TY - JOUR
T1 - Variability and task-responsiveness of electrophysiological dynamics
T2 - Scale-free stability and oscillatory flexibility
AU - Wainio-Theberge, Soren
AU - Wolff, Annemarie
AU - Gomez-Pilar, Javier
AU - Zhang, Jianfeng
AU - Northoff, Georg
N1 - Funding Information:
GN has received funding from the European Union's Horizon 2020 Framework Programme for Research and Innovation under the Specific Grant Agreement No. 785907 (Human Brain Project SGA2). GN is grateful for funding provided by UMRF, uOBMRI, CIHR (201103MOP-244752-BSBCECA-179644; 201103CCI-248496-CCI-CECA), the Canada-UK Artificial Intelligence Initiative (ES/T01279X/1), and PSI. JGP acknowledges funding from ?CIBER in Bioengineering, Biomaterials and Nanomedicine (CIBER-BBN)? through ?Instituto de Salud Carlos III?, co-funded with FEDER funds. Data were provided (in part) by the Human Connectome Project, WU-Minn Consortium (Principal Investigators: David Van Essen and Kamil Ugurbil; 1U54MH091657) funded by the 16 NIH Institutes and Centers that support the NIH Blueprint for Neuroscience Research; and by the McDonnell Center for Systems Neuroscience at Washington University. Data collection and sharing for this project was provided (in part) by the Cambridge Centre for Ageing and Neuroscience (CamCAN). CamCAN funding was provided by the UK Biotechnology and Biological Sciences Research Council (grant number BB/H008217/1), together with support from the UK Medical Research Council and University of Cambridge, UK.
Funding Information:
GN has received funding from the European Union's Horizon 2020 Framework Programme for Research and Innovation under the Specific Grant Agreement No. 785907 (Human Brain Project SGA2). GN is grateful for funding provided by UMRF , uOBMRI , CIHR ( 201103MOP-244752-BSBCECA-179644 ; 201103CCI-248496-CCI-CECA ), the Canada-UK Artificial Intelligence Initiative ( ES/T01279X/1 ), and PSI. JGP acknowledges funding from ‘CIBER in Bioengineering, Biomaterials and Nanomedicine (CIBER-BBN)’ through ‘Instituto de Salud Carlos III’, co-funded with FEDER funds. Data were provided (in part) by the Human Connectome Project, WU-Minn Consortium (Principal Investigators: David Van Essen and Kamil Ugurbil; 1U54MH091657 ) funded by the 16 NIH Institutes and Centers that support the NIH Blueprint for Neuroscience Research; and by the McDonnell Center for Systems Neuroscience at Washington University. Data collection and sharing for this project was provided (in part) by the Cambridge Centre for Ageing and Neuroscience (CamCAN). CamCAN funding was provided by the UK Biotechnology and Biological Sciences Research Council (grant number BB/H008217/1 ), together with support from the UK Medical Research Council and University of Cambridge, UK.
Publisher Copyright:
© 2022
PY - 2022/8/1
Y1 - 2022/8/1
N2 - Cortical oscillations and scale-free neural activity are thought to influence a variety of cognitive functions, but their differential relationships to neural stability and flexibility has never been investigated. Based on the existing literature, we hypothesize that scale-free and oscillatory processes in the brain exhibit different trade-offs between stability and flexibility; specifically, cortical oscillations may reflect variable, task-responsive aspects of brain activity, while scale-free activity is proposed to reflect a more stable and task-unresponsive aspect. We test this hypothesis using data from two large-scale MEG studies (HCP: n = 89; CamCAN: n = 195), operationalizing stability and flexibility by task-responsiveness and spontaneous intra-subject variability in resting state. We demonstrate that the power-law exponent of scale-free activity is a highly stable parameter, which responds little to external cognitive demands and shows minimal spontaneous fluctuations over time. In contrast, oscillatory power, particularly in the alpha range (8–13 Hz), responds strongly to tasks and exhibits comparatively large spontaneous fluctuations over time. In sum, our data support differential roles for oscillatory and scale-free activity in the brain with respect to neural stability and flexibility. This result carries implications for criticality-based theories of scale-free activity, state-trait models of variability, and homeostatic views of the brain with regulated variables vs. effectors.
AB - Cortical oscillations and scale-free neural activity are thought to influence a variety of cognitive functions, but their differential relationships to neural stability and flexibility has never been investigated. Based on the existing literature, we hypothesize that scale-free and oscillatory processes in the brain exhibit different trade-offs between stability and flexibility; specifically, cortical oscillations may reflect variable, task-responsive aspects of brain activity, while scale-free activity is proposed to reflect a more stable and task-unresponsive aspect. We test this hypothesis using data from two large-scale MEG studies (HCP: n = 89; CamCAN: n = 195), operationalizing stability and flexibility by task-responsiveness and spontaneous intra-subject variability in resting state. We demonstrate that the power-law exponent of scale-free activity is a highly stable parameter, which responds little to external cognitive demands and shows minimal spontaneous fluctuations over time. In contrast, oscillatory power, particularly in the alpha range (8–13 Hz), responds strongly to tasks and exhibits comparatively large spontaneous fluctuations over time. In sum, our data support differential roles for oscillatory and scale-free activity in the brain with respect to neural stability and flexibility. This result carries implications for criticality-based theories of scale-free activity, state-trait models of variability, and homeostatic views of the brain with regulated variables vs. effectors.
KW - Cortical oscillations
KW - Flexibility
KW - MEG
KW - Neural variability
KW - Scale-free activity
KW - Stability
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U2 - 10.1016/j.neuroimage.2022.119245
DO - 10.1016/j.neuroimage.2022.119245
M3 - Article
C2 - 35477021
AN - SCOPUS:85129461422
SN - 1053-8119
VL - 256
JO - NeuroImage
JF - NeuroImage
M1 - 119245
ER -