A model of smooth pursuit in primates based on learning the target dynamics.
While the predictive nature of the primate smooth pursuit system has been evident through several behavioural and neurophysiological experiments, few models have attempted to explain these results comprehensively. The model we propose in this paper in line with previous models employing optimal control theory; however, we hypothesize two new issues: (1) the medical superior temporal (MST) area in the cerebral cortex implements a recurrent neural network (RNN) in order to predict the current or future target velocity, and (2) a forward model of the target motion is acquired by on-line learning. We use stimulation studies to demonstrate how our new model supports these hypotheses.
Shibata
Tomohiro
T
Metalearing and Neuromodulation, CREST, Japan Science and Technology Corporation, Kyoto, Japan. tom@is.naist.jp
Tabata
Hiromitsu
H
Schaal
Stefan
S
Kawato
Mitsuo
M
D000818:Animals; D001921:Brain / Q000033:anatomy & histology / Q000502:physiology*; D003198:Computer Simulation; D006801:Humans; D007858:Learning / Q000502:physiology*; D008959:Models, Neurological; D009039:Motion Perception / Q000502:physiology; D009415:Nerve Net / Q000033:anatomy & histology / Q000502:physiology; D010775:Photic Stimulation; D011323:Primates; D011698:Pursuit, Smooth / Q000502:physiology*; D013702:Temporal Lobe / Q000033:anatomy & histology / Q000502:physiology; D014793:Visual Cortex / Q000033:anatomy & histology / Q000502:physiology