{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,19]],"date-time":"2026-08-19T10:26:47Z","timestamp":1787135207743,"version":"build-2736575974"},"reference-count":87,"publisher":"SAGE Publications","issue":"2-3","license":[{"start":{"date-parts":[[2026,2,18]],"date-time":"2026-02-18T00:00:00Z","timestamp":1771372800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/journals.sagepub.com\/page\/policies\/text-and-data-mining-license"}],"funder":[{"name":"iTAKL: Imaging Telemetry And Kinematic modeLing in youth football","award":["R01NS082453"],"award-info":[{"award-number":["R01NS082453"]}]}],"content-domain":{"domain":["journals.sagepub.com"],"crossmark-restriction":true},"short-container-title":["Brain Connectivity"],"published-print":{"date-parts":[[2026,4,1]]},"abstract":"<jats:sec>\n                    <jats:title>Introduction:<\/jats:title>\n                    <jats:p>The widespread participation of children in contact sports raises public interest and concern regarding neurological conditions later in life that may be related to repetitive head impacts (RHIs). Advanced neuroimaging techniques are advantageous for understanding functional brain changes. Particularly, magnetoencephalography (MEG) has shown promise as a clinical tool for concussion diagnosis and prognosis as well as understanding of RHI.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methodology:<\/jats:title>\n                    <jats:p>\n                      In this study, we utilized preseason and postseason eyes-open resting state MEG data to evaluate changes in functional connectivity correlated with RHI in 72 football players (\u03bc\n                      <jats:sub>age<\/jats:sub>\n                      = 12.2 years). In addition, MEG scans were acquired at baseline and follow-up for 17 control participants (\u03bc\n                      <jats:sub>age<\/jats:sub>\n                      = 11.5 years). Standard preprocessing techniques were followed, and coherence values were computed for regions of interest defined via the Desikan\u2013Killiany atlas. The network-based statistic toolbox was used, and standard analysis of covariance (ANCOVAs) were implemented with corrections for multiple comparisons.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results:<\/jats:title>\n                    <jats:p>Postseason comparisons between football players and controls showed global hypoconnectivity in the delta frequency band for football players and hyperconnectivity in the theta and beta frequency bands in left cortical regions. No significant differences were found in preseason versus postseason comparisons within the football and control groups or between the two groups during preseason.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Discussion:<\/jats:title>\n                    <jats:p>The combination of hypo- and hyperconnectivity may reflect compensatory mechanisms activated during postseason that deviate from typical cognitive development in this critical developmental age group. Further research is needed to explore the long-term effects of RHI on brain connectivity and cognitive development.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1177\/21580014261425220","type":"journal-article","created":{"date-parts":[[2026,2,19]],"date-time":"2026-02-19T06:33:33Z","timestamp":1771482813000},"page":"118-127","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":0,"title":["Understanding the Neural Connectivity Changes of Repetitive Head Impacts in Youth Football Players: A Cross-Sectional MEG Analysis"],"prefix":"10.1177","volume":"16","author":[{"given":"Natalie M.","family":"Bell","sequence":"first","affiliation":[{"name":"Advanced Neuroscience Imaging Research Laboratory, University of Texas Southwestern Medical Center, Dallas, TX, USA."},{"name":"Department of Radiology, University of Texas Southwestern Medical Center, Dallas, TX, 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Medicine, Winston-Salem, NC, USA."},{"name":"Clinical and Translational Science Institute, Wake Forest School of Medicine, Winston-Salem, NC, USA."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Amy L.","family":"Proskovec","sequence":"additional","affiliation":[{"name":"Advanced Neuroscience Imaging Research Laboratory, University of Texas Southwestern Medical Center, Dallas, TX, USA."},{"name":"Department of Radiology, University of Texas Southwestern Medical Center, Dallas, TX, USA."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Joel D.","family":"Stitzel","sequence":"additional","affiliation":[{"name":"Department of Biomedical Engineering, Wake Forest School of Medicine, Winston-Salem, NC, USA."},{"name":"Virginia Tech\u2014Wake Forest School of Biomedical Engineering, Wake Forest School of Medicine, Winston-Salem, NC, USA."},{"name":"Clinical and Translational Science Institute, Wake Forest School of Medicine, Winston-Salem, NC, 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