August 2016
Volume 16, Issue 12
Open Access
Vision Sciences Society Annual Meeting Abstract  |   September 2016
Investigating the temporal properties of visual object processing using a multivariate analysis of EEG data.
Author Affiliations
  • David Coggan
    Department of Psychology, University of York, UK
  • Timothy Andrews
    Department of Psychology, University of York, UK
  • Daniel Baker
    Department of Psychology, University of York, UK
Journal of Vision September 2016, Vol.16, 1311. doi:10.1167/16.12.1311
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      David Coggan, Timothy Andrews, Daniel Baker; Investigating the temporal properties of visual object processing using a multivariate analysis of EEG data.. Journal of Vision 2016;16(12):1311. doi: 10.1167/16.12.1311.

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

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Abstract

An understanding of human object recognition requires combining both spatial and temporal information about neural activity. Previous studies using fMRI have found distinct spatial patterns of response in the ventral visual pathway. However, the temporal dynamics of these patterns of response is less clear. Here, we acquired human electroencephalography (EEG) responses to images from different object categories (bottle, face, house). Our aims were to determine (1) whether there are distinct patterns of EEG response to different object categories; (2) the temporal properties of these patterns and (3) the extent to which these patterns are based on low-level image properties. Participants viewed images of bottles, faces and houses while EEG data was acquired from 64 electrodes. A correlation-based multivariate pattern analysis revealed distinct patterns of response across electrodes to different object categories that emerged at approximately 90 msec and remained distinct until approximately 600 msec after stimulus onset. Next, we asked whether these patterns of neural response could be explained by selectivity to more basic properties of the stimulus. To address this question, we measured patterns of EEG response to phase-scrambled images. Our rationale for using scrambled images is that they have many of the image properties found in intact images, but do not convey any categorical or semantic information. Again, distinct patterns of response to scrambled images from different object categories emerged approximately 70-100 msec after stimulus onset. Moreover, the patterns of neural response to scrambled images from each object category were similar to the patterns of response for intact images. However, distinct patterns to scrambled images were only evident until approximately 300-450 msec after stimulus onset. Together, these results provide new insights into the temporal dynamics of object processing in the human brain.

Meeting abstract presented at VSS 2016

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