December 2008
Volume 8, Issue 17
Free
OSA Fall Vision Meeting Abstract  |   December 2008
Inferring population responses in human visual cortex with classification analysis
Author Affiliations
  • Justin L. Gardner
    Laboratory for Cognitive Brain Mapping, RIKEN Brain Science Institute, Wako, Saitama, Japan, and Department of Psychology and Center for Neural Science, New York University, New York, NY, USA
  • Pei Sun
    Laboratory for Cognitive Brain Mapping, RIKEN Brain Science Institute, Saitama, Japan
  • Keiji Tanaka
    Laboratory for Cognitive Brain Mapping, RIKEN Brain Science Institute, Hirosawa, Wako, Saitama, Japan
  • David J. Heeger
    Department of Psychology and Center for Neural Science, New York University, New York, NY, USA
  • Kang Cheng
    Support Unit for Functional Magnetic Resonance Imaging and Laboratory for Cognitive Brain Mapping, RIKEN Brain Science Institute, Hirosawa, Wako, Saitama, Japan
Journal of Vision December 2008, Vol.8, 34. doi:10.1167/8.17.34
  • Views
  • Share
  • Tools
    • Alerts
      ×
      This feature is available to Subscribers Only
      Sign In or Create an Account ×
    • Get Citation

      Justin L. Gardner, Pei Sun, Keiji Tanaka, David J. Heeger, Kang Cheng; Inferring population responses in human visual cortex with classification analysis. Journal of Vision 2008;8(17):34. doi: 10.1167/8.17.34.

      Download citation file:


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

      ×
  • Supplements
Abstract

How the joint activity of many neurons with different selectivities represent visual stimuli is of key importance to understanding visual perception and visually guided behavior, yet most tools for probing these response properties in human visual cortex have been severely limited due to their coarse spatial-resolution. Conventional sized functional magnetic resonance imaging (fMRI) voxels (3×3×3 mm) are thought to encompass many dozens of cortical columns containing neurons with different specificities for basic visual stimulus properties like orientation and direction. However classification techniques have successfully shown that by combining responses across many voxels with small, noisy biases for orientation and direction, the stimulus a subject is viewing can be correctly classified. We used high-spatial resolution fMRI and classification analysis, and found that robust orientation and direction selectivity can be observed in large draining veins that would be expected to drain over an area of cortex comprising many cortical columns. Thus the success of classification techniques in fMRI may be based on sampling from easily measurable signals from large draining veins rather than biased sampling of well localized signals from cortical maps. Large veins may have specificity because they amplify a biased representation inherent to the cortical architecture or alternatively, because they might be organized to drain specifically from cortical columns that are functionally active together. Either way, our results suggest that inferring population response in human visual cortex can be made possible by measuring valid, if indirect, signals represented in large draining veins.

Gardner, J. L. Sun, P. Tanaka, K. Heeger, D. J. Cheng, K. (2008). Inferring population responses in human visual cortex with classification analysis [Abstract]. Journal of Vision, 8(17):34, 34a, http://journalofvision.org/8/17/34/, doi:10.1167/8.17.34. [CrossRef] [PubMed]
Footnotes
 JLG was supported by a Career Award in the Biomedical Sciences from the Burroughs-Wellcome Fund. P.S. was supported in part by a postdoctoral fellowship from the Japan Society for the Promotion of Science.
×
×

This PDF is available to Subscribers Only

Sign in or purchase a subscription to access this content. ×

You must be signed into an individual account to use this feature.

×