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The representation of biological classes in the human brain

Authors :
Andrew C. Connolly
Yaroslav O. Halchenko
Yu-Chien Wu
Michael Hanke
Jason Gors
James V. Haxby
J. Swaroop Guntupalli
Hervé Abdi
Source :
The Journal of neuroscience : the official journal of the Society for Neuroscience. 32(8)
Publication Year :
2012

Abstract

Evidence of category specificity from neuroimaging in the human visual system is generally limited to a few relatively coarse categorical distinctions—e.g., faces versus bodies, or animals versus artifacts—leaving unknown the neural underpinnings of fine-grained category structure within these large domains. Here we use functional magnetic resonance imaging (fMRI) to explore brain activity for a set of categories within the animate domain, including six animal species—two each from three very different biological classes: primates, birds, and insects. Patterns of activity throughout ventral object vision cortex reflected the biological classes of the stimuli. Specifically, the abstract representational space—measured as dissimilarity matrices defined between species-specific multivariate patterns of brain activity—correlated strongly with behavioral judgments of biological similarity of the same stimuli. This biological class structure was uncorrelated with structure measured in retinotopic visual cortex, which correlated instead with a dissimilarity matrix defined by a model of V1 cortex for the same stimuli. Additionally, analysis of the shape of the similarity space in ventral regions provides evidence for a continuum in the abstract representational space—with primates at one end and insects at the other. Further investigation into the cortical topography of activity that contributes to this category structure reveals the partial engagement of brain systems active normally for inanimate objects in addition to animate regions.

Details

ISSN :
15292401
Volume :
32
Issue :
8
Database :
OpenAIRE
Journal :
The Journal of neuroscience : the official journal of the Society for Neuroscience
Accession number :
edsair.doi.dedup.....56d70ebe63c9aeb2232a0dc3ce4ed67e