Key result
Transient arousal changes are associated with a recurrent pattern of fMRI, EEG, and autonomic changes, including brief signal reductions in salience and default-mode networks.
Why the study?
Removing non-neural autonomic hemodynamic changes from rsfMRI via regression may be inadequate if neuronal and autonomic activity covary.
Observational (n=27)
Proper measurement of functional brain connectivity with fMRI requires accounting for the co-variation of autonomic and neural changes during arousal state transitions.
Autonomic regression may inadequately remove confounds from rsfMRI connectivity; leaves open optimal denoising approaches for brain-autonomic studies.
Resting-state functional magnetic resonance imaging (rsfMRI) allows the study of functional brain connectivity based on spatially structured variations in neuronal activity. Proper evaluation of connectivity requires removal of non-neural contributions to the fMRI signal, in particular hemodynamic changes associated with autonomic variability. Regression analysis based on autonomic indicator signals has been used for this purpose, but may be inadequate if neuronal and autonomic activity covary. To investigate this potential co-variation, we performed rsfMRI experiments while concurrently acquiring electroencephalography and autonomic indicator signals, including heart rate, respiratory depth, and peripheral vascular tone. We identified a recurrent and systematic pattern of fMRI, EEG, and autonomic changes coincidental with intermittent arousal, suggesting arousal modulation. The temporal relationship between the various signals indicated combined neural and autonomic contribution to the fMRI signal, both of which involve widespread brain areas. The fMRI changes included brief signal reductions in salience and default-mode networks, and the thalamus, followed by a biphasic global change. These results suggest that proper measurement of functional connectivity with fMRI requires accounting for the full spectrum of autonomic and neural changes, as well as their co-variation during arousal state transitions.
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Gu et al. (2022) conducted an observational in Healthy (n=27). Transient arousal changes was evaluated on Spatiotemporal correlation of rsfMRI with EEG alpha power and physiological signals. Transient arousal changes are associated with a recurrent pattern of fMRI, EEG, and autonomic changes, including brief signal reductions in salience and default-mode networks.
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