Adult lifespan trajectories of neuromagnetic signals and interrelations with cortical thickness

Extensive MEG time-series phenotyping unveils neural markers predictive of age

“…Again, previous studies have identified the temporal cortex as an area associated with strong M/EEG power increases across the adult lifespan 3,4 , with an increase over the adult lifespan. However, the signal amplitude is not a normalized measure and strongly varies within and across individuals, hampering the distinction between the age groups and the generalizability of the model across the lifespan.…”

“…Hence, algorithms sensitive to non-linear relationships might yield different outcomes for some of the features investigated in this study. Indeed, previous work has observed quadratic age trajectories for MEG characteristics in the beta-gamma range 3,4,7 . However, machine-learning techniques detecting non-linear variability often yield less interpretable results.…”

“…Power and connectivity measures were estimated in four frequency bands, i.e., theta (4-8 Hz), alpha (8-13 Hz), beta (13-30 Hz) and gamma . We also passed the source power spectrum (1-60 Hz) to the specparam algorithm 39 with the following settings: peak width limits [1][2][3][4][5][6][7][8]; maximum number of peaks: infinitive; minimum peak height: 0; and aperiodic mode: fixed. This resulted in an aperiodic component (1/f exponent or slope) and periodic ("oscillatory") components, here referred to as adjusted power.…”

“…Efforts to delineate linear and non-linear age effects on neurophysiological activity using large-scale datasets have increased in recent years. Notable changes of spectral characteristics during rest have been described in distinct brain regions, spanning childhood and adolescence (for example 1,2 ), and a broad age range during adulthood [3][4][5] . These studies have been seminal in developing a deeper understanding of M/EEG measures widely applied in clinical and cognitive neurosciences.…”

“…These studies have been seminal in developing a deeper understanding of M/EEG measures widely applied in clinical and cognitive neurosciences. A common and early observation is that low-frequency power decreases and high-frequency power increases linearly with age [6][7][8][9][10] , with the most pronounced changes in frontal and temporal areas of the brain [2][3][4]11 . Studies on the brain's functional connectome are less frequent and consistent partly due to the various connectivity measures used, relying on either amplitude or phase information of the signals.…”