Background/Objectives: The glymphatic system plays a crucial role in clearing brain metabolic waste, and its dysfunction has been correlated to various neurological disorders. The Diffusion Tensor Imaging Analysis Along the Perivascular Space (DTI-ALPS) index has been proposed as a non-invasive marker of glymphatic function by measuring diffusivity along perivascular spaces; however, its sensitivity to sleep-related changes in glymphatic activity has not yet been validated. This study aimed to evaluate the feasibility of using the DTI-ALPS index as a quantitative marker of dynamic glymphatic activity during sleep. Methods: Diffusion tensor imaging (DTI) data were obtained from 12 healthy male participants (age = 24.44 ± 2.5 years; Pittsburgh Sleep Quality Index (PSQI) < 5), once while awake and 16 times during sleep, following 24 h sleep deprivation and administration of 10 mg zolpidem. Simultaneous MR-compatible electroencephalography was used to determine whether the subject was asleep or awake. DTI preprocessing included eddy current correction and tensor fitting. The DTI-ALPS index was calculated from nine regions of interest in projection and association areas aligned to standard space. The final analysis included nine participants (age = 24.56 ± 2.74 years; PSQI < 5) who maintained a continuous sleep state for 1 h without awakening. Results: Among nine ROI pairs, three showed significant increases in the DTI-ALPS index during sleep compared to wakefulness (Friedman test; p = 0.027, 0.029, 0.034). These ROIs showed changes at 14, 19, and 25 min after sleep induction, with FDR-corrected p-values of 0.024, 0.018, and 0.018, respectively. Conclusions: This study demonstrated a statistically significant increase in the DTI-ALPS index within 30 min after sleep induction through time-series DTI analysis during wakefulness and sleep, supporting its potential as a biomarker reflecting glymphatic activity.

Background/objectives: The acute stress response affects brain metabolites closely linked to the tricarboxylic acid (TCA) cycle. This response involves time-dependent changes in hormones and neurotransmitters, which contribute to resilience and the ability to adapt to acute stress while maintaining homeostasis. This physiological mechanism of metabolic dynamics, combined with time-series analysis, has prompted the development of new methods to observe the relationship between TCA cycle-related brain metabolites. This study aimed to observe the acute stress response through metabolic interactions using time-series proton magnetic resonance spectroscopy (1H-MRS) in the left hippocampus of mice. Methods: In this study, 4-week-old male C57BL/6N mice (n = 24) were divided into control (n = 12) and acute stress groups (n = 12). Acute stress was induced through a 2 h restraint protocol. Time-series 1H-MRS data were obtained on the left hippocampus of both groups using a 9.4 T 1H-MRS scanner. Time-series MRS data were quantified using LCModel, and significant metabolic interactions were identified through Spearman correlation analysis, a one-tailed sign test, and false discovery rate correction. Results: No significant metabolic correlation coefficient was observed in the control group. However, in the acute stress group, glutathione (GSH) and N-acetyl aspartate (NAA) showed a significant positive correlation over time, with a high correlation coefficient exceeding 0.5. Conclusions: Temporal measurement of GSH and NAA, combined with correlation analysis, offers a comprehensive understanding for the metabolic dynamics during acute stress. This approach emphasizes their distinct roles and interdependence in the progression of oxidative stress, mitochondrial function, and the maintenance of physiological homeostasis.