An algorithmic method for functionally defining regions of interest in the ventral visual pathway
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kanwisher.pdf
Description
article
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1.4 MB
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Author(s)
Fedorenko, Evelina
Webster, Jason
Kanwisher, Nancy
Julian, Joshua B.
Date Issued
March 2012
Journal
NeuroImage
Publisher
Elsevier
Citation
Julian, J.B., Evelina Fedorenko, Jason Webster, and Nancy Kanwisher. “An Algorithmic Method for Functionally Defining Regions of Interest in the Ventral Visual Pathway.” NeuroImage 60, no. 4 (May 2012): 2357–2364.
Version
Author's final manuscript
Abstract
In a widely used functional magnetic resonance imaging (fMRI) data analysis method, functional regions of interest (fROIs) are handpicked in each participant using macroanatomic landmarks as guides, and the response of these regions to new conditions is then measured. A key limitation of this standard handpicked fROI method is the subjectivity of decisions about which clusters of activated voxels should be treated as the particular fROI in question in each subject. Here we apply the Group-Constrained Subject-Specific (GSS) method for defining fROIs, recently developed for identifying language fROIs (Fedorenko et al., 2010), to algorithmically identify fourteen well-studied category-selective regions of the ventral visual pathway (Kanwisher, 2010). We show that this method retains the benefit of defining fROIs in individual subjects without the subjectivity inherent in the traditional handpicked fROI approach. The tools necessary for using this method are available on our website (http://web.mit.edu/bcs/nklab/GSS.shtml).
MIT Department
Massachusetts Institute of Technology. Department of Brain and Cognitive Sciences
McGovern Institute for Brain Research at MIT
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Creative Commons Attribution-NonCommercial-NoDerivs License
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DOI of Published Version
https://doi.org/10.1016/j.neuroimage.2012.02.055
