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We sought to identify correlates of decreased CMRGlc in the spectral properties of fMRI signals imaged in the task\u2010free state. Lifespan resting\u2010state fMRI data acquired in 455 healthy adults (ages 18\u201387\u00a0years) and cerebral metabolic data acquired in a separate cohort of 94 healthy adults (ages 25\u201345\u00a0years, 65\u201385\u00a0years) were analyzed. The spectral properties of the fMRI data were characterized in terms of the relative predominance of slow versus fast activity using the spectral slope (SS) measure. We found that the relative proportion of fast activity increases with advancing age (SS flattening) across most cortical regions. The regional distribution of spectral slope was topographically correlated with CMRGlc in young adults. Notably, whereas most older adults maintain a youthful pattern of SS topography, a distinct subset of older adults significantly diverged from the youthful pattern. This subset of older adults also diverged from the youthful pattern of CMRGlc metabolism. This divergent pattern was associated with T2\u2010weighted signal changes in frontal lobe white matter, an independent marker of small vessel disease. These findings suggest that BOLD signal spectral slope flattening may represent a biomarker of age\u2010associated neurometabolic pathology.<\/jats:p>","DOI":"10.1002\/advs.202417644","type":"journal-article","created":{"date-parts":[[2025,7,17]],"date-time":"2025-07-17T04:40:10Z","timestamp":1752727210000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Aging and the Spectral Properties of Brain Hemodynamics"],"prefix":"10.1002","volume":"12","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-2413-9421","authenticated-orcid":false,"given":"Ki Yun","family":"Park","sequence":"first","affiliation":[{"name":"Medical Scientist Training Program Washington University School of Medicine  St. Louis MO 63110 USA"},{"name":"Department of Neurological Surgery Washington University School of Medicine  St. Louis MO 63110 USA"},{"name":"Center for Innovation in Neuroscience and Technology Washington University School of 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