Spontaneous Alpha and Theta Oscillations Are Related to Complementary Aspects of Cognitive Control in Younger and Older Adults

Abstract

The resting-state human electroencephalogram (EEG) power spectrum is dominated by alpha (8–12 Hz) and theta (4–8 Hz) oscillations, and also includes non-oscillatory broadband activity inversely related to frequency (1/f activity). Gratton proposed that alpha and theta oscillations are both related to cognitive control function, though in a complementary manner. Alpha activity is hypothesized to facilitate the maintenance of representations, such as task sets in preparation for expected task conditions. In contrast, theta activity would facilitate changes in representations, such as the updating of task sets in response to unpredicted task demands. Therefore, theta should be related to reactive control (which may prompt changes in task representations), while alpha may be more relevant to proactive control (which implies the maintenance of current task representations). Less is known about the possible relationship between 1/f activity and cognitive control, which was analyzed here in an exploratory fashion. To investigate these hypothesized relationships, we recorded eyes-open and eyes-closed resting-state EEG from younger and older adults and subsequently tested their performance on a cued flanker task, expected to elicit both proactive and reactive control processes. Results showed that alpha power and 1/f offset were smaller in older than younger adults, whereas theta power did not show age-related reductions. Resting alpha power and 1/f offset were associated with proactive control processes, whereas theta power was related to reactive control as measured by the cued flanker task. All associations were present over and above the effect of age, suggesting that these resting-state EEG correlates could be indicative of trait-like individual differences in cognitive control performance, which may be already evident in younger adults, and are still similarly present in healthy older adults.

Dynamics of alpha suppression and enhancement may be related to resource competition in cross-modal cortical regions

“…Nonetheless, some alpha suppression should still occur when a new sound is presented. Of note, this prediction regarding stimulus-related alpha suppression occurs on top of the well-known general alpha reduction when the eyes open after being closed (e.g., Adrian and Matthews, 1934 ; Barry et al, 2007 ; Berger, 1929 ; Polich, 1997 ; Clements et al, 2021a ). Additionally, we hypothesize that it will be easier to generate and maintain new representations of auditory stimuli with closed than with open eyes because there will be little competition between vision and hearing, and that should be reflected in alpha dynamics.…”

“…Three blocks were resting-state: one with eyes open, one with eyes closed, and one with eyes open but wearing an eye-mask to block visual input. The resting state data were used for other purposes and are reported elsewhere ( Clements et al, 2021a ; Gyurkovics et al, 2021 ). The masked data were inconclusive 1 and 2 and are not described further.…”

“…Power values were baseline corrected using condition-specific subtractive baselining. We have previously shown that, compared to divisive baselining, subtractive baselining minimizes the potential of Type I errors that might occur due to the effect of the aperiodic, 1 /f component of power spectra ( Clements et al, 2021a , 2021b ; Gyurkovics et al, 2021 ). Baseline activity differs for the eyes open and eyes closed conditions, especially in the aperiodic 1/ f activity (as well as oscillatory activity), such that the eyes-closed condition has a greater 1/ f offset than the eyes-open condition ( Supp.…”

“…We chose to analyze the time-frequency space over a frontocentral subset of electrodes (Fz, FCz, Cz, CPz FC1, FC2, C1, C2) where theta is typically observed and a posterior subset of electrodes where alpha is typically the largest (Pz, POz, Oz, PO3, PO4, PO7, PO8, O1, and O2). These locations were informed by assessing the scalp topographies of activity compared to baseline and matched those used in a previous publication ( Clements, et al, 2021a ). We used a permutation testing-based approach to assess the difference between baseline and post-stimulus activity as well as the difference between the eyes closed and eyes open time-frequency “maps” (i.e., a time x frequency heat plot representing, for each frequency [row] the power at each time point [column] relative to the average baseline value).…”

Stimulus-induced changes in 1/f-like background activity in EEG

“…Nevertheless, changes in the shape of 1/f activity in the brain have been linked to shifts in the balance between excitatory and inhibitory synaptic inputs in local neural circuits (Gao et al, 2017). Furthermore, although 1/f activity is often regarded as noise to be excluded before performing frequency-domain analyses (Gyurkovics et al, 2021), the shape parameters of 1/f activity have been found to be related to behavior and cognition (Bódizs et al, 2021;Clements, Bowie, et al, 2021;Immink et al, 2021;Lendner et al, 2020;Ouyang et al, 2020).…”