Categorical signals in a single-trial neuron activity of the inferotemporal cortex.
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.
Matsumoto
Narihisa
N
Neuroscience Research Institute, National Institute of Advanced Industrial Science and Technology, Ibaraki, Japan. xmatumo@ni.aist.go.jp
Sugase-Miyamoto
Yasuko
Y
Okada
Masato
M
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*