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  Cortical surface-based searchlight decoding

Chen, Y., Namburi, P., Elliott, L. T., Heinzle, J., Soon, C. S., Chee, M. W. L., et al. (2011). Cortical surface-based searchlight decoding. NeuroImage, 56(2), 582-592. doi:10.1016/j.neuroimage.2010.07.035.

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Item Permalink: http://hdl.handle.net/11858/00-001M-0000-0012-2A3C-A Version Permalink: http://hdl.handle.net/21.11116/0000-0002-B377-E
Genre: Journal Article

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 Creators:
Chen, Yi1, 2, Author              
Namburi, Praneeth3, Author
Elliott, Lloyd T.2, 4, Author
Heinzle, Jakob2, Author
Soon, Chun Siong1, 2, 3, Author              
Chee, Michael W. L.3, Author
Haynes, John-Dylan1, 2, 5, 6, Author              
Affiliations:
1Max Planck Fellow Research Group Attention and Awareness, MPI for Human Cognitive and Brain Sciences, Max Planck Society, ou_634553              
2Bernstein Center for Computational Neuroscience Berlin and Charité - Universitätsmedizin Berlin, Germany, ou_persistent22              
3Duke-NUS Graduate Medical School, Singapore, Singapore, ou_persistent22              
4Gatsby Computational Neuroscience Unit, University College London, United Kingdom, ou_persistent22              
5Department of Neurology, Otto-von-Guericke University, Magdeburg, Germany, ou_persistent22              
6Graduate School of Mind and Brain, Humboldt Universität zu Berlin, Germany, ou_persistent22              

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 Abstract: Local voxel patterns of fMRI signals contain specific information about cognitive processes ranging from basic sensory processing to high level decision making. These patterns can be detected using multivariate pattern classification, and localization of these patterns can be achieved with searchlight methods in which the information content of spherical sub-volumes of the fMRI signal is assessed. The only assumption made by this approach is that the patterns are spatially local. We present a cortical surface-based searchlight approach to pattern localization. Voxels are grouped according to distance along the cortical surface—the intrinsic metric of cortical anatomy—rather than Euclidean distance as in volumetric searchlights. Using a paradigm in which the category of visually presented objects is decoded, we compare the surface-based method to a standard volumetric searchlight technique. Group analyses of accuracy maps produced by both methods show similar distributions of informative regions. The surface-based method achieves a finer spatial specificity with comparable peak values of significance, while the volumetric method appears to be more sensitive to small informative regions and might also capture information not located directly within the gray matter. Furthermore, our findings show that a surface centered in the middle of the gray matter contains more information than to the white–gray boundary or the pial surface.

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Language(s): eng - English
 Dates: 2010-07-152010-03-172010-07-192010-07-232011-05-15
 Publication Status: Published in print
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Method: Peer
 Identifiers: DOI: 10.1016/j.neuroimage.2010.07.035
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Title: NeuroImage
Source Genre: Journal
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Publ. Info: Orlando, FL : Academic Press
Pages: - Volume / Issue: 56 (2) Sequence Number: - Start / End Page: 582 - 592 Identifier: ISSN: 1053-8119
CoNE: /journals/resource/954922650166