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Cerebral Cortex Advance Access published online on November 24, 2004

Cerebral Cortex, doi:10.1093/cercor/bhh209
© 2004 by Oxford University Press
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Article

Population Dynamics of Face-responsive Neurons in the Inferior Temporal Cortex

Narihisa Matsumoto 1*, Masato Okada 2, Yasuko Sugase-Miyamoto 3, Shigeru Yamane 3, and Kenji Kawano 4

1 PRESTO, Japan Science and Technology Agency, Saitama 351-0198, Japan; RIKEN Brain Science Institute, Saitama 351-0198, Japan; National Institute of Advanced Industrial Science and Technology (AIST), Ibaraki 305-8568, Japan
2 PRESTO, Japan Science and Technology Agency, Saitama 351-0198, Japan; RIKEN Brain Science Institute, Saitama 351-0198, Japan; Kawato Dynamic Brain Project, ERATO, JST, Kyoto 619-0288, Japan; Graduate School of Frontier Sciences, University of Tokyo, Chiba 277-8561, Japan
3 National Institute of Advanced Industrial Science and Technology (AIST), Ibaraki 305-8568, Japan
4 National Institute of Advanced Industrial Science and Technology (AIST), Ibaraki 305-8568, Japan; Graduate School of Medicine, Kyoto University, Kyoto 606-8501, Japan

* To whom correspondence should be addressed.
Narihisa Matsumoto, E-mail: xmatumo{at}ni.aist.go.jp


   Abstract

Neurons in the inferior temporal (IT) cortex of monkeys respond selectively to complex visual stimuli, such as faces. Single neurons in the IT cortex encode different kinds of information about visual stimuli in their temporal firing patterns. To understand the temporal aspects of the information encoded at a population level in the IT cortex, we applied principal component analysis (PCA) to the responses of a population of neurons. The responses of each neuron were recorded while visual stimuli that consisted of geometric shapes and faces of humans and monkeys were presented. We found that global categorization, i.e. human faces versus monkey faces versus shapes, occurred in the earlier part of the population response, and that fine categorization occurred within each member of the global category in the later part of the population response. A cluster analysis, a mixture of Gaussians analysis, confirmed that the clusters in the earlier part of the responses represented the global category. Moreover, the clusters in the earlier part separated into sub-clusters corresponding to either human identity or monkey expression in the later part of the responses, and the global categorization was maintained even after the appearance of the sub-clusters. The results suggest that a hierarchical relationship of the test stimuli is represented temporally by the population response of IT neurons.

Keywords: hierarchical relationship; mixture of Gaussians analysis; principal component analysis; variational Bayes algorithm.
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