Time in Brain: How Biological Rhythms Impact on EEG Signals and on EEG-Derived Brain Networks

被引:24
作者
Lehnertz, Klaus [1 ,2 ,3 ]
Rings, Thorsten [1 ,2 ]
Broehl, Timo [1 ,2 ]
机构
[1] Univ Bonn, Dept Epileptol, Med Ctr, Bonn, Germany
[2] Univ Bonn, Helmholtz Inst Radiat & Nucl Phys, Bonn, Germany
[3] Univ Bonn, Interdisciplinary Ctr Complex Syst, Bonn, Germany
来源
FRONTIERS IN NETWORK PHYSIOLOGY | 2021年 / 1卷
关键词
electroencephalography; biological rhythms; brain dynamics; statistical moments; synchronization; functional brain networks; clustering coefficient; centrality; AGE-RELATED-CHANGES; FUNCTIONAL CONNECTIVITY; CIRCADIAN-RHYTHMS; SPECTRAL-ANALYSIS; HUMAN SLEEP; SCALE; SYNCHRONIZATION; HEALTHY; POWER; FLUCTUATIONS;
D O I
10.3389/fnetp.2021.755016
中图分类号
Q4 [生理学];
学科分类号
071003 ;
摘要
Electroencephalography (EEG) is a widely employed tool for exploring brain dynamics and is used extensively in various domains, ranging from clinical diagnosis via neuroscience, cognitive science, cognitive psychology, psychophysiology, neuromarketing, neurolinguistics, and pharmacology to research on brain computer interfaces. EEG is the only technique that enables the continuous recording of brain dynamics over periods of time that range from a few seconds to hours and days and beyond. When taking long-term recordings, various endogenous and exogenous biological rhythms may impinge on characteristics of EEG signals. While the impact of the circadian rhythm and of ultradian rhythms on spectral characteristics of EEG signals has been investigated for more than half a century, only little is known on how biological rhythms influence characteristics of brain dynamics assessed with modern EEG analysis techniques. At the example of multiday, multichannel non-invasive and invasive EEG recordings, we here discuss the impact of biological rhythms on temporal changes of various characteristics of human brain dynamics: higher-order statistical moments and interaction properties of multichannel EEG signals as well as local and global characteristics of EEG-derived evolving functional brain networks. Our findings emphasize the need to take into account the impact of biological rhythms in order to avoid erroneous statements about brain dynamics and about evolving functional brain networks.
引用
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页数:13
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共 143 条
[1]   Estimating the reproducibility of psychological science [J].
Aarts, Alexander A. ;
Anderson, Joanna E. ;
Anderson, Christopher J. ;
Attridge, Peter R. ;
Attwood, Angela ;
Axt, Jordan ;
Babel, Molly ;
Bahnik, Stepan ;
Baranski, Erica ;
Barnett-Cowan, Michael ;
Bartmess, Elizabeth ;
Beer, Jennifer ;
Bell, Raoul ;
Bentley, Heather ;
Beyan, Leah ;
Binion, Grace ;
Borsboom, Denny ;
Bosch, Annick ;
Bosco, Frank A. ;
Bowman, Sara D. ;
Brandt, Mark J. ;
Braswell, Erin ;
Brohmer, Hilmar ;
Brown, Benjamin T. ;
Brown, Kristina ;
Bruening, Jovita ;
Calhoun-Sauls, Ann ;
Callahan, Shannon P. ;
Chagnon, Elizabeth ;
Chandler, Jesse ;
Chartier, Christopher R. ;
Cheung, Felix ;
Christopherson, Cody D. ;
Cillessen, Linda ;
Clay, Russ ;
Cleary, Hayley ;
Cloud, Mark D. ;
Cohn, Michael ;
Cohoon, Johanna ;
Columbus, Simon ;
Cordes, Andreas ;
Costantini, Giulio ;
Alvarez, Leslie D. Cramblet ;
Cremata, Ed ;
Crusius, Jan ;
DeCoster, Jamie ;
DeGaetano, Michelle A. ;
Della Penna, Nicolas ;
den Bezemer, Bobby ;
Deserno, Marie K. .
SCIENCE, 2015, 349 (6251)
[2]   A comprehensive review of EEG-based brain-computer interface paradigms [J].
Abiri, Reza ;
Borhani, Soheil ;
Sellers, Eric W. ;
Jiang, Yang ;
Zhao, Xiaopeng .
JOURNAL OF NEURAL ENGINEERING, 2019, 16 (01)
[3]   Two circadian rhythms in the human electroencephalogram during wakefulness [J].
Aeschbach, D ;
Matthews, JR ;
Postolache, TT ;
Jackson, MA ;
Giesen, HA ;
Wehr, TA .
AMERICAN JOURNAL OF PHYSIOLOGY-REGULATORY INTEGRATIVE AND COMPARATIVE PHYSIOLOGY, 1999, 277 (06) :R1771-R1779
[4]   EEG-Based Neurohaptics Research: A Literature Review [J].
Alsuradi, Haneen ;
Park, Wanjoo ;
Eid, Mohamad .
IEEE ACCESS, 2020, 8 :49313-49328
[5]   Age increases brain complexity [J].
Anokhin, AP ;
Birbaumer, N ;
Lutzenberger, W ;
Nikolaev, A ;
Vogel, F .
ELECTROENCEPHALOGRAPHY AND CLINICAL NEUROPHYSIOLOGY, 1996, 99 (01) :63-68
[6]   Passive BCI beyond the lab: current trends and future directions [J].
Arico, P. ;
Borghini, G. ;
Di Flumeri, G. ;
Sciaraffa, N. ;
Babiloni, F. .
PHYSIOLOGICAL MEASUREMENT, 2018, 39 (08)
[7]   A Tutorial Review of Functional Connectivity Analysis Methods and Their Interpretational Pitfalls [J].
Bastos, Andre M. ;
Schoffelen, Jan-Mathijs .
FRONTIERS IN SYSTEMS NEUROSCIENCE, 2016, 9
[8]   Under-sampling in epilepsy: Limitations of conventional EEG [J].
Baud, Maxime O. ;
Schindler, Kaspar ;
Rao, Vikram R. .
CLINICAL NEUROPHYSIOLOGY PRACTICE, 2021, 6 :41-49
[9]   Does the 1/f frequency scaling of brain signals reflect self-organized critical states? [J].
Bedard, C. ;
Kroger, H. ;
Destexhe, A. .
PHYSICAL REVIEW LETTERS, 2006, 97 (11)
[10]   Being critical of criticality in the brain [J].
Beggs, John M. ;
Timme, Nicholas .
FRONTIERS IN PHYSIOLOGY, 2012, 3