in light of both psychophysical and physiological data on motion processing. The motion extension suggests a role for another important class of cortical cells known as complex cells. The static model is evaluated through a series of computer simulations that probe its capabilities with natural images, synthetic images (to assess noise tolerance), as well as images that allow us to compare the model's behavior with physiological results. The motion processing capabilities of the extended scheme are also evaluated through computer simulations. We suggest that this type of investigation can be used to attempt to advance our understanding of brain function, as well as devise powerful computational schemes that can be incorporated into artificial vision systems |
publishDate |
1997 |
dc.date.none.fl_str_mv |
1997-07-01 |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0104-65001997000200002 |
url |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0104-65001997000200002 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
10.1590/S0104-65001997000200002 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
text/html |
dc.publisher.none.fl_str_mv |
Sociedade Brasileira de Computação |
publisher.none.fl_str_mv |
Sociedade Brasileira de Computação |
dc.source.none.fl_str_mv |
Journal of the Brazilian Computer Society v.4 n.1 1997 reponame:Journal of the Brazilian Computer Society instname:Sociedade Brasileira de Computação (SBC) instacron:UFRGS |
instname_str |
Sociedade Brasileira de Computação (SBC) |
instacron_str |
UFRGS |
institution |
UFRGS |
reponame_str |
Journal of the Brazilian Computer Society |
collection |
Journal of the Brazilian Computer Society |
repository.name.fl_str_mv |
Journal of the Brazilian Computer Society - Sociedade Brasileira de Computação (SBC) |
repository.mail.fl_str_mv |
jbcs@icmc.sc.usp.br |
_version_ |
1754734669485572096 |