Journal
CEREBRAL CORTEX
Volume 15, Issue 8, Pages 1103-1112Publisher
OXFORD UNIV PRESS INC
DOI: 10.1093/cercor/bhh209
Keywords
hierarchical relationship; mixture of Gaussians analysis; principal component analysis; variational Bayes algorithm
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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.
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