College of Electronic Engineering, Heilongjiang University, Harbin 150080, China.
State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing 100875, China.
Neuroimage. 2022 Apr 1;249:118875. doi: 10.1016/j.neuroimage.2022.118875. Epub 2022 Jan 5.
Brain entropy (BEN) calculated from resting state fMRI has been the subject of increasing research interest in recent years. Previous studies have shown the correlations between rest BEN and neurocognition and task performance, but how this relates to task-evoked brain activations and deactivations remains unknown. The purpose of this study is to address this open question using large data (n = 862). Voxel wise correlations were calculated between rest BEN and task activations/deactivations of five different tasks. For most of the assessed tasks, lower rest BEN was found to be associated with stronger activations (negative correlations) and stronger deactivations (positive correlations) only in brain regions activated or deactivated by the tasks. Higher workload evoked spatially more extended negative correlations between rest BEN and task activations. These results not only confirm that resting brain activity can predict brain activity during task performance but also for the first time show that resting brain activity may facilitate both task activations and deactivations. In addition, the results provide a clue to understanding the individual differences of task performance and brain activations.
近年来,基于静息态 fMRI 的脑熵(BEN)计算已成为研究热点。先前的研究表明,静息 BEN 与神经认知和任务表现之间存在相关性,但它与任务诱发的大脑激活和去激活之间的关系尚不清楚。本研究旨在使用大数据(n=862)来解决这个开放性问题。对静息 BEN 与五个不同任务的任务激活/去激活的体素进行了相关分析。对于大多数评估任务,发现静息 BEN 越低,与任务激活(负相关)和去激活(正相关)的相关性越强,仅在被任务激活或去激活的脑区。更高的工作负荷引起了静息 BEN 与任务激活之间空间上更广泛的负相关。这些结果不仅证实了静息大脑活动可以预测任务执行期间的大脑活动,而且首次表明静息大脑活动可能促进任务的激活和去激活。此外,该结果为理解任务表现和大脑激活的个体差异提供了线索。