Cognitive Mechanisms Laboratories, Advanced Telecommunications Research Institute International (ATR)
Graduate School of Frontier Biosciences, Osaka University
Department of Psychology, Graduate School of Humanities and Sociology, The University of Tokyo
Department of Psychology, Graduate School of Letters, Hokkaido University
Center for Information and Neural Networks (CiNet), National Institute of Information and Communications Technology and Osaka University
抄録
Neural activity prior to movement onset contains essential information for predictive assistance for humans using brain-machine-interfaces (BMIs). Even though previous studies successfully predicted different goals for upcoming movements, it is unclear whether non-invasive recording signals contain the information to predict trial-by-trial behavioral variability under the same movement. In this paper, we examined the predictability of subsequent short or long reaction times (RTs) from magnetoencephalography (MEG) signals in a delayed-reach task. The difference in RTs was classified significantly above chance from 550 ms before the go-signal onset using the cortical currents in the premotor cortex. Significantly above-chance classification was performed in the lateral prefrontal and the right inferior parietal cortices at the late stage of the delay period. Thus, inter-trial variability in RTs is predictable information. Our study provides a proof-of-concept of the future development of non-invasive BMIs to prevent delayed movements.
内容記述
UTokyo Research掲載「運動前の脳活動から反応の速さを予測することに成功」 URI: http://www.u-tokyo.ac.jp/ja/utokyo-research/research-news/prediction-of-reaction-speed-from-pre-movement-brain-activity.html
UTokyo Research "Prediction of reaction speed from pre-movement brain activity" URI: http://www.u-tokyo.ac.jp/en/utokyo-research/research-news/prediction-of-reaction-speed-from-pre-movement-brain-activity.html
Single-trial prediction of reaction time variability from MEG brain activity
srep27416.pdf
(1.73MB)
