August 2012
Volume 12, Issue 9
Free
Vision Sciences Society Annual Meeting Abstract  |   August 2012
Object recognition under little or no visibility
Author Affiliations
  • Radoslaw Martin Cichy
    Bernstein Center for Computational Neuroscience Berlin and Charité – Universitätsmedizin Berlin, Berlin, Germany\nBerlin Center for Advanced Neuroimaging, Charité-Universitätsmedizin Berlin, Berlin, Germany
  • Stefan Bode
    Department of Psychology, University of Melbourne, Melbourne, Australia
  • Philip Sterzer
    Department of Psychiatry, Campus Charité Mitte, Charité – Universitätsmedizin Berlin, Berlin, Germany\nBerlin School of Mind and Brain, Humboldt Universität zu Berlin, Berlin, Germany
  • John-Dylan Haynes
    Bernstein Center for Computational Neuroscience Berlin and Charité – Universitätsmedizin Berlin, Berlin, Germany\nBerlin Center for Advanced Neuroimaging, Charité-Universitätsmedizin Berlin, Berlin, Germany
Journal of Vision August 2012, Vol.12, 522. doi:10.1167/12.9.522
  • Views
  • Share
  • Tools
    • Alerts
      ×
      This feature is available to Subscribers Only
      Sign In or Create an Account ×
    • Get Citation

      Radoslaw Martin Cichy, Stefan Bode, Philip Sterzer, John-Dylan Haynes; Object recognition under little or no visibility. Journal of Vision 2012;12(9):522. doi: 10.1167/12.9.522.

      Download citation file:


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

      ×
  • Supplements
Abstract

How do we form perceptual decisions about objects under conditions of little or no visibility? Two explanations have been proposed. For one, random noise fluctuations in sensory regions might determine the decision. Alternatively, networks for guessing distinct from the networks active during normal object viewing might determine the choice. Here we employed multivariate pattern classification analysis of fMRI data (searchlight decoding) to investigate the encoding of perceptual decisions about objects under conditions of little or no visibility. In experiment 1, subjects discriminated between noisy images of faces, houses and cars presented for 33ms. Performance was titrated to 50% correct (33% chance level). Correct choices(and thus correctly perceived stimuli) weredecoded from bilateral occipito-temporal cortex and left parietal cortex. Incorrect choices were encoded in left occipito-temporal cortex and medial parietal cortex (all results p<0.05, FWE cluster-level corrected). Experiment 2 implemented the same discrimination task as experiment 1 using pictures of faces, houses and cars in 1/3 of trials. In 2/3 of the trials, however, pure Fourier-scrambled noise images with the mean amplitude spectrum of the object images were presented. Category choices for pure-noise trials were found to be encoded in bilateral occipito-temporal cortex, bilateral parietal cortex and left DLPFC (p<0.05, FWE cluster-level corrected). Additionally, a reverse correlation analysis of the presented noise images and the category choices on the respective trials revealed that the averaged noise images were similar to the average face and car images. This indicates that subjects used the extremely limited visual information to make category decisions, even on pure-noise trials. In summary, our results implicate the involvement of ventral temporal, parietal and prefrontal regions in perceptual decision making when little or no visual information is available to inform the decision process.

Meeting abstract presented at VSS 2012

×
×

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.

×