Probabilistic maps of visual topography in human cortex

Liang Wang, Ryan E.B. Mruczek, Michael J. Arcaro, Sabine Kastner

Research output: Contribution to journalArticlepeer-review

180 Scopus citations

Abstract

The human visual system contains an array of topographically organized regions. Identifying these regions in individual subjects is a powerful approach to group-level statistical analysis, but this is not always feasible.We addressed this limitation by generating probabilistic maps of visual topographic areas in 2 standardized spaces suitable for use with adult human brains. Using standard fMRI paradigms, we identified 25 topographic maps in a large population of individual subjects (N = 53) and transformed them into either a surface-or volume-based standardized space. Here, we provide a quantitative characterization of the inter-subject variability within and across visual regions, including the likelihood that a given point would be classified as a part of any region (full probability map) and the most probable region for any given point (maximum probability map). By evaluating the topographic organization across the whole of visual cortex, we provide new information about the organization of individual visual field maps and large-scale biases in visual field coverage. Finally, we validate each atlas for use with independent subjects. Overall, the probabilistic atlases quantify the variability of topographic representations in human cortex and provide a useful reference for comparing data across studies that can be transformed into these standard spaces.

Original languageEnglish (US)
Pages (from-to)3911-3931
Number of pages21
JournalCerebral Cortex
Volume25
Issue number10
DOIs
StatePublished - Oct 2015

All Science Journal Classification (ASJC) codes

  • Cognitive Neuroscience
  • Cellular and Molecular Neuroscience

Keywords

  • Atlas
  • Cortical organization
  • Functional magnetic resonance imaging
  • Mapping
  • Topography

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