The Temporal Structures and Functional Significance of Scale-free Brain Activity

Abstract

SUMMARY Scale-free dynamics, with a power spectrum following P ∝ f-β, are an intrinsic feature of many complex processes in nature. In neural systems, scale-free activity is often neglected in electrophysiological research. Here, we investigate scale-free dynamics in human brain and show that it contains extensive nested frequencies, with the phase of lower frequencies modulating the amplitude of higher frequencies in an upward progression across the frequency spectrum. The functional significance of scale-free brain activity is indicated by task performance modulation and regional variation, with β being larger in default network and visual cortex and smaller in hippocampus and cerebellum. The precise patterns of nested frequencies in the brain differ from other scale-free dynamics in nature, such as earth seismic waves and stock market fluctuations, suggesting system-specific generative mechanisms. Our findings reveal robust temporal structures and behavioral significance of scale-free brain activity and should motivate future study on its physiological mechanisms and cognitive implications.

Mesoscale infraslow spontaneous membrane potential fluctuations recapitulate high-frequency activity cortical motifs

“…Furthermore, we were not limited to only sensorimotor ROIs in our approach. The interconnected nature of the activity structure of infraslow and slow activity is consistent with a cross-frequency phase-amplitude coupling relationship that has previously been indicated for infraslow fluctuations in EEG and MEG recordings in human subjects [13][14][15]60 .…”

“…Interestingly, we also note the presence of substantial signal power in the infraslow frequency range (o0.1 Hz). This activity lacked the fully resolved structure of a local peak in the power spectrum that typically signifies truly oscillatory activity and thus has been interpreted as underlying low-frequency asynchronous brain activity 2,10,14 . We quantified infraslow EEG signal power across an infraslow frequency range (0.009-0.08 Hz) typically associated with brain activity used in functional connectivity analyses of resting-state functional magnetic resonance imaging (fc-fMRI) studies 18,35 (Fig.…”

“…In the developing brain, electrophysiological infraslow activity in the form of neuronal activity transients or bursting activity has been linked with the development of neuronal networks 11,12 , whereas in the adult brain, infraslow activity has been demonstrated to synchronize with higher-frequency brain activity 13,14 and to correlate to variability in behavioural performance 15,16 . Renewed focus on the nature of spontaneous resting-state infraslow activity has been precipitated due to an immense proliferation of functional neuroimaging studies that have revealed much about the brain's functional organization and have identified what has been described as the brain's Default Mode Network (DMN) 17 , a network of brain structures that are coherently, highly active at rest and reduced during active task performance 18 .…”

“…Renewed focus on the nature of spontaneous resting-state infraslow activity has been precipitated due to an immense proliferation of functional neuroimaging studies that have revealed much about the brain's functional organization and have identified what has been described as the brain's Default Mode Network (DMN) 17 , a network of brain structures that are coherently, highly active at rest and reduced during active task performance 18 . The DMN may represent a consistent functional organizing principle and infraslow spontaneous activity of this kind may play a profound role in modulating and/or synchronizing higher-frequency brain activity due to cross-frequency, phase-amplitude coupling 10,13,14 . Furthermore, alterations in its structure have been linked with neurodegenerative and psychiatric disease [19][20][21] suggesting the potential for the identification of novel biomarkers and a greater understanding of both disease progression and recovery.…”

Disrupted brain network functional dynamics and hyper‐correlation of structural and functional connectome topology in patients with breast cancer prior to treatment

“…However, their study involved a task‐fMRI paradigm, whereas ours involved resting‐state fMRI. Hurst exponent is highest during resting state and tends to decrease with increased task load (He, 2011; He, Zempel, Snyder, & Raichle, 2010). Therefore, the Churchill et al.…”