State-dependent alpha peak frequency shifts: Experimental evidence, potential mechanisms and functional implications

Abstract

Neural populations produce complex oscillatory patterns thought to implement brain function. The dominant rhythm in the healthy adult human brain is formed by alpha oscillations with a typical power peak most commonly found between 8 and 12Hz. This alpha peak frequency has been repeatedly discussed as a highly heritable and stable neurophysiological "trait" marker reflecting anatomical properties of the brain, and individuals' general cognitive capacity. However, growing evidence suggests that the alpha peak frequency is highly volatile at shorter time scales, dependent on the individuals' "state". Based on the converging experimental and theoretical results from numerous recent studies, here we propose that alpha frequency variability forms the basis of an adaptive mechanism mirroring the activation level of neural populations which has important functional implications. We here integrate experimental and computational perspectives to shed new light on the potential role played by shifts in alpha peak frequency and discuss resulting implications. We further propose a potential mechanism by which alpha oscillations are regulated in a noisy network of spiking neurons in presence of delayed feedback.

From thoughtless awareness to effortful cognition: alpha - theta cross-frequency dynamics in experienced meditators during meditation, rest and arithmetic

“…Based on this mathematical reality, it has been recently posited that transient changes in peak frequencies within different brain rhythms 24,25,43,56 could reflect a key mechanism for coordinating cross-frequency coupling and decoupling in the brain (for extent see Klimesch, 2012Klimesch, , 2013Klimesch, , 2018. In this view, when information integration is needed to accomplish a specific task, the peak frequency arrangement of task-relevant rhythms is anticipated to change into a harmonic relationship in order to facilitate the communication between their underlying neural networks via cross-frequency phase synchronization.…”

Neural oscillations and connectivity characterizing the state of tonic experimental pain in humans

“…The previous studies used passive control conditions whereas we used an active control condition. As cognitive load can influence the peak alpha frequency (Haegens, Cousijn, Wallis, Harrison, & Nobre, 2014;Mierau, Klimesch, & Lefebvre, 2017), a comparison of pain to different control conditions can yield different results. In the present study, we chose an active control condition whose cognitive load was intended to match that of the pain condition.…”

Frequency and power of human alpha oscillations drift systematically with time-on-task

“…during trial baselines), neural oscillators are often assumed to spontaneously fluctuate around their mean frequency and power (Furushima et al, 2017;Romei et al, 2007;Samaha and Postle, 2015), leading in the case of alpha activity to the characteristic, band-limited alpha peak in the power spectrum. However, across the course of an experimental session, tonic power changes in certain frequencies (such as an increase in alpha-band power) (Kasten et al, 2016;Mathewson et al, 2009;Mathewson et al, 2015;Simon et al, 2011) and state-and stimulus-dependent fluctuations in oscillation peak frequency have been reported (Babu Henry Samuel et al, 2018;Haegens et al, 2014;Nelli et al, 2017), even during two minute resting-state EEG recordings (Cohen, 2014; for an overview see Mierau et al, 2017). These non-stationarities of oscillatory activity are likely of theoretical importance but are rarely accounted for when analysing experimental data.…”