Three-year reliability of MEG resting-state oscillatory power

Abstract

Introduction: Resting-state oscillatory activity has been extensively studied across a wide array of disorders. Establishing which spectrally- and spatially-specific oscillatory components exhibit test-retest reliability is essential to move the field forward. While studies have shown short-term reliability of MEG resting-state activity, no studies have examined test-retest reliability across an extended period of time to establish the stability of these signals which is critical for reproducibility. Methods: We examined 18 healthy adults age 23 – 61 who completed three visits across three years. For each visit participants completed both a resting state MEG and structural MRI scan. MEG data were source imaged, and the cortical power in canonical frequency bands (delta, theta, alpha, beta, low gamma, high gamma) was computed Intra-class correlation coefficients (ICC) were then calculated across the cortex for each frequency band. Results: Over three years, power in the alpha and beta bands displayed the highest reliability estimates, while gamma showed the lowest estimates of three-year reliability. Spatially, delta, alpha, and beta all showed the highest degrees of reliability in the parietal cortex. Interestingly, the peak signal for each of these frequency bands was located outside of the parietal cortex, suggesting that reliability estimates were not solely dependent on the signal-to-noise ratio. Conclusion: Oscillatory resting-state power in parietal delta, posterior beta, and alpha across most of the cortex are reliable across three years and future MEEG studies may focus on these measures for the development of specific markers.

Eyes-closed versus eyes-open differences in spontaneous neural dynamics during development

“…Finally, care should be taken to interpret the data in the context of the specific analysis that we performed. Notably, the current results represent the difference between EC and EO conditions in normalized spectral units, where each frequency band is quantified as a percentage of the total spectral power, consistent with several previous reports ( Candelaria-Cook et al, 2022 ; Lew et al, 2021 ; Niso et al, 2019 ; Ott et al, 2021 ; Wiesman et al, 2021 , but see Muthuraman et al 2015 who compared absolute power). Given that the total absolute power was greater in the EC compared to EO condition, it is possible that the stronger relative delta, theta, beta, and gamma power in the EO condition could instead show that the distribution of absolute power among the canonical bands differed between the conditions, with alpha having a much larger share of the overall absolute power in the EC relative to the EO condition.…”

“…Power spectrum densities (PSD) were estimated using Welch’s method ( Welch, 1967 ) on each four-second epoch, with one second sliding Hamming windows overlapping at 50%. The PSDs were then normalized within each frequency band to the total power across the total frequency spectrum per condition, consistent with previous reports on resting state MEG data ( Candelaria-Cook et al, 2022 ; Lew et al, 2021 ; Niso et al, 2019 ; Ott et al, 2021 ; Wiesman et al, 2021 , 2022 ). The PSD maps were then averaged within each participant, separated by the two conditions, and for each of the five frequency bands separately, resulting in 10 PSD maps for each participant.…”

Altered spontaneous cortical activity predicts pain perception in individuals with cerebral palsy

“…Furthermore, increased spontaneous cortical activity within the beta band has previously been illustrated in patients with chronic pain, 64–68 and when measured using magnetoencephalographic (MEG) imaging has been shown to be highly stable over at least a three-year period. 69 The latter findings are highly important for any potential neural marker. Thus, a potential link may exist between disruptions in the brain’s intrinsic spontaneous cortical activity and the increased pain perception experienced by individuals with CP.…”

Oscillatory markers of neuroHIV-related cognitive impairment and Alzheimer’s disease during attentional interference processing

“…MEG enables quantification of multi-spectral oscillatory activity including responses in the theta (4-8 Hz) and alpha (8-14 Hz) bands, which are known to critically support attention processing [16][17][18][19]. Further, recent work has shown that MEG responses are stable over at least three years in adults [20,21] and vary systematically with mental/task states [22], both of which are critical for the development of neural markers of disease. However, less is understood about the impact of disease progression on MEG responses.…”