Open AccessSpatial variability of low frequency brain signal differentiates brain states
Author(s) -
Yifeng Wang,
Yujia Ao,
Qi Yang,
Yang Liu,
Yujie Ouyang,
Xiujuan Jing,
Yajing Pang,
Qian Cui,
Huafu Chen
Publication year - 2020
Publication title -
plos one
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.99
H-Index - 332
ISSN - 1932-6203
DOI - 10.1371/journal.pone.0242330
Subject(s) - neuroimaging , brain activity and meditation , resting state fmri , sample entropy , spatial variability , signal (programming language) , brain function , brain mapping , pattern recognition (psychology) , neuroscience , computer science , human brain , artificial intelligence , psychology , electroencephalography , mathematics , statistics , programming language
Temporal variability of the neural signal has been demonstrated to be closely related to healthy brain function. Meanwhile, the evolving brain functions are supported by dynamic relationships among brain regions. We hypothesized that the spatial variability of brain signal might provide important information about brain function. Here we used the spatial sample entropy (SSE) to investigate the spatial variability of neuroimaging signal during a steady-state presented face detection task. Lower SSE was found during task state than during resting state, associating with more repetitive functional interactions between brain regions. The standard deviation (SD) of SSE during the task was negatively related to the SD of reaction time, suggesting that the spatial pattern of neural activity is reorganized according to particular cognitive function and supporting the previous theory that greater variability is associated with better task performance. These results were replicated with reordered data, implying the reliability of SSE in measuring the spatial organization of neural activity. Overall, the present study extends the research scope of brain signal variability from the temporal dimension to the spatial dimension, improving our understanding of the spatiotemporal characteristics of brain activities and the theory of brain signal variability.