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Cortical representation of information about visual attributes: One network or many?

  • Youping Xiao
  • , Ravi Rao
  • , Guilermo Cecchi
  • , Ehud Kaplan

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

3 Scopus citations

Abstract

Information about various visual attributes, such as orientation or color, is represented in the primate striate cortex (V1) before reaching extrastriate cortices. Previous studies, using single- or multi-unit recordings, have reached conflicting conclusions regarding the question of whether these different attributes are represented by separate populations of neurons in V1. We addressed this question with imaging of intrinsic optical signals from macaque V1. The animals viewed either full field (uniform) color stimuli or drifting black and white gratings of various orientations. We used the Support Vector Machine (SVM) algorithm to determine the relative amount of information about a given attribute at each cortical location. We found that each single-trial image contained significant amounts of information about color or orientation. The information about either attribute was distributed unevenly across V1. Color information was concentrated in small regions of high information density, surrounded by large regions of low information density, while orientation information showed the opposite pattern. Our results are consistent with the hypothesis that color and orientation are represented in different compartments in V1.

Original languageEnglish
Title of host publicationThe 2007 International Joint Conference on Neural Networks, IJCNN 2007 Conference Proceedings
Pages1785-1789
Number of pages5
DOIs
StatePublished - 2007
Event2007 International Joint Conference on Neural Networks, IJCNN 2007 - Orlando, FL, United States
Duration: 12 Aug 200717 Aug 2007

Publication series

NameIEEE International Conference on Neural Networks - Conference Proceedings
ISSN (Print)1098-7576

Conference

Conference2007 International Joint Conference on Neural Networks, IJCNN 2007
Country/TerritoryUnited States
CityOrlando, FL
Period12/08/0717/08/07

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