Cerebral Cortex Advance Access published online on April 22, 2009
Cerebral Cortex, doi:10.1093/cercor/bhp076
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Quantifying the Adequacy of Neural Representations for a Cross-Language Phonetic Discrimination Task: Prediction of Individual Differences
1 Neukom Institute for Computational Science, Dartmouth College, Hanover, NH 03755, USA, 2 Department of Psychology, National Taiwan University, Taipei 10617, Taiwan, 3 Department of Special Education, National Taiwan Normal University, Taipei 10644, Taiwan, 4 Institute for Learning and Brain Sciences, University of Washington, Seattle, WA 98195, USA
Address correspondence to Dr Feng-Ming Tsao. Email: tsaosph{at}ntu.edu.tw.
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.
Key Words: auditory cortex • classifier • nonnative language • pattern-based fMRI • SVM