July 2013
Volume 13, Issue 9
Free
Vision Sciences Society Annual Meeting Abstract  |   July 2013
Population-code representations of natural images across human visual areas
Author Affiliations
  • Linda Henriksson
    MRC Cognition and Brain Sciences Unit, Cambridge, UK\nBrain Research Unit, O.V. Lounasmaa Laboratory, Aalto University, Espoo, Finland
  • Seyed-Mahdi Khaligh-Razavi
    MRC Cognition and Brain Sciences Unit, Cambridge, UK
  • Nikolaus Kriegeskorte
    MRC Cognition and Brain Sciences Unit, Cambridge, UK
Journal of Vision July 2013, Vol.13, 1035. doi:10.1167/13.9.1035
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      Linda Henriksson, Seyed-Mahdi Khaligh-Razavi, Nikolaus Kriegeskorte; Population-code representations of natural images across human visual areas. Journal of Vision 2013;13(9):1035. doi: 10.1167/13.9.1035.

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      © ARVO (1962-2015); The Authors (2016-present)

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Abstract

Visual information is represented in multiple areas in the human brain. The primary visual cortex (V1) is typically associated with representing low-level image properties of the visual stimuli, whereas higher-level areas encode more abstract information, such as object category. What is not well understood is how the visual information is represented in the intermediate-level visual areas, such as visual areas V2 and V4. Here we used representational similarity analysis (RSA; Kriegeskorte et al. 2008) to characterize population-code representations of natural images across hierarchy of visual areas (for details on the fMRI data, see Kay et al. 2008; Naselaris et al. 2009). We found a gradual change in the representational similarity structure across the visual areas V1, V2, V3, V4 and LO (lateral occipital area). The representations in V3A and V3B were most similar to that in V3 and were more distinct from the representations in V4 and LO. We aim to characterize the visual features that drive these differences in the representations across the hierarchy of visual areas and to relate the results to computational models of visual processing.

Meeting abstract presented at VSS 2013

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