Tracking Sleep-Linked Brain Fluid Dynamics Using Modified fNIRS: A Novel Noninvasive Window into Glymphatic Function
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Background
The glymphatic system, a brain-wide perivascular and interstitial waste and signal transport pathway for cerebrospinal fluid (CSF) to exchange with interstitial fluid (ISF), has pronounced activity during non-rapid eye movement (NREM) sleep and has been implicated in the pathophysiology of traumatic brain injury, Alzheimer’s disease, and mood disorders. However, direct measurement in humans is limited because current imaging methods rely on intrathecal contrast-enhanced magnetic resonance imaging (MRI), which is unsuitable for routine or naturalistic sleep studies. The absence of real-time, noninvasive monitoring methods that allow for natural sleep poses a major barrier to advancing glymphatic research in clinical settings.
Methods
To address this barrier, we developed a non-invasive functional near-infrared spectroscopy (fNIRS) forehead array in a wearable headband using non-standard wavelengths to allow for better sensitivity for water measurement. We monitored cortical blood and water dynamics during overnight sleep, quantifying oscillatory patterns of oxyhemoglobin (HbO) and water across sleep stages within the outer layers of the frontal cortex, subarachnoid space, and scalp. A component of the extracted water metrics is hypothesized to serve as a proxy for glymphatic transport without the need for contrast agents or surgical intervention.
Results
Our results demonstrate water concentrations were highest in SWS (d = 1.93, p =0.0002), while HbO concentrations also showed a modest elevation (d = 1.06, ns). Additionally, low-frequency oscillations (LFOs) of both water and HbO signals exhibited distinct dynamics of suprathreshold envelope peak (SEP) frequencies during NREM stages (N2 and N3) as compared to REM and wake, with effect size (d= 1.31, p = 0.003) for water. Interestingly, these water-derived metrics correlate with EEG slow-wave activity, linking fluid-sensitive oscillations to established electrophysiological markers of sleep depth. These findings indicate that water-sensitive oscillatory processes are selectively amplified during deep sleep and scale with EEG-defined sleep depth, consistent with a role for glymphatic-related fluid transport in human sleep.
Conclusion
We report novel cortical water shift parameters that are robustly sensitive to sleep stage transitions via a wearable, non-invasive, scalable headband, consistent with predicted glymphatic activity. Future work will cross-validate this method with MRI and other techniques.
