Magnetic Resonance Imaging of Human Brain Anatomy and Function

National Institute Of Neurological Disorders And Stroke

Investigators

Linked publications, trials & patents

Abstract

Previous work in the lab has shown that signal variability in fMRI strongly depends on arousal state, and that both neuronal and autonomic activity contribute to this variability. To comprehensively investigate underlying mechanisms, we have been performing overnight fMRI-EEG studies across the sleep-wake cycle, while collecting autonomic indicator signals. After completing our pilot study on 16 subjects, we started a main study under which we now have collected two entire nights of data on 15 subjects. Initial data analysis, completed in previous years, showed a strong correlation between peripheral vascular tone (measured from the finger skin with photoplethysmography) and fMRI global signal (GS), in particular during light (N1 and N2) sleep (and REM), but not N3. We attributed this to sympathetic constriction of both cerebral and peripheral vasculature. During light sleep, these constrictions appeared precipitated by EEG complexes. We developed an explanatory model postulating that joint fMRI and autonomic effects may be caused by autonomic arousals that involve sympathetic activation. Outside N3 sleep, we also found strong correlations between fMRI GS and CSF flow through the cerebral aqueduct. CSF flow may have relevance for brain waste clearance through the glymphatic system as it improves CSF solute mixing and possible a net transport out of the brain. We developed an explanatory model confirming an earlier report that this CSF flow may be generated by the cerebral blood volume changes associated with the fMRI signal. This new type of CSF flow co-occurs with previously reported pulsations associated with cardiac and respiratory cycles but may be of larger amplitude; it therefore may have an unique role in glymphatic clearance. We are currently developing methodology to accurately quantify CSF flow volumes associated with the individual mechanisms. In parallel, we have explored various approaches to separate autonomic and neuronal contributions to the fMRI signal. A preliminary analysis pipeline was developed by which various confounds are regressed out of the fMRI signal in a time-segmented fashion. Removed confounds include cardiac and respiratory cycles, motion, respiratory flow rate, and peripheral vascular tone.