{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,5]],"date-time":"2026-08-05T08:57:12Z","timestamp":1785920232029,"version":"3.56.0"},"reference-count":45,"publisher":"Wiley","issue":"7","license":[{"start":{"date-parts":[[2024,4,24]],"date-time":"2024-04-24T00:00:00Z","timestamp":1713916800000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100000049","name":"National Institute on Aging","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100000049","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"publisher","award":["K01EB032989"],"award-info":[{"award-number":["K01EB032989"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Aging Cell"],"published-print":{"date-parts":[[2024,7]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>Gray matter (GM) alterations play a role in aging\u2010related disorders like Alzheimer's disease and related dementias, yet MRI studies mainly focus on macroscopic changes. Although reliable indicators of atrophy, morphological metrics like cortical thickness lack the sensitivity to detect early changes preceding visible atrophy. Our study aimed at exploring the potential of diffusion MRI in unveiling sensitive markers of cortical and subcortical age\u2010related microstructural changes and assessing their associations with cognitive and behavioral deficits. We leveraged the Human Connectome Project\u2010Aging cohort that included 707 participants (394 female; median age\u2009=\u200958, range\u2009=\u200936\u201390\u2009years) and applied the powerful mean apparent diffusion propagator model to measure microstructural parameters, along with comprehensive behavioral and cognitive test scores. Both macro\u2010 and microstructural GM characteristics were strongly associated with age, with widespread significant microstructural correlations reflective of cellular morphological changes, reduced cellular density, increased extracellular volume, and increased membrane permeability. Importantly, when correlating MRI and cognitive test scores, our findings revealed no link between macrostructural volumetric changes and neurobehavioral performance. However, we found that cellular and extracellular alterations in cortical and subcortical GM regions were associated with neurobehavioral performance. Based on these findings, it is hypothesized that increased microstructural heterogeneity and decreased neurite orientation dispersion precede macrostructural changes, and that they play an important role in subsequent cognitive decline. These alterations are suggested to be early markers of neurocognitive performance that may distinctly aid in identifying the mechanisms underlying phenotypic aging and subsequent age\u2010related functional decline.<\/jats:p>","DOI":"10.1111\/acel.14166","type":"journal-article","created":{"date-parts":[[2024,4,25]],"date-time":"2024-04-25T01:39:44Z","timestamp":1714009184000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":26,"title":["Neuronal microstructural changes in the human brain are associated with neurocognitive aging"],"prefix":"10.1111","volume":"23","author":[{"given":"Kavita","family":"Singh","sequence":"first","affiliation":[{"name":"Multiscale Imaging and Integrative Biophysics Unit National Institute on Aging, NIH  Baltimore Maryland USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0003-8135-5590","authenticated-orcid":false,"given":"Stephanie","family":"Barsoum","sequence":"additional","affiliation":[{"name":"Multiscale Imaging and Integrative Biophysics Unit National Institute on Aging, NIH  Baltimore Maryland USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kurt G.","family":"Schilling","sequence":"additional","affiliation":[{"name":"Department of Radiology and Radiological Sciences Vanderbilt University Medical Center  Nashville Tennessee USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yang","family":"An","sequence":"additional","affiliation":[{"name":"Brain Aging and Behavior Section National Institute on Aging, NIH  Baltimore Maryland USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6273-1613","authenticated-orcid":false,"given":"Luigi","family":"Ferrucci","sequence":"additional","affiliation":[{"name":"Translational Gerontology Branch National Institute on Aging, NIH  Baltimore Maryland USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9558-7056","authenticated-orcid":false,"given":"Dan","family":"Benjamini","sequence":"additional","affiliation":[{"name":"Multiscale Imaging and Integrative Biophysics Unit National Institute on Aging, NIH  Baltimore Maryland USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2024,4,24]]},"reference":[{"key":"e_1_2_10_2_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2022.119653"},{"key":"e_1_2_10_3_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2015.11.027"},{"key":"e_1_2_10_4_1","doi-asserted-by":"publisher","DOI":"10.1016\/S0006\u20103495(94)80775\u20101"},{"key":"e_1_2_10_5_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.mri.2018.12.001"},{"key":"e_1_2_10_6_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2020.117195"},{"key":"e_1_2_10_7_1","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2018.2852259"},{"key":"e_1_2_10_8_1","doi-asserted-by":"publisher","DOI":"10.1093\/brain\/awac298"},{"key":"e_1_2_10_9_1","doi-asserted-by":"publisher","DOI":"10.1093\/cercor\/bhu093"},{"key":"e_1_2_10_10_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2018.10.009"},{"key":"e_1_2_10_11_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neurobiolaging.2022.12.016"},{"key":"e_1_2_10_12_1","doi-asserted-by":"publisher","DOI":"10.1093\/acprof:oso\/9780199556984.001.0001"},{"key":"e_1_2_10_13_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroscience.2012.09.077"},{"key":"e_1_2_10_14_1","doi-asserted-by":"publisher","DOI":"10.1073\/pnas.0704320104"},{"key":"e_1_2_10_15_1","doi-asserted-by":"publisher","DOI":"10.1001\/jamanetworkopen.2023.18153"},{"key":"e_1_2_10_16_1","doi-asserted-by":"publisher","DOI":"10.1093\/cercor\/bhab180"},{"key":"e_1_2_10_17_1","doi-asserted-by":"publisher","DOI":"10.1002\/gps.2087"},{"key":"e_1_2_10_18_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2018.09.060"},{"key":"e_1_2_10_19_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2021.118530"},{"key":"e_1_2_10_20_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2019.03.041"},{"key":"e_1_2_10_21_1","unstructured":"Irfanoglu M. 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