Single-trial prediction of reaction time variability from MEG brain activity.
Single-trial prediction of reaction time variability from MEG brain activity.
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DOI：
10.1038/srep27416
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发表时间：
2016-06-02
影响因子：
4.6
通讯作者：
Imamizu H
中科院分区：
文献类型：
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作者：
Ohata R;Ogawa K;Imamizu H
运动开始之前的神经活动包含使用脑机接口（BMI）为人类提供预测帮助的基本信息。尽管先前的研究成功地预测了即将到来的运动的不同目标，但目前尚不清楚非侵入性记录信号是否包含预测同一运动下逐个试验行为变异性的信息。在本文中，我们研究了可预测性的后续短或长的反应时间（RT）从脑磁图（MEG）信号在延迟达到任务。使用前运动皮层中的皮层电流，从go信号发作前550 ms开始，将RT的差异显著归类为高于偶然性。在延迟期的晚期，外侧前额叶和右下顶叶皮层进行了显着的机会上分类。因此，RT的试验间变异性是可预测的信息。我们的研究提供了一个概念验证的未来发展的非侵入性BMI，以防止延迟运动。
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.