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Multiscale energy reallocation during low-frequency steady-state brain response

Authors :
Qi Yang
Qian Cui
Yifeng Wang
Qijun Zou
Xujun Duan
Xinqi Wang
Wei Liao
Huafu Chen
Bharat B. Biswal
Wang Chen
Liangkai Ye
Xuezhi Yang
Pu Yang
Source :
Hum Brain Mapp
Publication Year :
2018
Publisher :
Wiley, 2018.

Abstract

Traditional task‐evoked brain activations are based on detection and estimation of signal change from the mean signal. By contrast, the low‐frequency steady‐state brain response (lfSSBR) reflects frequency‐tagging activity at the fundamental frequency of the task presentation and its harmonics. Compared to the activity at these resonant frequencies, brain responses at nonresonant frequencies are largely unknown. Additionally, because the lfSSBR is defined by power change, we hypothesize using Parseval's theorem that the power change reflects brain signal variability rather than the change of mean signal. Using a face recognition task, we observed power increase at the fundamental frequency (0.05 Hz) and two harmonics (0.1 and 0.15 Hz) and power decrease within the infra‐slow frequency band ( .955) of their spatial distribution and brain–behavior relationship at all frequency bands. Additionally, the reallocation of finite energy was observed across various brain regions and frequency bands, forming a particular spatiotemporal pattern. Overall, results from this study strongly suggest that frequency‐specific power and variability may measure the same underlying brain activity and that these results may shed light on different mechanisms between lfSSBR and brain activation, and spatiotemporal characteristics of energy reallocation induced by cognitive tasks.

Details

ISSN :
10659471
Volume :
39
Database :
OpenAIRE
Journal :
Human Brain Mapping
Accession number :
edsair.doi.dedup.....6e60679fa4df77e93abd0cb8943b3479