December 2014
Volume 14, Issue 15
OSA Fall Vision Meeting Abstract  |   December 2014
fMRI decoding: What does it reflect, and what can we learn
Author Affiliations
  • Eli Merriam
    Center for Neural Science, New York University
Journal of Vision December 2014, Vol.14, 15. doi:
  • Views
  • Share
  • Tools
    • Alerts
      This feature is available to authenticated users only.
      Sign In or Create an Account ×
    • Get Citation

      Eli Merriam; fMRI decoding: What does it reflect, and what can we learn. Journal of Vision 2014;14(15):15.

      Download citation file:

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

  • Supplements

To encode and make inferences about the world, the brain represents patterns -- visual, auditory, cognitive -- using populations of neurons with diverse and complex forms of selectivity. A coarse-scale method like functional magnetic resonance imaging (fMRI) would, at first glance, appear poorly suited to studying these representations. Consider the case of orientation representation in primary visual cortex (V1). A single fMRI voxel pools responses from many orientation-tuned neurons. Because orientation tuning varies at a fine, columnar spatial-scale, tuning should cancel at the level of fMRI voxels. Surprisingly, results from multivariate decoding analyses imply that voxels in human V1 are weakly but reliably orientation selective. It is widely believed that these small biases arise because of random spatial irregularities in the underlying columnar architecture, and this interpretation, while untested, has been extended to the study of cognitive functions throughout the brain. I will describe a set of experiments that test this hypothesis by characterizing both orientation selectivity and motion direction selectivity using fMRI in human visual cortex. We discovered coarse-scale biases for both orientation and motion direction. The existence of these coarse-scale biases are both necessary and sufficient for multivariate decoding, demonstrating that random spatial irregularities do not contribute to decoding. Our results imply a parsimonious, but sobering, explanation for why fMRI decoding works, and help guide the interpretation of the rapidly growing number of studies based on this technique.


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.