{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,23]],"date-time":"2026-10-23T19:11:01Z","timestamp":1792782661516,"version":"4.5.0"},"reference-count":23,"publisher":"Springer Science and Business Media LLC","issue":"7","license":[{"start":{"date-parts":[[2026,8,29]],"date-time":"2026-08-29T00:00:00Z","timestamp":1787961600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2026,8,29]],"date-time":"2026-08-29T00:00:00Z","timestamp":1787961600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"funder":[{"name":"University of Southern California","id":[{"id":"https:\/\/ror.org\/03taz7m60","id-type":"ROR","asserted-by":"crossref"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Brain Struct Funct"],"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>\n                    Dietary patterns covary with cognitive performance during adolescence, but the structural brain features associated with this covariance remain incompletely characterized. To identify structural brain correlates of cognition-aligned dietary patterns in adolescents while addressing adiposity, ethnicity adjustment, family relatedness, and multiple testing. We analyzed 3,308 adolescents from ABCD Release 5.1. Ten food-group measures were summarized by five dietary principal components (PCs). We constructed sample-derived, cognition-aligned dietary scores (PolyIQ) and used repeated five-fold family-level cross-fitting so that each participant\u2019s score was calculated using cognition-derived weights estimated without that participant or members of the same family. The original PCs provided an outcome-independent benchmark. Primary models adjusted for age, sex, pubertal stage, socioeconomic status, income-to-needs ratio, sleep, and age- and sex-standardized BMI; ethnicity was excluded from primary models and added in sensitivity analyses. Brain\u2013cognition models and family-cluster bootstrap indirect-effect models examined fractional anisotropy (FA), cortical thickness, surface area, and regional volume. All pre-specified indirect-effect models, including nonsignificant results, were retained. Cross-fitted dietary scores were associated with crystallized cognition (\u03b2\u2009=\u20090.099, SE\u2009=\u20090.018,\n                    <jats:italic>P<\/jats:italic>\n                    \u2009&lt;\u20090.001) and fluid cognition (\u03b2\u2009=\u20090.064, SE\u2009=\u20090.015,\n                    <jats:italic>P<\/jats:italic>\n                    \u2009&lt;\u20090.001); the five original dietary PCs were jointly associated with both domains. Brain\u2013cognition associations in the bilateral fornix and hippocampal cingulum remained after BMI adjustment. In the all-ROI analysis, indirect associations through right and left fornix FA survived false-discovery-rate correction for both crystallized cognition (right: 0.0067, 95% CI [0.0016, 0.0134]; left: 0.0063, [0.0013, 0.0126]) and fluid cognition (right: 0.0061, [0.0019, 0.0127]; left: 0.0052, [0.0011, 0.0106]). No gray-matter indirect effect survived correction across all tested regions. A sample-derived dietary pattern aligned with cognition covaried with FA in bilateral fornix pathways. The findings were robust to adiposity adjustment and were similar when ethnicity was added, but the cross-sectional design supports only a decomposition of shared variance, not a causal or temporally ordered mechanism.\n                  <\/jats:p>","DOI":"10.1007\/s00429-026-03190-w","type":"journal-article","created":{"date-parts":[[2026,8,29]],"date-time":"2026-08-29T03:23:49Z","timestamp":1787973829000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Brain structural pathways linking dietary patterns and cognitive performance in adolescents"],"prefix":"10.1007","volume":"231","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-5847-1428","authenticated-orcid":false,"given":"Isabelle","family":"Brocas","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Liam","family":"Kirwin","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Matthew","family":"Kuloszewski","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2026,8,29]]},"reference":[{"issue":"1","key":"3190_CR1","doi-asserted-by":"publisher","first-page":"21","DOI":"10.1016\/j.jand.2015.08.010","volume":"116","author":"EC Banfield","year":"2016","unstructured":"Banfield EC, Liu Y, Davis JS, Chang S, Alexis C, Frazier-Wood (2016) Poor adherence to us dietary guidelines for children and adolescents in the national health and nutrition examination survey population. 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After using this tool, the corresponding author reviewed and edited the content as needed and takes full responsibility for the content of the publication.","order":2,"name":"Ethics","label":"Declaration of generative AI and AI-assisted technologies in the writing process","group":{"name":"EthicsHeading","label":"Declarations"}}],"article-number":"129"}}