{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,22]],"date-time":"2026-07-22T23:11:29Z","timestamp":1784761889198,"version":"3.55.0"},"reference-count":78,"publisher":"Wiley","issue":"5","license":[{"start":{"date-parts":[[2025,9,3]],"date-time":"2025-09-03T00:00:00Z","timestamp":1756857600000},"content-version":"vor","delay-in-days":2,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"},{"start":{"date-parts":[[2025,9,1]],"date-time":"2025-09-01T00:00:00Z","timestamp":1756684800000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Journal of Neuroimaging"],"published-print":{"date-parts":[[2025,9]]},"abstract":"<jats:title>ABSTRACT<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Background and Purpose<\/jats:title>\n                    <jats:p>Cognitive impairment is common and disabling in multiple sclerosis (MS), yet poorly explained by lesion burden. This study aimed to determine whether the indirect impact of lesions, quantified through disconnectomes, explains multidomain cognitive deficits more effectively than lesion load, and to identify specific white matter tracts underlying these deficits.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>Thirty adults with MS completed the Brief International Cognitive Assessment for MS, covering processing speed (Symbol Digit Modalities Test; SDMT), verbal memory (California Verbal Learning Test\u2010II; CVLT\u2010II), and visuospatial memory (Brief Visuospatial Memory Test\u2013Revised; BVMT\u2010R). Lesions were segmented using 3 Tesla fluid\u2010attenuated inversion recovery images and used to estimate tract\u2010specific disconnections and generate voxel\u2010wise disconnectome maps. Tract\u2010specific and voxel\u2010wise analyses were used to identify disconnection patterns associated with cognitive performance.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      Cognition was impaired across all domains (all\n                      <jats:italic>p<\/jats:italic>\n                      &lt; 0.001). Disconnectome volume was a significant independent determinant of cognitive performance (\u03b2 = \u20130.41,\n                      <jats:italic>p<\/jats:italic>\n                      = 0.004), whereas lesion volume was not. Tract\u2010specific analyses revealed distinct disconnection patterns: slower SDMT was associated with left cingulum posterior (\u03b2 = \u22120.310, 95% confidence interval [CI] [\u22120.599, \u22120.021]); poorer CVLT\u2010II with left arcuate fasciculus (\u03b2 = \u22120.232, 95% CI [\u22120.435, \u22120.030]); and lower BVMT\u2010R with right cingulum posterior (\u03b2 = \u22120.218, 95% CI [\u22120.383, \u22120.054]). Voxel\u2010wise analyses identified where the strongest associations between disconnectomes and cognitive performance were located.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>Lesion\u2010driven disconnection is a more robust determinant of cognitive impairment in MS than lesion burden alone, and disconnectome mapping may help understand the indirect network\u2010level mechanisms underlying cognitive deficits in MS.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1111\/jon.70081","type":"journal-article","created":{"date-parts":[[2025,9,3]],"date-time":"2025-09-03T07:04:18Z","timestamp":1756883058000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Lesion\u2010Based Disconnectome Explains Cognitive Outcomes in Multiple Sclerosis"],"prefix":"10.1111","volume":"35","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-4216-333X","authenticated-orcid":false,"given":"Jonadab","family":"dos Santos Silva","sequence":"first","affiliation":[{"name":"Postgraduate Program in Neurology Universidade Federal Fluminense  Niter\u00f3i Brazil"},{"name":"Department of Neurology Yale School of Medicine  New Haven Connecticut USA"},{"name":"Department of Neurology Icahn School of Medicine at Mount Sinai  New York New York USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Claudia C. 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