A common, high-dimensional model of the representational space in human ventral temporal cortex.
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.
Department of Psychological and Brain Sciences, Dartmouth College, Hanover, NH 03755, USA. james.v.haxby@dartmouth.edu
James V
JV
Haxby
J Swaroop
JS
Guntupalli
Andrew C
AC
Connolly
Yaroslav O
YO
Halchenko
Bryan R
BR
Conroy
M Ida
MI
Gobbini
Michael
M
Hanke
Peter J
PJ
Ramadge
D000328:Adult; D001931:Brain Mapping / Q000379:methods*; D059907:Functional Neuroimaging; D006801:Humans; D007091:Image Processing, Computer-Assisted; D008959:Models, Neurological; D009474:Neurons / Q000502:physiology*; D010775:Photic Stimulation; D013702:Temporal Lobe / Q000502:physiology*; D014793:Visual Cortex / Q000502:physiology*; D014796:Visual Perception / Q000502:physiology*