眼球運動とその制御モデルを利用した眠気予兆検知とロボット適応制御

抄録

Oculomotor system has been a popular model system in neuroscience to study motor control and learning. Eye movements have also attracted much attention in medicine, ergonomics, and engineering as many brain areas are involved in oculomotor control and their activities are reflected in different ways in various types of eye movements. In this talk, I will introduce our study on adaptive robot control by a realistic neuronal network model of the cerebellum that were configured based upon neuroanatomical evidence on adaptive eye movement control revealed by our monkey and goldfish behavioral and electrophysiological experiments. The model implemented on LabVIEW was registered to International Neuroinformatics Coordinating Facility Japan Node, Cerebellar Platform, and publicly available. I will also talk about an application of reflexive eye movements to detect and predict sleepiness of car drivers. This application was inspired by behavioral experiments in monkeys in which simple reflexive eye movements called the vestibuloocular reflex were found to be less responsive and more variable when they were sleepy than when they were alert.