Resting-state brain activity in the motor cortex reflects task-induced activity: A multi-voxel pattern analysis
Resting-state brain activity in the motor cortex reflects task-induced activity: A multi-voxel pattern analysis
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DOI：
10.1109/embc.2015.7319343
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发表时间：
2015-11
期刊：
影响因子：
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通讯作者：
Toshiki Kusano;Hiroki Kurashige;I. Nambu;Y. Moriguchi;T. Hanakawa;Y. Wada;R. Osu
中科院分区：
文献类型：
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作者：
Toshiki Kusano;Hiroki Kurashige;I. Nambu;Y. Moriguchi;T. Hanakawa;Y. Wada;R. Osu
有人认为，休息状态下的大脑活动反映了任务诱导的大脑活动模式。在这项研究中，我们检查是否可以观察到特定运动的神经表征在静息状态下的运动区的大脑活动模式。首先，我们定义了两个感兴趣区域（ROI）来检查与两种不同行为任务相关的大脑活动。使用带有正则化逻辑回归的多体素模式分析，我们设计了一个解码器来检测与每个感兴趣区域中的任务对应的体素级神经表示。接下来，我们将解码器应用于休息状态的大脑活动。我们发现，解码器区分静息态神经活动的准确性与任务引起的神经活动。学习加权参数的分布为每个ROI是相似的休息状态和任务引起的活动。大的加权参数主要位于连接区域。此外，检测的准确性高于其权重被随机打乱的解码器，这表明静息状态的大脑活动包括类似于任务的神经表示的多体素模式。因此，这些结果表明，静息态大脑活动的神经表征比传统认为的更精细，更复杂。
It has been suggested that resting-state brain activity reflects task-induced brain activity patterns. In this study, we examined whether neural representations of specific movements can be observed in the resting-state brain activity patterns of motor areas. First, we defined two regions of interest (ROIs) to examine brain activity associated with two different behavioral tasks. Using multi-voxel pattern analysis with regularized logistic regression, we designed a decoder to detect voxel-level neural representations corresponding to the tasks in each ROI. Next, we applied the decoder to resting-state brain activity. We found that the decoder discriminated resting-state neural activity with accuracy comparable to that associated with task-induced neural activity. The distribution of learned weighted parameters for each ROI was similar for resting-state and task-induced activities. Large weighted parameters were mainly located on conjunctive areas. Moreover, the accuracy of detection was higher than that for a decoder whose weights were randomly shuffled, indicating that the resting-state brain activity includes multi-voxel patterns similar to the neural representation for the tasks. Therefore, these results suggest that the neural representation of resting-state brain activity is more finely organized and more complex than conventionally considered.