Age-related changes in “cortical” 1/f dynamics are linked to cardiac activity

Abstract

The power of electrophysiologically measured cortical activity decays 1/fX. The slope of this decay (i.e. the spectral exponent) is modulated by various factors such as age, cognitive states or psychiatric/neurological disorders. Interestingly, a mostly parallel line of research has shown similar effects for the spectral exponent in the electrocardiogram (ECG). This raises the question whether these bodywide changes in spectral exponents are independent or if the 'cortically' measured decay in power is explained by cardiac activity captured by cortical sensors (via volume conduction). Focusing on well-established age-related changes in spectral exponents, we analyzed a total of 1282 recordings of magnetoencephalography (MEG) resting state measurements with concurrent ECG in an age-diverse sample. We show that age-related changes of the spectral exponent of neural power spectra are largely explained by cardiac activity. Our results raise concerns when interpreting aperiodic activity as 'cortical' in absence of ECG recordings.

Cardiometabolic state links neurovascular burden with brain structure and function across age: evidence from EEG and MRI

“…This result suggests that the cardiometabolic state links structural imprinting of neuroinflammatory pathways seen in WMHs and ventricular enlargement with EEG aperiodic activity. Although it has been shown that the 1/f exponent is related to neuronal circuit properties such as the balance between excitation and inhibition (Gao et al, 2017;Medel et al, 2023;Trakoshis et al, 2020), recent evidence links this global electrophysiological signature with physiological signals, such as oxygen availability (Coronel-Oliveros et al, 2024), respiration (Kluger et al, 2023) and cardiac measures (Schmidt et al, 2022). Our work provides evidence that this relation does not suggest an artefactual origin but rather a natural consequence of the close relation between electrophysiological function, measured by 1/f exponent background signal, and the energetic requirements of neural circuits.…”