Journal
CEREBRAL CORTEX
Volume 20, Issue 1, Pages 1-12Publisher
OXFORD UNIV PRESS INC
DOI: 10.1093/cercor/bhp076
Keywords
auditory cortex; classifier; nonnative language; pattern-based fMRI; SVM
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Funding
- National Science Foundation (NSF) [0354453]
- EUNICE KENNEDY SHRIVER NATIONAL INSTITUTE OF CHILD HEALTH &HUMAN DEVELOPMENT [R01HD037954] Funding Source: NIH RePORTER
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In order for stimuli to be perceptually discriminable, their representations in the brain must be distinct. Investigating the task of discriminating the syllables /ra/ and /la/, we hypothesized that the more distinct a person's neural representations of those sounds were, the better their behavioral ability to discriminate them would be. Standard neuroimaging approaches are ill-suited to testing this hypothesis as they have problems differentiating between neural representations spatially intermingled within the same brain area. We therefore performed multi-voxel pattern-based analysis of the functional magnetic resonance imaging (fMRI) activity elicited by these syllables, in native speakers of English and Japanese. In right primary auditory cortex, the statistical separability of these fMRI patterns predicted subjects' behavioral ability to tell the sounds apart, not only across groups but also across individuals. This opens up a new approach for identifying neural representations and for quantifying their task suitability.
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