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原文連結
論文資訊
- 類型：已發表論文
- 日期：2021-03-16
摘要
Objective. 大腦-computer interfaces (BCIs) constitute a promising tool for communication and control. However, mastering non-invasive closed-loop systems remains a learned skill that is difficult to develop for a non-negligible proportion of users. The involved learning process induces 神經 changes associated with a 大腦 網絡 reorganization that remains poorly understood. Approach. To address this inter-subject variability, we adopted a multilayer approach to integrate 大腦 網絡 properties from electroencephalographic and magnetoencephalographic data resulting from a four-session BCI training program followed by a group of healthy subjects. Our method gives access to the contribution of each layer to multilayer 網絡 that tends to be equal with time. Main results. We show that regardless the chosen modal
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