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- Title
A Model of Representational Spaces in Human Cortex.
- Authors
Guntupalli, J. Swaroop; Hanke, Michael; Halchenko, Yaroslav O.; Connolly, Andrew C.; Ramadge, Peter J.; Haxby, James V.
- Abstract
Current models of the functional architecture of human cortex emphasize areas that capture coarse-scale features of cortical topography but provide no account for population responses that encode information in fine-scale patterns of activity. Here, we present a linear model of shared representational spaces in human cortex that captures fine-scale distinctions among population responses with response-tuning basis functions that are common across brains and models cortical patterns of neural responses with individual-specific topographic basis functions.We derive a common model space for the whole cortex using a new algorithm, searchlight hyperalignment, and complex, dynamic stimuli that provide a broad sampling of visual, auditory, and social percepts. The model aligns representations across brains in occipital, temporal, parietal, and prefrontal cortices, as shown by between-subject multivariate pattern classification and intersubject correlation of representational geometry, indicating that structural principles for shared neural representations apply across widely divergent domains of information. The model provides a rigorous account for individual variability ofwell-known coarse-scale topographies, such as retinotopy and category selectivity, and goes further to account for fine-scale patterns that are multiplexed with coarse-scale topographies and carry finer distinctions.
- Publication
Cerebral Cortex, 2016, Vol 26, Issue 6, p2919
- ISSN
1047-3211
- Publication type
Article
- DOI
10.1093/cercor/bhw068