Others Single-trial prediction of reaction time variability from MEG brain activity

Ohata, Ryu  ,  Ogawa, Kenji  ,  Imamizu, Hiroshi

62016-06-02 , Nature Publishing Group , 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
ISSN:2045-2322 (online)
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
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.


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