Exemplar selectivity reflects perceptual similarities in the human fusiform cortex

Ido Davidesco, Elana Zion-Golumbic, Stephan Bickel, Michal Harel, David M. Groppe, Corey J. Keller, Catherine A. Schevon, Guy M. McKhann, Robert R. Goodman, Gadi Goelman, Charles E. Schroeder, Ashesh D. Mehta, Rafael Malach

Research output: Contribution to journalArticlepeer-review

53 Scopus citations

Abstract

While brain imaging studies emphasized the category selectivity of face-related areas, the underlying mechanisms of our remarkable ability to discriminate between different faces are less understood. Here, we recorded intracranial local field potentials from face-related areas in patients presented with images of faces and objects. A highly significant exemplar tuning within the category of faces was observed in high-Gamma (80-150 Hz) responses. The robustness of this effect was supported by single-trial decoding of face exemplars using a minimal (n = 5) training set. Importantly, exemplar tuning reflected the psychophysical distance between faces but not their low-level features. Our results reveal a neuronal substrate for the establishment of perceptual distance among faces in the human brain. They further imply that face neurons are anatomically grouped according to well-defined functional principles, such as perceptual similarity.

Original languageEnglish
Pages (from-to)1879-1893
Number of pages15
JournalCerebral Cortex
Volume24
Issue number7
DOIs
StatePublished - Jul 2014
Externally publishedYes

Bibliographical note

Funding Information:
This research was supported by the Kimmel Award for Innovative Research to R.M., and NIMH grant MH093061 to E.Z. and MH086385 to C.E.S.

Funding

This research was supported by the Kimmel Award for Innovative Research to R.M., and NIMH grant MH093061 to E.Z. and MH086385 to C.E.S.

FundersFunder number
Kimmel Award for Innovative Research
National Institute of Mental HealthF32MH093061, MH086385

    Keywords

    • ECoG
    • face perception
    • high-gamma
    • perceptual similarity

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