Representation of maximally regular textures in human visual cortex

Peter J. Kohler, Alasdair Clarke, Alexandra Yakovleva, Yanxi Liu, Anthony M. Norcia

Research output: Contribution to journalArticlepeer-review

34 Scopus citations

Abstract

Naturalistic textures with an intermediate degree of statistical regularity can capture key structural features of natural images (Freeman and Simoncelli, 2011). V2 and later visual areas are sensitive to these features, while primary visual cortex is not (Freeman et al., 2013). Here we expand on this work by investigating a class of textures that have maximal formal regularity, the 17 crystallographic wallpaper groups (Fedorov, 1891). We used texture stimuli from four of the groups that differ in the maximum order of rotation symmetry they contain, and measured neural responses in human participants using functional MRI and high-density EEG. We found that cortical area V3 has a parametric representation of the rotation symmetries in the textures that is not present in either V1 or V2, the first discovery of a stimulus property that differentiates processing in V3 from that of lower-level areas. Parametric responses were also seen in higherorder ventral stream areas V4, VO1, and lateral occipital complex (LOC), but not in dorsal stream areas. The parametric response pattern was replicated in the EEG data, and source localization indicated that responses in V3 and V4 lead responses in LOC, which is consistent with a feedforward mechanism. Finally, we presented our stimuli to four well developed feedforward models and found that none of them were able to account for our results. Our results highlight structural regularity as an important stimulus dimension for distinguishing the early stages of visual processing, and suggest a previously unrecognized role for V3 in the visual form-processing hierarchy.

Original languageEnglish (US)
Pages (from-to)714-729
Number of pages16
JournalJournal of Neuroscience
Volume36
Issue number3
DOIs
StatePublished - Jan 20 2016

All Science Journal Classification (ASJC) codes

  • Neuroscience(all)

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