{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,9]],"date-time":"2026-05-09T07:09:52Z","timestamp":1778310592832,"version":"3.51.4"},"reference-count":33,"publisher":"SAGE Publications","issue":"2","license":[{"start":{"date-parts":[[2026,4,1]],"date-time":"2026-04-01T00:00:00Z","timestamp":1775001600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"},{"start":{"date-parts":[[2026,4,1]],"date-time":"2026-04-01T00:00:00Z","timestamp":1775001600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/journals.sagepub.com\/page\/policies\/text-and-data-mining-license"}],"content-domain":{"domain":["journals.sagepub.com"],"crossmark-restriction":true},"short-container-title":["Multiple Sclerosis Journal \u2013 Experimental, Translational and Clinical"],"published-print":{"date-parts":[[2026,4]]},"abstract":"<jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Cognitive dysfunction involving working memory is common in multiple sclerosis (MS) but is often under-detected in clinical assessments. Noninvasive digital biomarkers like oculomotor metrics may enhance the detection of neurofunctional changes.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Objective<\/jats:title>\n                    <jats:p>\n                      Determine whether oculomotor metrics during a visuospatial\n                      <jats:italic toggle=\"yes\">N-<\/jats:italic>\n                      back task reflect cognitive dysfunction and correspond with clinical measures in patients with MS.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>\n                      In a cross-sectional study, 38 patients completed an\n                      <jats:italic toggle=\"yes\">N-<\/jats:italic>\n                      back working memory task with eye tracking to record gaze duration and task accuracy. Clinical measures included Symbol Digit Modalities Test (SDMT), retinal nerve fiber layer (RNFL), macular volume, Expanded Disability Status Scale (EDSS), and Nine-Hole Peg Test (9HPT). Linear regression models examined relationships between task accuracy, gaze duration, and clinical measures.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>Gaze duration and task accuracy were inversely correlated (r\u2009=\u2009\u22120.57, p\u2009&lt;\u20090.001). Shorter gaze duration and higher task accuracy, indicators of better cognitive processing efficiency, were associated with better SDMT scores, greater RNFL thickness and macular volume, and better EDSS and 9HPT completion times.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>Oculomotor metrics recorded during a working memory task are associated with cognitive, retinal, and functional measures in pwMS, supporting their potential as noninvasive biomarkers to complement standard clinical assessments in detecting cognitive dysfunction.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1177\/20552173261446213","type":"journal-article","created":{"date-parts":[[2026,5,6]],"date-time":"2026-05-06T13:07:56Z","timestamp":1778072876000},"update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":0,"title":["Eye movement analysis during working memory tasks correlates with cognitive, clinical, and anatomical metrics in multiple sclerosis"],"prefix":"10.1177","volume":"12","author":[{"given":"Cecilie Fjeldstad","family":"Pardo","sequence":"first","affiliation":[{"name":"Multiple Sclerosis Center of Excellence"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Gerardo","family":"Fernandez","sequence":"additional","affiliation":[{"name":"Medical Division"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0008-4329-7103","authenticated-orcid":false,"given":"Bujana","family":"Allushi","sequence":"additional","affiliation":[{"name":"Multiple Sclerosis Center of Excellence"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Adithya A","family":"Bhaktaram","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3131-6246","authenticated-orcid":false,"given":"Lorna","family":"Galleguillos","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Danilo","family":"Verge","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2207-3708","authenticated-orcid":false,"given":"Gabriel","family":"Pardo","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"179","published-online":{"date-parts":[[2026,5,6]]},"reference":[{"key":"e_1_3_3_2_2","doi-asserted-by":"publisher","DOI":"10.1177\/1352458520970841"},{"key":"e_1_3_3_3_2","doi-asserted-by":"publisher","DOI":"10.1146\/annurev.neuro.30.051606.094313"},{"key":"e_1_3_3_4_2","doi-asserted-by":"publisher","DOI":"10.1101\/cshperspect.a028936"},{"key":"e_1_3_3_5_2","doi-asserted-by":"publisher","DOI":"10.1056\/NEJMcp053247"},{"key":"e_1_3_3_6_2","doi-asserted-by":"publisher","DOI":"10.1212\/WNL.33.11.1444"},{"key":"e_1_3_3_7_2","unstructured":"Smith A. 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