Robust and replicable effects of ageing on resting-state brain electrophysiology measured with MEG

In investigations of brain electrophysiology, non-invasive recordings shed light on the decline of neuronal function as individuals age. To address the challenge of preserving brain health in the elderly, novel methods are needed to glean clinically relevant insights from these recordings. While alterations in neuronal dynamics linked to ageing have been detected in the power spectra of EEG and MEG recordings, inconsistencies in methodology across studies impede the formation of a cohesive understanding of these effects.

This paper estimates a comprehensive frequency and spatial profile of the age-related changes in eyes-closed resting-state MEG employing the GLM-Spectrum. This standardized data format enables sharing and meta-analysis, as well as the calculation of statistical power for future research planning. By analyzing multiple open-access MEG datasets, the study reveals that the age-related effects on MEG recordings are consistent and remain stable even after accounting for common covariates.

The distinct components within the full-frequency profile manifest varying effect sizes, emphasizing the necessity of tailoring sample-size planning to the specific aspects of interest when studying age-related changes. Moreover, the age-related frequency profile demonstrates robustness to a wide range of common covariates, albeit partially robust when grey matter volume is taken into account.

The authors caution that a study may appear adequately powered to detect an age effect, yet it could become underpowered if the analysis is designed to isolate an age-related signal that is linearly separable from another age-relevant covariate, such as grey matter volume.