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1 Research Group for Brain and Cognitive Sciences, School of Medicine, Shaheed Beheshti University, Tehran, Tehran, Iran, Islamic Republic of; Physiology and Biophysics, University of Washington, Seattle, Washington, United States
2 Research Group for Brain and Cognitive Sciences, School of Medicine, Shaheed Beheshti University, Tehran, Tehran, Iran, Islamic Republic of; School of Cognitive Sciences, Institute for Studies in Theoretical Physics and Mathematics, Tehran, Tehran, Iran, Islamic Republic of
3 School of Cognitive Sciences, Institute for Studies in Theoretical Physics and Mathematics, Tehran, Tehran, Iran, Islamic Republic of
4 Cognitive Brain Mapping Laboratory, RIKEN Brain Science Institute, Wako, Saitama, Japan; Graduate School of Science and Engineering, Saitama University, Saitama, Saitama, Japan
* To whom correspondence should be addressed. E-mail: esteky{at}ipm.ir.
Our mental representation of object categories is hierarchically organized, and our rapid and seemingly effortless categorization ability is crucial for our daily behavior. Here, we examine responses of a large number (>600) of neurons in monkey inferior temporal (IT) cortex with a large number (>1000) of natural and artificial object images. During the recordings the monkeys performed a passive fixation task. We found that the categorical structure of objects is represented by the pattern of activity distributed over the cell population. Animate and inanimate objects created distinguishable clusters in the population code. The global category of animate objects was divided into bodies, hands and faces. Faces were divided into primate and non-primate faces, and the primate-face group was divided into human and monkey faces. Bodies of human, birds, and four-limb animals clustered together, while lower animals such as fish, reptile and insects made another cluster. Thus, the cluster analysis showed that IT population responses reconstruct a large part of our intuitive category structure, including the global division into animate and inanimate objects, and further hierarchical subdivisions of animate objects. The representation of categories was distributed in several respects, e.g., the similarity of response patterns to stimuli within a category was maintained by both the cells that maximally responded to the category and the cells that responded weakly to the category. These results advance our understanding of the nature of the IT neural code, suggesting an inherently categorical representation that comprises a range of categories including the amply investigated face category.
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