Exploring the neuronal and systemic physiological contributions to spontaneous cerebral fluctuations - Insights from functional MRI in The Maastricht Study

ObjectiveFunctional MRI (fMRI) is sensitive to changes in the blood oxygen level-dependent (BOLD) signal, which originates from neurovascular coupling, the mechanism that links neuronal activity to changes in cerebral blood flow. Isolating the native spontaneous neuronal fluctuations from the BOLD signal of the resting-state is challenging, as the signal induced by neuronal activity represents only a small part of this signal. Furthermore, many other non-neuronal (systemic) oscillations contribute, such as from the cardiovascular and respiratory system with frequencies partly overlapping those of the spontaneous fluctuations. The objective of this study is to investigate to what extent various systemic physiological signals are associated with the measured BOLD signal, in particular the frequency interval pertaining to the spontaneous cerebral fluctuations (10-100 mHz). Additionally, we investigate whether these associations were independent of cardiometabolic risk factors. MethodsWithin the population-based Maastricht Study, 3T resting-state functional MRI and physiological measures, covering cardiac, respiratory, myogenic, neurogenic, and endothelial activity, were acquired (n=1,651, 48% woman, aged 59{+/-}8 years). As both neuronal and non-neuronal physiological signals contain frequencies that vary over time, a wavelet transformation (WT) was used. Time-series were decomposed into seven wavelet subbands, and for each subband, the energy of the BOLD signal was calculated. Multivariable linear regression analysis was used to investigate the association of the physiological measures, in particular cognitive function, with the wavelet energy per subband, independent of cardiometabolic risk factors. ResultsWe found that physiological measures were associated with the energy of certain frequency subbands of the spectrum of the measured fMRI signal. Both cognitive performance and blood pressure variations, as measures of neurogenic and myogenic activity respectively, were associated with the energy of the frequency subband 3 (31.2-62.5 mHz). Furthermore, cardiac and respiratory activity were associated with the energy of the high frequency subband 1 (>125 mHz), and endothelial activity with the energy of low frequency subbands 6 and 7 (<10 mHz). Part of these associations were dependent on cardiometabolic risk factors. ConclusionWe found an association between myogenic and neurogenic activity and the frequency specific BOLD signal. Our findings highlight the strong intertwining of neuronal, vascular, and cardiometabolic activity and emphasize the importance of a proper selection of the resting-state frequency range in fMRI studies on cognitive function.