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

Authors

Yifeng Wang, University of Electronic Science and Technology of China
Wang Chen, University of Electronic Science and Technology of China
Liangkai Ye, University of Electronic Science and Technology of China
Bharat B. Biswal, University of Electronic Science and Technology of China
Xuezhi Yang, University of Electronic Science and Technology of China
Qijun Zou, University of Electronic Science and Technology of China
Pu Yang, University of Electronic Science and Technology of China
Qi Yang, University of Electronic Science and Technology of China
Xinqi Wang, University of Electronic Science and Technology of China
Qian Cui, University of Electronic Science and Technology of China
Xujun Duan, University of Electronic Science and Technology of China
Wei Liao, University of Electronic Science and Technology of China
Huafu Chen, University of Electronic Science and Technology of China

Document Type

Article

Publication Date

5-1-2018

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 (<0.1 Hz), suggesting a multifrequency energy reallocation. The consistency of power and variability was demonstrated by the high correlation (r >.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.

Identifier

85041236084 (Scopus)

Publication Title

Human Brain Mapping

External Full Text Location

https://doi.org/10.1002/hbm.23992

e-ISSN

10970193

ISSN

10659471

PubMed ID

29389047

First Page

2121

Last Page

2132

Issue

5

Volume

39

Grant

31400901

Fund Ref

National Natural Science Foundation of China

Recommended Citation

Wang, Yifeng; Chen, Wang; Ye, Liangkai; Biswal, Bharat B.; Yang, Xuezhi; Zou, Qijun; Yang, Pu; Yang, Qi; Wang, Xinqi; Cui, Qian; Duan, Xujun; Liao, Wei; and Chen, Huafu, "Multiscale energy reallocation during low-frequency steady-state brain response" (2018). Faculty Publications. 8693.
https://digitalcommons.njit.edu/fac_pubs/8693