August 2016
Volume 16, Issue 12
Open Access
Vision Sciences Society Annual Meeting Abstract  |   September 2016
Investigating functional organization with Grouping by Response Similarity
Author Affiliations
  • Jason Webster
    Department of Psychology, University of Washington
  • Ione Fine
    Department of Psychology, University of Washington
Journal of Vision September 2016, Vol.16, 506. doi:10.1167/16.12.506
  • Views
  • Share
  • Tools
    • Alerts
      ×
      This feature is available to Subscribers Only
      Sign In or Create an Account ×
    • Get Citation

      Jason Webster, Ione Fine; Investigating functional organization with Grouping by Response Similarity. Journal of Vision 2016;16(12):506. doi: 10.1167/16.12.506.

      Download citation file:


      © 2017 Association for Research in Vision and Ophthalmology.

      ×
  • Supplements
Abstract

Cortical parcellation has been conducted using gene expression, cytoarchitectonics, receptor architecture, connectivity, and intrinsic activity; however, stimulus-driven functional parcellation has remained elusive, particularly for the ventral temporal cortex (VTC). While several category-selective regions (e.g. face and scene areas) have been identified, these occupy less than half of non-retinotopic visual cortex. Whether the remaining cortex contains distinct functional regions remains unknown. Representational Similarity Analysis (RSA) is a powerful tool for studying these regions, however, the logic of RSA requires a region of interest (ROI) containing a unitary, complete representation. Here, we show that Grouping by Response Similarity (GRS), a data-driven method for identifying regions containing functionally coherent responses, can identify regions containing distinct representations as demonstrated using RSA. During two fMRI sessions, subjects viewed separate sets of video clips of naturalistic stimuli while performing a one-back task. For each dataset, a vector of responses to each stimulus was calculated for each VTC vertex. In order to group functionally similar vertices, response vectors were correlated and the correlation matrix was then permuted to maximize the summed values along the subdiagonal. An automated segmentation method identified functional clusters in the matrix, which were projected onto the cortical surface. Importantly, the algorithm finds regions with coherent responses without assumptions regarding the relationships between stimuli or spatial locations. Functional clusters in the GRS matrix produced discrete ROIs on the cortical surface, resulting in parcellation of the VTC. ROI stimulus preferences were replicable across split halves of the data through much of VTC and ROI boundaries were replicable across the two naturalistic stimulus sets. RSA within these ROIs demonstrated that the ROIs encode distinct representations of the stimulus space. Thus, GRS provides a framework for exploratory analysis of cortical functional organization in which regional boundaries are unknown and stimulus preferences are unclear.

Meeting abstract presented at VSS 2016

×
×

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.

×