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

James V. Haxby, J. Swaroop Guntupalli, Andrew C. Connolly, Yaroslav O. Halchenko, Bryan R. Conroy, M. Ida Gobbini, Michael Hanke, Peter Jeffrey Ramadge

Research output: Contribution to journalArticle

262 Scopus citations

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.

Original languageEnglish (US)
Pages (from-to)404-416
Number of pages13
JournalNeuron
Volume72
Issue number2
DOIs
StatePublished - Oct 20 2011

All Science Journal Classification (ASJC) codes

  • Neuroscience(all)

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    Haxby, J. V., Guntupalli, J. S., Connolly, A. C., Halchenko, Y. O., Conroy, B. R., Gobbini, M. I., Hanke, M., & Ramadge, P. J. (2011). A common, high-dimensional model of the representational space in human ventral temporal cortex. Neuron, 72(2), 404-416. https://doi.org/10.1016/j.neuron.2011.08.026