期刊
NEURON
卷 72, 期 2, 页码 404-416出版社
CELL PRESS
DOI: 10.1016/j.neuron.2011.08.026
关键词
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资金
- National Institutes of Mental Health [F32MH085433-01A1, 5R01MH075706]
- Neukom Institute for Computational Sciences at Dartmouth
- Direct For Social, Behav & Economic Scie
- Division Of Behavioral and Cognitive Sci [1129764] Funding Source: National Science Foundation
We present a high-dimensional model of the representational space in human ventral temporal (VT) cortex in which dimensions are response-tuning functions that are common across individuals and patterns of response are modeled as weighted sums of basis patterns associated with these response tunings. We map response-pattern vectors, measured with fMRI, from individual subjects' voxel spaces into this common model space using a new method, hyperalignment. Hyperalignment parameters based on responses during one experiment-movie viewing-identified 35 common response-tuning functions that captured fine-grained distinctions among a wide range of stimuli in the movie and in two category perception experiments. Between-subject classification (BSC, multivariate pattern classification based on other subjects' data) of response-pattern vectors in common model space greatly exceeded BSC of anatomically aligned responses and matched within-subject classification. Results indicate that population codes for complex visual stimuli in VT cortex are based on response-tuning functions that are common across individuals.
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