Aperiodic and Periodic Components of Ongoing Oscillatory Brain Dynamics Link Distinct Functional Aspects of Cognition across Adult Lifespan

Abstract

In accordance with the data usage agreement for CAMCAN dataset, the article has been submitted as open access.

Resting EEG spectral slopes are associated with age-related differences in information processing speed

“…Thus, combining the current data with past work, it appears that the flattening of the exponent with age is a reliable effect (Tran et al, 2020;Waschke et al, 2017). Further, the exponent is related to cognition not only in tightly controlled laboratory tasks (Thuwal et al, 2021, Tran et al, 2020, but also in validated clinical tests (the Coding subtest of the RBANS in the present data).…”

“…Behaviorally, some of these and other studies have linked flatter slopes in older adults to poorer performances on tasks of spatial attention (Tran et al, 2020) and visual-short-term memory (Thuwal et al, 2021). Still other work has linked changes in the spectral offset to poorer cognitive control across the adult age range (Clements et al, 2021), while spectral slope has been linked to speeded target detection in adults aged 40 and below (Ouyang et al, 2020).…”

Can you hear me now? Momentary increase in smartphone usage enhances neural processing of task-irrelevant sound tones

“…However, we did not observe such a gradient either using the continuous wavelet transform or using Welch's method. The exponent was higher at the frontal electrodes, to become lower in the more posterior electrodes, and then increased again over the central electrodes akin to what has been reported in young adults (Thuwal et al, 2021). Another factor (apart from age of the participants) that may have contributed to the distinct gradient compared to the initial report is that our measurements were conducted while actively engaged in a task, and the exponent is known to alter topology in a task-dependent manner (Waschke et al, 2021).…”

Oscillatory and aperiodic neural activity jointly predict language learning

“…The effect of differing levels of 1/ f slope on, for instance, beta power and behavioural performance likely reflect more nuanced inter-individual differences in information processing capacities (Dziego et al, 2022; Immink, Cross et al, 2021; Thuwal, Banerjee, & Roy, 2021), which may explain behavioural gains that are otherwise related to the manifestation of oscillatory activity (e.g., Kepinska et al, 2017). For example, here we observed that a decrease in beta power predicted better behavioural performance for flexible rules, while the inverse was seen for fixed word order rules.…”