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Reading out the perceptual boundary between human and monkey face categories from the inferior temporal cortex of the macaque monkey

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http://pubman.mpdl.mpg.de/cone/persons/resource/persons84221

Alanis,  GRS
Department Physiology of Cognitive Processes, Max Planck Institute for Biological Cybernetics, Max Planck Society;

http://pubman.mpdl.mpg.de/cone/persons/resource/persons84063

Logothetis,  NK
Department Physiology of Cognitive Processes, Max Planck Institute for Biological Cybernetics, Max Planck Society;

http://pubman.mpdl.mpg.de/cone/persons/resource/persons84154

Rainer,  G
Department Physiology of Cognitive Processes, Max Planck Institute for Biological Cybernetics, Max Planck Society;

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Citation

Alanis, G., Logothetis, N., & Rainer, G. (2007). Reading out the perceptual boundary between human and monkey face categories from the inferior temporal cortex of the macaque monkey. Poster presented at 30th European Conference on Visual Perception, Arezzo, Italy.


Cite as: http://hdl.handle.net/11858/00-001M-0000-0013-CC6B-4
Abstract
We demonstrated that, when human subjects have to classify human/monkey morphed faces that change along a continuum, they draw the category boundary closer to their own species (at approximately 60 human/40 monkey). Considering that neurons in the infero-temporal (IT) cortex encode face information, we recorded the single-unit activity (SUA) of 118 neurons and the local field potential (LFP) at 58 sites of the IT cortex of one macaque monkey during fixation of morphed faces. Out of 118 single units, 85 were visually responsive and 23 were face cells according to standard criteria. We used a two-class (human - monkey) classifier (k-NearestNeighbor) to analyze the population activity of visually responsive units and all LFPs. Symmetric to the findings in humans, the classifier drew the category boundary closer to the monkey category (at approximately 40 human/60 monkey) for both kinds of neural signals. These results suggest an ‘own-species‘ advantage in the encod ing of face stimuli. Our findings also indicate that a large fraction of IT neurons participate in the encoding of face categories.