{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"institution":[{"name":"bioRxiv"}],"indexed":{"date-parts":[[2026,10,23]],"date-time":"2026-10-23T21:18:39Z","timestamp":1792790319534,"version":"4.5.0"},"posted":{"date-parts":[[2026,10,1]]},"group-title":"Neuroscience","reference-count":93,"publisher":"openRxiv","license":[{"start":{"date-parts":[[2026,10,1]],"date-time":"2026-10-01T00:00:00Z","timestamp":1790812800000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by-nd\/4.0\/"}],"funder":[{"name":"Eunice Kennedy Shriver National Institute of Child Health and Human Development","award":["P50 HD105352"],"award-info":[{"award-number":["P50 HD105352"]}],"id":[{"id":"https:\/\/ror.org\/04byxyr05","id-type":"ROR","asserted-by":"crossref"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"accepted":{"date-parts":[[2026,10,1]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                <jats:sec>\n                  <jats:title>Background<\/jats:title>\n                  <jats:p>Autism spectrum disorder (ASD) is neurobiologically heterogeneous, and group comparisons may mask effects confined to subgroups. We tested whether distinct biotypes exist within ASD using unsupervised clustering of multimodal MRI.<\/jats:p>\n                <\/jats:sec>\n                <jats:sec>\n                  <jats:title>Methods<\/jats:title>\n                  <jats:p>We analyzed 149 participants with ASD and 129 typically developing (TD) controls from the Autism Brain Imaging Data Exchange II (6 sites; age 5 to 64 years). Site-harmonized features comprised free water (FW), tissue anisotropy and diffusivity, diffusion tensor image analysis along the perivascular space (DTI-ALPS), cerebrospinal fluid (CSF) volumes and exploratory resting-state regional homogeneity. ASD participants were clustered with k-means using global (7 features) and regional (17 features) sets, with robustness tested by permutation and two further algorithms. TD participants were projected post hoc to test specificity. A composite imaging score was related to Social Responsiveness Scale (SRS) subscales, symptom severity and IQ using partial correlations with false discovery rate correction.<\/jats:p>\n                <\/jats:sec>\n                <jats:sec>\n                  <jats:title>Results<\/jats:title>\n                  <jats:p>Clustering identified an elevated free-water (EFW) biotype comprising approximately 10% of ASD participants, defined by markedly increased FW (d = +4.91 versus remaining ASD participants), reduced tissue anisotropy, reduced DTI-ALPS and enlarged ventricles. It was recovered across feature sets and algorithms (permutation p &lt; .0001) and departed from TD norms, unlike the remaining ASD participants. The composite score correlated with social-perceptual and communicative SRS subscales, most strongly social awareness (r = +0.253, q = .026), but not with symptom severity or IQ. FW related to social motivation in children and adolescents (r = +0.287, q = .037) but not adults.<\/jats:p>\n                <\/jats:sec>\n                <jats:sec>\n                  <jats:title>Limitations<\/jats:title>\n                  <jats:p>Each person was scanned once, so we cannot tell whether these brain differences cause social difficulties or how they change with age. The subgroup was small, clinical data were incomplete, the sample was mostly male with a wide age range, and the findings await confirmation in an independent group. Free water can reflect inflammation, swelling or tissue loss, so its biological meaning remains uncertain.<\/jats:p>\n                <\/jats:sec>\n                <jats:sec>\n                  <jats:title>Conclusions<\/jats:title>\n                  <jats:p>We identify an ASD subgroup defined by extracellular fluid excess and altered white matter that is associated with greater social difficulties. If replicated, this signature may help stratify individuals with ASD in mechanistic studies and clinical trials.<\/jats:p>\n                <\/jats:sec>","DOI":"10.64898\/2026.09.25.754196","type":"posted-content","created":{"date-parts":[[2026,10,1]],"date-time":"2026-10-01T18:55:15Z","timestamp":1790880915000},"source":"Crossref","is-referenced-by-count":0,"title":["Multimodal MRI Clustering Reveals an Elevated Free-Water Biotype in Autism with Increased Social Symptoms"],"prefix":"10.64898","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-8069-1766","authenticated-orcid":false,"given":"Faye","family":"McKenna","sequence":"first","affiliation":[{"name":"Department of Radiology and Gruss Magnetic Resonance Research Center, Montefiore Health System and Albert Einstein College of Medicine, Bronx, NY"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kimberly J.","family":"Hemmerling","sequence":"additional","affiliation":[{"name":"Department of Radiology and Gruss Magnetic Resonance Research Center, Montefiore Health System and Albert Einstein College of Medicine, Bronx, NY"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3588-3838","authenticated-orcid":false,"given":"Shounak","family":"Nandi","sequence":"additional","affiliation":[{"name":"Department of Radiology and Gruss Magnetic Resonance Research Center, Montefiore Health System and Albert Einstein College of Medicine, Bronx, NY"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sophie","family":"Molholm","sequence":"additional","affiliation":[{"name":"Departments of Pediatrics and Neuroscience, Albert Einstein College of Medicine"},{"name":"The Dominick P. Purpura Department of Neuroscience"},{"name":"Rose F. Kennedy IDDRC, Albert Einstein College of Medicine, Bronx, NY"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5264-0144","authenticated-orcid":false,"given":"David C.","family":"Zhu","sequence":"additional","affiliation":[{"name":"Department of Radiology and Gruss Magnetic Resonance Research Center, Montefiore Health System and Albert Einstein College of Medicine, Bronx, NY"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"54368","reference":[{"key":"2026100607551538000_2026.09.25.754196v1.1","doi-asserted-by":"publisher","DOI":"10.1038\/s41380-018-0321-0"},{"key":"2026100607551538000_2026.09.25.754196v1.2","doi-asserted-by":"publisher","DOI":"10.1016\/j.biopsych.2020.03.022"},{"key":"2026100607551538000_2026.09.25.754196v1.3","doi-asserted-by":"publisher","DOI":"10.1176\/APPI.AJP.21100992"},{"key":"2026100607551538000_2026.09.25.754196v1.4","doi-asserted-by":"publisher","DOI":"10.1016\/j.tics.2019.03.009"},{"key":"2026100607551538000_2026.09.25.754196v1.5","doi-asserted-by":"publisher","DOI":"10.1038\/nm.4246"},{"key":"2026100607551538000_2026.09.25.754196v1.6","doi-asserted-by":"publisher","DOI":"10.1093\/schbul\/sbt179"},{"key":"2026100607551538000_2026.09.25.754196v1.7","doi-asserted-by":"crossref","first-page":"1103","DOI":"10.1001\/jamapsychiatry.2018.2451","article-title":"Using Brain-Based Phenotyping to Improve Discovery in Psychiatry","volume":"75","year":"2018","journal-title":"JAMA Psychiatry"},{"key":"2026100607551538000_2026.09.25.754196v1.8","doi-asserted-by":"publisher","DOI":"10.1038\/s41467-021-22265-2"},{"key":"2026100607551538000_2026.09.25.754196v1.9","doi-asserted-by":"publisher","DOI":"10.1038\/s41467-018-05892-0"},{"key":"2026100607551538000_2026.09.25.754196v1.10","doi-asserted-by":"publisher","DOI":"10.1212\/WNL.0000000000009058"},{"key":"2026100607551538000_2026.09.25.754196v1.11","doi-asserted-by":"crossref","first-page":"e56257","DOI":"10.7554\/eLife.56257","article-title":"Functional connectivity subtypes associate robustly with ASD diagnosis","volume":"11","year":"2022","journal-title":"Elife"},{"key":"2026100607551538000_2026.09.25.754196v1.12","doi-asserted-by":"publisher","DOI":"10.1002\/hbm.24400"},{"key":"2026100607551538000_2026.09.25.754196v1.13","doi-asserted-by":"publisher","DOI":"10.1038\/s41593-026-02287-z"},{"key":"2026100607551538000_2026.09.25.754196v1.14","doi-asserted-by":"publisher","DOI":"10.1038\/s41593-023-01259-x"},{"key":"2026100607551538000_2026.09.25.754196v1.15","doi-asserted-by":"publisher","DOI":"10.1093\/brain\/awx146"},{"key":"2026100607551538000_2026.09.25.754196v1.16","doi-asserted-by":"crossref","unstructured":"Vijayakumari AA , Sakaie KE , Teixeira-Dos-Santos D , Fernandez HH , Walter BL . Data-driven neurobiological subtyping of Parkinson\u2019s disease using diffusion MRI-derived isotropic diffusion. Neuroradiology. 2026;68:e-pub ahead of print.","DOI":"10.21203\/rs.3.rs-7880492\/v1"},{"key":"2026100607551538000_2026.09.25.754196v1.17","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2017.12.096"},{"key":"2026100607551538000_2026.09.25.754196v1.18","first-page":"e2221","article-title":"Cerebral white matter free water: A sensitive biomarker of cognition and function","volume":"92","year":"2019","journal-title":"Neurology"},{"key":"2026100607551538000_2026.09.25.754196v1.19","doi-asserted-by":"crossref","unstructured":"Cai Y , Zhang Y , Leng S , Ma Y , Jiang Q , Wen Q , et al. The relationship between inflammation, impaired glymphatic system, and neurodegenerative disorders: A vicious cycle. Neurobiol Dis. 2024;192:106426.","DOI":"10.1016\/j.nbd.2024.106426"},{"key":"2026100607551538000_2026.09.25.754196v1.20","doi-asserted-by":"publisher","DOI":"10.1002\/mrm.22055"},{"key":"2026100607551538000_2026.09.25.754196v1.21","doi-asserted-by":"publisher","DOI":"10.1126\/sciadv.abq2923"},{"key":"2026100607551538000_2026.09.25.754196v1.22","doi-asserted-by":"publisher","DOI":"10.1007\/s00429-019-02017-1"},{"key":"2026100607551538000_2026.09.25.754196v1.23","doi-asserted-by":"crossref","first-page":"283","DOI":"10.1016\/j.bbi.2019.09.010","article-title":"Increased extracellular free-water in adult male rats following in utero exposure to maternal immune activation","volume":"83","year":"2020","journal-title":"Brain Behav Immun"},{"key":"2026100607551538000_2026.09.25.754196v1.24","doi-asserted-by":"crossref","unstructured":"Walsh MJM , Ofori E , Pagni BA , Chen K , Sullivan G , Braden BB . Preliminary findings of accelerated visual memory decline and baseline brain correlates in middle-age and older adults with autism: The case for hippocampal free-water. Front Aging Neurosci. 2022;14:1029166.","DOI":"10.3389\/fnagi.2022.1029166"},{"key":"2026100607551538000_2026.09.25.754196v1.25","doi-asserted-by":"crossref","unstructured":"Zhang Y , Ofori E , Chen K , Harker SA , Velez M , Gallegos S , et al. Association of glymphatic dysfunction, free water, white matter integrity and long-term memory performance in aging autistic adults. Mol Autism. 2026;17:10.","DOI":"10.1186\/s13229-026-00705-4"},{"key":"2026100607551538000_2026.09.25.754196v1.26","doi-asserted-by":"crossref","unstructured":"Wilkes BJ , Archer DB , Farmer AL , Bass C , Korah H , Vaillancourt DE , et al. Cortico-basal ganglia white matter microstructure is linked to restricted repetitive behavior in autism spectrum disorder. Mol Autism. 2024;15:6.","DOI":"10.1186\/s13229-023-00581-2"},{"key":"2026100607551538000_2026.09.25.754196v1.27","doi-asserted-by":"crossref","unstructured":"Surgent O , Riaz A , Ausderau KK , Adluru N , Kirk GR , Guerrero-Gonzalez J , et al. Brainstem white matter microstructure is associated with hyporesponsiveness and overall sensory features in autistic children. Mol Autism. 2022;13:48.","DOI":"10.1186\/s13229-022-00524-3"},{"key":"2026100607551538000_2026.09.25.754196v1.28","doi-asserted-by":"publisher","DOI":"10.1016\/j.biopsych.2017.02.1095"},{"key":"2026100607551538000_2026.09.25.754196v1.29","doi-asserted-by":"crossref","unstructured":"Peterson M , Prigge MBD , Bigler ED , Zielinski B , King JB , Lange N , et al. Evidence for normal extra-axial cerebrospinal fluid volume in autistic males from middle childhood to adulthood. Neuroimage. 2021;240:118387.","DOI":"10.1016\/j.neuroimage.2021.118387"},{"key":"2026100607551538000_2026.09.25.754196v1.30","doi-asserted-by":"crossref","unstructured":"Shen MD . Cerebrospinal fluid and the early brain development of autism. J Neurodev Disord. 2018;10:39.","DOI":"10.1186\/s11689-018-9256-7"},{"key":"2026100607551538000_2026.09.25.754196v1.31","doi-asserted-by":"publisher","DOI":"10.1126\/scitranslmed.3003748"},{"key":"2026100607551538000_2026.09.25.754196v1.32","doi-asserted-by":"publisher","DOI":"10.1152\/physrev.00031.2020"},{"key":"2026100607551538000_2026.09.25.754196v1.33","first-page":"431","article-title":"Features of the cerebral vascular pattern that predict vulnerability to perfusion or oxygenation deficiency: An anatomic study","volume":"11","year":"1990","journal-title":"AJNR Am J Neuroradiol"},{"key":"2026100607551538000_2026.09.25.754196v1.34","doi-asserted-by":"crossref","unstructured":"Taoka T , Ito R , Nakamichi R , Nakane T , Naganawa S . Diffusion tensor image analysis along the perivascular space (DTI-ALPS): redefining its interpretation and role. Jpn J Radiol. 2026:e-pub ahead of print.","DOI":"10.1007\/s11604-026-02035-0"},{"key":"2026100607551538000_2026.09.25.754196v1.35","doi-asserted-by":"publisher","DOI":"10.1007\/s11604-017-0617-z"},{"key":"2026100607551538000_2026.09.25.754196v1.36","first-page":"3653","article-title":"Assessment of glymphatic function and white matter integrity in children with autism using multi-parametric MRI and machine learning","volume":"35","year":"2025","journal-title":"Eur Radiol"},{"key":"2026100607551538000_2026.09.25.754196v1.37","doi-asserted-by":"crossref","unstructured":"Zhao S , Zhang M , Luo T , Li L , Jiang Y , Situ M , et al. Glymphatic system dysfunction in children with autism spectrum disorder as evidenced by the diffusion tensor imaging along perivascular spaces index. Front Psychiatry. 2025;16:1701816.","DOI":"10.3389\/fpsyt.2025.1701816"},{"key":"2026100607551538000_2026.09.25.754196v1.38","doi-asserted-by":"publisher","DOI":"10.1097\/MD.0000000000032061"},{"key":"2026100607551538000_2026.09.25.754196v1.39","doi-asserted-by":"crossref","unstructured":"Costa T , Manuello J , Premi E , Mattioli I , Lasagna L , Lahoz CB , et al. Evaluating the robustness of DTI-ALPS in clinical context: a meta-analytic parallel on Alzheimer\u2019s and Parkinson\u2019s diseases. Sci Rep. 2024;14:26381.","DOI":"10.1038\/s41598-024-78132-9"},{"key":"2026100607551538000_2026.09.25.754196v1.40","doi-asserted-by":"crossref","unstructured":"Zhang F , Li Q , Wang M , Zhang Y , Chen J , Shang X . A systematic review and meta-analysis on glymphatic flow dysfunction in depression:Evidence from the DTI-ALPS index. J Affect Disord. 2026;410:121960.","DOI":"10.1016\/j.jad.2026.121960"},{"key":"2026100607551538000_2026.09.25.754196v1.41","doi-asserted-by":"publisher","DOI":"10.1038\/mp.2013.78"},{"key":"2026100607551538000_2026.09.25.754196v1.42","doi-asserted-by":"publisher","DOI":"10.1016\/J.NEUROIMAGE.2017.11.024"},{"key":"2026100607551538000_2026.09.25.754196v1.43","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2017.08.047"},{"key":"2026100607551538000_2026.09.25.754196v1.44","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2003.12.030"},{"key":"2026100607551538000_2026.09.25.754196v1.45","doi-asserted-by":"crossref","first-page":"kkad026","DOI":"10.1093\/psyrad\/kkad026","article-title":"Data-driven multimodal fusion: Approaches and applications in psychiatric research","volume":"3","year":"2023","journal-title":"Psychoradiology"},{"key":"2026100607551538000_2026.09.25.754196v1.46","first-page":"230","article-title":"Multimodal Fusion of Brain Imaging Data: A Key to Finding the Missing Link(s) in Complex Mental Illness","volume":"1","year":"2016","journal-title":"Biol Psychiatry Cogn Neurosci Neuroimaging"},{"key":"2026100607551538000_2026.09.25.754196v1.47","doi-asserted-by":"publisher","DOI":"10.1176\/appi.ajp.2015.14091200"},{"key":"2026100607551538000_2026.09.25.754196v1.48","doi-asserted-by":"publisher","DOI":"10.1148\/rg.2017160061"},{"key":"2026100607551538000_2026.09.25.754196v1.49","doi-asserted-by":"crossref","unstructured":"Zhang R , Zhou Y , Yan S , Zhong G , Liu C , Jiaerken Y , et al. A brain region-based deep medullary veins visual score on susceptibility weighted imaging. Front Aging Neurosci. 2017;9:269.","DOI":"10.3389\/fnagi.2017.00269"},{"key":"2026100607551538000_2026.09.25.754196v1.50","doi-asserted-by":"crossref","unstructured":"Di Martino A , O\u2019Connor D , Chen B , Alaerts K , Anderson JS , Assaf M , et al. Enhancing studies of the connectome in autism using the autism brain imaging data exchange II. Sci Data. 2017;4:170010.","DOI":"10.1038\/sdata.2017.10"},{"key":"2026100607551538000_2026.09.25.754196v1.51","doi-asserted-by":"publisher","DOI":"10.1023\/A:1005592401947"},{"key":"2026100607551538000_2026.09.25.754196v1.52","doi-asserted-by":"publisher","DOI":"10.1007\/BF02172145"},{"key":"2026100607551538000_2026.09.25.754196v1.53","unstructured":"Constantino JN , Gruber CP . Social Responsiveness Scale, Second Edition (SRS-2). Los Angeles, CA: Western Psychological Services; 2012."},{"key":"2026100607551538000_2026.09.25.754196v1.54","doi-asserted-by":"crossref","unstructured":"Kaufman AS , Kaufman NL . Kaufman Brief Intelligence Test, Second Edition. Encyclopedia of Special Education, Bloomington, MN: NCS Pearson; 2004.","DOI":"10.1037\/t27706-000"},{"key":"2026100607551538000_2026.09.25.754196v1.55","doi-asserted-by":"crossref","unstructured":"Wechsler D . Manual for the Wechsler abbreviated intelligence scale (WASI). San Antonio, TX: Psychological Corporation; 1999.","DOI":"10.1037\/t15170-000"},{"key":"2026100607551538000_2026.09.25.754196v1.56","doi-asserted-by":"crossref","first-page":"278","DOI":"10.1177\/0734282906288389","article-title":"Test Review: Wechsler Intelligence Scale for Children, Fourth Edition (WISC-IV)","volume":"24","year":"2006","journal-title":"J Psychoeduc Assess"},{"key":"2026100607551538000_2026.09.25.754196v1.57","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2004.07.051"},{"key":"2026100607551538000_2026.09.25.754196v1.58","doi-asserted-by":"publisher","DOI":"10.1109\/42.906424"},{"key":"2026100607551538000_2026.09.25.754196v1.59","doi-asserted-by":"crossref","unstructured":"Tournier J-D , Smith R , Raffelt D , Tabbara R , Dhollander T , Pietsch M , et al. MRtrix3: a fast, flexible and open software framework for medical image processing and visualisation. Neuroimage. 2019;202:116137.","DOI":"10.1016\/j.neuroimage.2019.116137"},{"key":"2026100607551538000_2026.09.25.754196v1.60","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2011.09.015"},{"key":"2026100607551538000_2026.09.25.754196v1.61","doi-asserted-by":"publisher","DOI":"10.1016\/j.mri.2019.05.008"},{"key":"2026100607551538000_2026.09.25.754196v1.62","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2010.07.033"},{"key":"2026100607551538000_2026.09.25.754196v1.63","doi-asserted-by":"crossref","first-page":"442","DOI":"10.1002\/ana.26710","article-title":"Regional Glymphatic Abnormality in Behavioral Variant Frontotemporal Dementia","volume":"94","year":"2023","journal-title":"Ann Neurol"},{"key":"2026100607551538000_2026.09.25.754196v1.64","doi-asserted-by":"publisher","DOI":"10.1002\/mrm.28599"},{"key":"2026100607551538000_2026.09.25.754196v1.65","doi-asserted-by":"publisher","DOI":"10.1006\/cbmr.1996.0014"},{"key":"2026100607551538000_2026.09.25.754196v1.66","doi-asserted-by":"publisher","DOI":"10.1002\/mrm.1910350312"},{"key":"2026100607551538000_2026.09.25.754196v1.67","doi-asserted-by":"publisher","DOI":"10.1111\/j.2517-6161.1995.tb02031.x"},{"key":"2026100607551538000_2026.09.25.754196v1.68","doi-asserted-by":"publisher","DOI":"10.1038\/s41386-022-01272-x"},{"key":"2026100607551538000_2026.09.25.754196v1.69","doi-asserted-by":"publisher","DOI":"10.1016\/j.biopsych.2020.01.016"},{"key":"2026100607551538000_2026.09.25.754196v1.70","doi-asserted-by":"crossref","unstructured":"Kim BH , Shin D , Kang SH , Jang H , Yun J , Park YH , et al. Mapping Alzheimer\u2019s disease pathology using free water through integrated analysis of plasma biomarkers, microstructural DTI metrics, and macrostructural MRI measures. Sci Rep. 2025;15:30702.","DOI":"10.1038\/s41598-025-14200-y"},{"key":"2026100607551538000_2026.09.25.754196v1.71","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0173982"},{"key":"2026100607551538000_2026.09.25.754196v1.72","doi-asserted-by":"crossref","unstructured":"Bergamino M , McElvogue MM , Stokes AM . Distinguishing Early from Late Mild Cognitive Impairment Using Magnetic Resonance Free-Water Diffusion Tensor Imaging. NeuroSci. 2025;6:8.","DOI":"10.3390\/neurosci6010008"},{"key":"2026100607551538000_2026.09.25.754196v1.73","doi-asserted-by":"crossref","first-page":"774","DOI":"10.1002\/mds.29366","article-title":"Monitoring Substantia Nigra Degeneration Using Free Water Imaging across Prodromal and Clinical Parkinson\u2019s Disease","volume":"38","year":"2023","journal-title":"Mov Disord"},{"key":"2026100607551538000_2026.09.25.754196v1.74","doi-asserted-by":"publisher","DOI":"10.3174\/ajnr.A5545"},{"key":"2026100607551538000_2026.09.25.754196v1.75","doi-asserted-by":"crossref","first-page":"174","DOI":"10.1176\/appi.ajp.2020.19090934","article-title":"Pervasively thinner neocortex as a transdiagnostic feature of general psychopathology","volume":"178","year":"2021","journal-title":"Am J Psychiatry"},{"key":"2026100607551538000_2026.09.25.754196v1.76","doi-asserted-by":"crossref","first-page":"kkaf031","DOI":"10.1093\/psyrad\/kkaf031","article-title":"Assessing glymphatic-associated fluid dynamics in psychiatric disorders: evidence from neuroimaging - a review","volume":"5","year":"2025","journal-title":"Psychoradiology"},{"key":"2026100607551538000_2026.09.25.754196v1.77","doi-asserted-by":"crossref","first-page":"1396","DOI":"10.1093\/schbul\/sbae060","article-title":"Evaluation of the Glymphatic System in Schizophrenia Spectrum Disorder Using Proton Magnetic Resonance Spectroscopy Measurement of Brain Macromolecule and Diffusion Tensor Image Analysis Along the Perivascular Space Index","volume":"50","year":"2024","journal-title":"Schizophr Bull"},{"key":"2026100607551538000_2026.09.25.754196v1.78","doi-asserted-by":"crossref","first-page":"e70475","DOI":"10.1111\/cns.70475","article-title":"Free Water-Corrected Fractional Anisotropy in Normal-Appearing White Matter as a Potential Neuroimaging Biomarker for Attention and Executive Function Impairment in Cerebral Small Vessel Disease","volume":"31","year":"2025","journal-title":"CNS Neurosci Ther"},{"key":"2026100607551538000_2026.09.25.754196v1.79","doi-asserted-by":"publisher","DOI":"10.1002\/ana.20315"},{"key":"2026100607551538000_2026.09.25.754196v1.80","doi-asserted-by":"publisher","DOI":"10.1016\/j.biopsych.2010.05.024"},{"key":"2026100607551538000_2026.09.25.754196v1.81","doi-asserted-by":"crossref","unstructured":"Andica C , Kamagata K , Kirino E , Uchida W , Irie R , Murata S , et al. Neurite orientation dispersion and density imaging reveals white matter microstructural alterations in adults with autism. Mol Autism. 2021;12:48.","DOI":"10.1186\/s13229-021-00456-4"},{"key":"2026100607551538000_2026.09.25.754196v1.82","doi-asserted-by":"crossref","unstructured":"Aoki Y , Abe O , Nippashi Y , Yamasue H . Comparison of white matter integrity between autism spectrum disorder subjects and typically developing individuals: A meta-analysis of diffusion tensor imaging tractography studies. Mol Autism. 2013;4:25.","DOI":"10.1186\/2040-2392-4-25"},{"key":"2026100607551538000_2026.09.25.754196v1.83","doi-asserted-by":"publisher","DOI":"10.1089\/neu.2023.0222"},{"key":"2026100607551538000_2026.09.25.754196v1.84","first-page":"e099476","article-title":"Periventricular white matter hyperintensities co-localize with deep intramedullary venules, sparing compact fiber tracts and can increase or decrease over time in Alzheimer\u2019s disease","volume":"41","year":"2025","journal-title":"Alzheimers Dement"},{"key":"2026100607551538000_2026.09.25.754196v1.85","doi-asserted-by":"crossref","unstructured":"Moody DM , Brown WR , Challa VR , Anderson RL . Periventricular venous collagenosis: Association with leukoaraiosis. Radiology. 1995;194.","DOI":"10.1148\/radiology.194.2.7824728"},{"key":"2026100607551538000_2026.09.25.754196v1.86","doi-asserted-by":"publisher","DOI":"10.1093\/jnen\/nlx009"},{"key":"2026100607551538000_2026.09.25.754196v1.87","doi-asserted-by":"crossref","unstructured":"Chen D , Sun J , Li Q , Bai W , Mao J . An Important Finding of White Matter Injury in Late Preterm Infant: Deep Medullary Vein Involvement. Front Pediatr. 2020;8:597567.","DOI":"10.3389\/fped.2020.597567"},{"key":"2026100607551538000_2026.09.25.754196v1.88","doi-asserted-by":"crossref","first-page":"e2348341","DOI":"10.1001\/jamanetworkopen.2023.48341","article-title":"Enlarged Perivascular Spaces in Infancy and Autism Diagnosis, Cerebrospinal Fluid Volume, and Later Sleep Problems","volume":"6","year":"2023","journal-title":". JAMA Netw Open"},{"key":"2026100607551538000_2026.09.25.754196v1.89","doi-asserted-by":"publisher","DOI":"10.1007\/s00330-023-10220-2"},{"key":"2026100607551538000_2026.09.25.754196v1.90","doi-asserted-by":"publisher","DOI":"10.1016\/j.tics.2012.02.007"},{"key":"2026100607551538000_2026.09.25.754196v1.91","doi-asserted-by":"publisher","DOI":"10.1111\/cdev.13649"},{"key":"2026100607551538000_2026.09.25.754196v1.92","doi-asserted-by":"publisher","DOI":"10.1126\/science.1220845"},{"key":"2026100607551538000_2026.09.25.754196v1.93","doi-asserted-by":"publisher","DOI":"10.1093\/brain\/awy191"}],"container-title":[],"original-title":[],"link":[{"URL":"https:\/\/syndication.highwire.org\/content\/doi\/10.64898\/2026.09.25.754196","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,10,6]],"date-time":"2026-10-06T14:55:33Z","timestamp":1791298533000},"score":1,"resource":{"primary":{"URL":"http:\/\/biorxiv.org\/lookup\/doi\/10.64898\/2026.09.25.754196"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,10,1]]},"references-count":93,"URL":"https:\/\/doi.org\/10.64898\/2026.09.25.754196","relation":{},"subject":[],"published":{"date-parts":[[2026,10,1]]},"subtype":"preprint"}}