Cerebral Cortex Advance Access originally published online on December 22, 2004
Cerebral Cortex 2005 15(9):1308-1321; doi:10.1093/cercor/bhi014
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© Oxford University Press 2004; all rights reserved
Representation of Regular and Irregular Shapes in Macaque Inferotemporal Cortex
1 Laboratorium voor Neuro- en Psychofysiologie, KU Leuven Medical School, Leuven, Belgium and 2 Department of Psychology and Neuroscience Program, University of Southern California, Los Angeles, CA, USA
Address correspondence to Rufin Vogels, Laboratorium voor Neuro- en Psychofysiologie, KU Leuven Medical School, Onderwijs en Navorsing, Campus Gasthuisberg, B3000 Leuven, Belgium. Email: rufin.vogels{at}med.kuleuven.ac.be.
We determined the degree to which the response modulation of macaque inferior temporal (IT) neurons corresponds to perceptual versus physical shape similarities. IT neurons were tested with four groups of shapes. One group consisted of variations of simple, symmetrical (i.e. regular) shapes that differed in nonaccidental properties (NAPs, i.e. viewpoint-invariant), such as curved versus straight contours. The second and third groups were composed of, respectively, simple and complex asymmetrical (i.e. irregular) shapes, all with curved contours. A fourth group consisted of simple, asymmetrical shapes, but with straight (corners) instead of curved contours. The neural modulations were greater for the shapes differing in NAPs than for the shapes differing in the configuration of the convexities and concavities. Multidimensional scaling showed that a population code of the neural activity could readily distinguish the four shape groups. This pattern of neural modulation was strongly manifested in the results of a sorting task by human subjects but could not be predicted using current image-based models (i.e. pixel energies, V1-like Gabor-jet filtering and HMAX). The representation of shape in IT thus exceeds a mere faithful representation of physical reality, by emphasizing perceptually salient features relevant for essential categorizations.
Key Words: categorization • object recognition • shapes • single cell • symmetry
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