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.

A common, high-dimensional model of the representational space in human ventral temporal cortex

GOBBINI, MARIA IDA;
2011

Abstract

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.
Haxby J.V.; Guntupalli J.S.; Connolly A.C.; Halchenko Y.O.; Conroy B.R.; Gobbini M.I.; Hanke M.; Ramadge P.J.
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11585/106369
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