Coupled electrophysiological, hemodynamic, and cerebrospinal fluid oscillations in human sleep

Abstract

Sleep is essential for both cognition and maintenance of healthy brain function. Slow waves in neural activity contribute to memory consolidation, whereas cerebrospinal fluid (CSF) clears metabolic waste products from the brain. Whether these two processes are related is not known. We used accelerated neuroimaging to measure physiological and neural dynamics in the human brain. We discovered a coherent pattern of oscillating electrophysiological, hemodynamic, and CSF dynamics that appears during non-rapid eye movement sleep. Neural slow waves are followed by hemodynamic oscillations, which in turn are coupled to CSF flow. These results demonstrate that the sleeping brain exhibits waves of CSF flow on a macroscopic scale, and these CSF dynamics are interlinked with neural and hemodynamic rhythms.

Fig. 1:. Large oscillations in CSF signals appear in the fourth ventricle during sleep.

A) Example scan positioning. Thick yellow line: position of the functional image relative to the anatomy. The bottom edge intersects with the fourth ventricle (red arrow), allowing CSF inflow to be measured. A subset of the 40 acquired slices are displayed. B) Example functional image from the bottom slice: inflow through the ventricle is detected as a bright signal (red arrow). C) EEG spectrogram from this subject shows long periods of NREM sleep and wake (~10 Hz occipital alpha). D) Behavioral responses from this subject. E) Timeseries of a single CSF voxel (smoothed with 10-TR kernel) shows large slow dynamics in sleep, that subside during wakefulness. F) Mean power spectral density (PSD) of occipital EEG confirms slow-delta power in sleep, as opposed to high alpha power in wake (n=13 subjects sleep; 11 subjects wake). G) PSD of CSF signal shows increased 0.05 Hz power during sleep (n=13 subjects sleep; 11 subjects wake). Shaded region is 95% CIs; red lines and star mark non-overlapping CIs. H) Low-frequency (LF, 0–0.1 Hz) CSF power increased during sleep (n=11 subjects for pairwise comparison). I) This sleep-selective power increase was specific to the ventricle ROI and not observed in a neighboring size-matched control ROI (n=11 subjects).

Fig. 2:. Ventricle signals correspond to a 0.05 Hz pulsatile inflow of CSF.

A) Schematic of acquisition: new CSF flowing into the imaging volume will generate bright signals. B) Inflow signals will be largest in the bottom slice, and decrease in amplitude inwards. If flow exceeds the critical velocity, then CSF in the bottom slice is completely replaced and signal amplitudes are large in inner slices as well. C) Mean amplitude across slices decays in ascending slices. Error bars are standard error across all sleep segments with the ROI present in 4 contiguous slices (n=129 segments, 11 subjects). D) Example timeseries from the bottom slices of the imaging volume in the 4th ventricle demonstrates largest signal in the lower slices (e.g. 2nd) and smaller signals in higher slices (e.g. 4th). Orange arrows schematically illustrate flow velocity (larger arrows=higher velocity) and black arrows point out individual events.

Fig. 3:. CSF flow oscillations are anticorrelated to a hemodynamic oscillation in the cortical gray matter that appears during sleep, with CSF flow increasing when blood volume decreases.

A) Example timeseries of the cortical gray matter BOLD signal and the mean CSF signal from one subject. During wake, signals are low-amplitude and synchronized to respiration (0.25 Hz). B) During sleep, a large-amplitude BOLD oscillation appears, and its timecourse is coupled to the ventricle CSF signal (~0.05 Hz). C) The mean cortical gray matter BOLD signal power increases during sleep (n=11 subjects for pairwise test). D) The mean cross-correlation between the zero-thresholded negative derivative of BOLD and CSF signals shows strong correlation (n=176 segments, 13 subjects). Shaded blue is standard error across segments; black dashed line is 95% interval of shuffled distribution. E) Example timeseries showing the correlation, suggesting that CSF flows up the fourth ventricle when cerebral blood volume decreases.

Fig. 4:. EEG slow-delta waves are coupled to and precede BOLD and CSF oscillations.

A) The mean amplitude envelope of slow-delta EEG; B) mean derivative of BOLD; and C) mean CSF signal, all locked to the peaks of CSF waves during sleep. Shaded region is standard error across peak-locked trials (n=123 peaks). D) Calculated impulse response of the CSF signal to the EEG envelope shows a similar timecourse to previously established hemodynamic models. Shading is standard deviation across model folds. E) Diagram of model linking the timecourse of neural activity to CSF flow. Variables include cerebral blood flow (CBF) and cerebral blood volume (CBV).