title: Categorical signals in a single-trial neuron activity of the inferotemporal cortex.
abstract: We developed an algorithm that decodes categorical signals from the single-trial activity of a neuronal population in the monkey inferotemporal cortex. We defined a global category (i.e. human faces vs. monkey faces vs. shape) and fine categories (i.e. human identity, monkey expression, and shape form) from the single-trial activity. The accuracy of estimation for the trials was roughly 100% for the global category and 88.1% for the fine categories. The accuracy of stimulus identification for the trials was 70.4%. These results suggest that signals concerning global and fine categories as well as object identification can be decoded using the single-trial activity of a neuronal population in the inferotemporal cortex.
authors.affiliation: Neuroscience Research Institute, National Institute of Advanced Industrial Science and Technology, Ibaraki, Japan. xmatumo@ni.aist.go.jp
authors.forename: Narihisa
authors.initials: N
authors.lastname: Matsumoto
authors.forename: Yasuko
authors.initials: Y
authors.lastname: Sugase-Miyamoto
authors.forename: Masato
authors.initials: M
authors.lastname: Okada
mesh_terms: D000465:Algorithms; D000818:Animals; D005145:Face; D006801:Humans; D008251:Macaca; D009474:Neurons / Q000502:physiology*; D010775:Photic Stimulation; D025341:Principal Component Analysis; D021641:Recognition, Psychology / Q000502:physiology; D013702:Temporal Lobe / Q000502:physiology*