{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,23]],"date-time":"2026-08-23T15:19:17Z","timestamp":1787498357971,"version":"build-2736575974"},"reference-count":41,"publisher":"Wiley","issue":"4","license":[{"start":{"date-parts":[[2025,4,18]],"date-time":"2025-04-18T00:00:00Z","timestamp":1744934400000},"content-version":"vor","delay-in-days":17,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"},{"start":{"date-parts":[[2025,4,1]],"date-time":"2025-04-01T00:00:00Z","timestamp":1743465600000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["82001777"],"award-info":[{"award-number":["82001777"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["CNS Neurosci Ther"],"published-print":{"date-parts":[[2025,4]]},"abstract":"<jats:title>ABSTRACT<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Aims<\/jats:title>\n                    <jats:p>\n                      The current study aimed to investigate brain network abnormalities in glioma\u2010related epilepsy (\n                      <jats:styled-content style=\"fixed-case\">gre<\/jats:styled-content>\n                      ) patients through high\u2010density electroencephalography (\n                      <jats:styled-content style=\"fixed-case\">eeg<\/jats:styled-content>\n                      ) data analysis.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>The study included 35 patients with newly diagnosed frontal gliomas. All participants underwent 128\u2010channel resting\u2010state EEG recordings before surgery. Afterward, graph theory and microstate analyses were performed, and the resulting metrics were compared between patients with GRE and those without GRE.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      The network topology analysis demonstrated that the GRE group had a higher clustering coefficient, global efficiency, and local efficiency; a lower characteristic path length; and a higher small\u2010worldness coefficient than the non\u2010GRE group (adjusted\n                      <jats:italic>p<\/jats:italic>\n                      \u2009&lt;\u20090.05 for all). Additionally, the microstate analysis indicated that the GRE group had lower occurrence and global explained variance of microstate E and higher global explained variance of microstate D (adjusted\n                      <jats:italic>p<\/jats:italic>\n                      \u2009&lt;\u20090.05 for all). Moreover, the occurrence of microstate D was significantly negatively correlated with the maximum tumor diameter in the non\u2010GRE group (\n                      <jats:italic>r<\/jats:italic>\n                      \u2009=\u2009\u22120.542,\n                      <jats:italic>p<\/jats:italic>\n                      \u2009=\u20090.009).\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>The current study revealed specific brain network abnormalities in GRE patients based on graph theory and microstate analyses of resting\u2010state high\u2010density EEG data. These findings can enhance our comprehension of the mechanisms behind GRE and offer potential biomarkers for improving individualized management of glioma patients.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1111\/cns.70396","type":"journal-article","created":{"date-parts":[[2025,4,30]],"date-time":"2025-04-30T03:00:10Z","timestamp":1745982010000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["High\u2010Density Electroencephalography Detects Spatiotemporal Abnormalities in Brain Networks in Patients With Glioma\u2010Related Epilepsy"],"prefix":"10.1111","volume":"31","author":[{"given":"Jiajia","family":"Liu","sequence":"first","affiliation":[{"name":"Department of Neurophysiology Beijing Neurosurgical Institute, Capital Medical University  Beijing China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jiawei","family":"Shi","sequence":"additional","affiliation":[{"name":"Department of 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