August 2014
Volume 14, Issue 10
Vision Sciences Society Annual Meeting Abstract  |   August 2014
Decoding orientation of visual stimuli from human magnetoencephalography data
Author Affiliations
  • Radoslaw Cichy
    Computer Science and Artificial Intelligence Laboratory, MIT, Cambridge, MA
  • Dimitrios Pantazis
    McGovern Institute for Brain Research, MIT, Cambridge, MA
Journal of Vision August 2014, Vol.14, 46. doi:
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      Radoslaw Cichy, Dimitrios Pantazis; Decoding orientation of visual stimuli from human magnetoencephalography data. Journal of Vision 2014;14(10):46.

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

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Local orientation is a fundamental feature extracted by visual perception. Recent advances in multivariate analysis methods in fMRI have allowed the direct and non-invasive localization of orientation encoding in the human brain, but have left its temporal aspects unclear. Here, using magnetoencephalography (MEG) we resolve with high temporal resolution the time course of orientation encoding. In experiment 1, participants observed sinusoidal gratings tilted 45째 to the right or left from vertical. In experiment 2, sinusoidal gratings were oriented from 0 to 150째 in 30째 steps; and in experiment 3, they were radially balanced exponential spirals oriented 45째 to the right or left. All stimuli were shown in two different phases (phase and anti-phase) to allow dissociation of orientation from local luminance differences. We used time-resolved multivariate pattern classification (support-vector machines) to decode the observed orientation from MEG data. In all three experiments and for all orientations, we find robust and significant decoding starting at ~65-70ms after stimulus onset. In addition, experiment 2 shows that orientation decoding is not merely due to a radial bias in the representation of orientation. Comparing decoding for oblique vs. cardinal orientations (experiment 3), we find only weak evidence for a cardinal bias as a factor in orientation decoding in MEG. Importantly, results were independent of the local luminance of the stimuli, i.e. they generalized across phase. Our results demonstrate that multivariate analysis of MEG signals allows content-sensitive and direct read-out of local visual orientation information, and inform about the factors enabling orientation decoding.

Meeting abstract presented at VSS 2014


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