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We analyzed 223 typically developing children aged 0\u20133 years with multimodal MRI and paired fecal shotgun metagenomics. Microbiome-wide association analyses identified associations with cortical morphology, white-matter microstructure, and functional connectivity. Ridge-regularized canonical correlation analysis identified two principal covariance patterns: a structural\u2013metabolic mode and a functional\u2013taxonomic mode. Sparse canonical partial least squares recovered the principal CCA score and phenotype patterns within the same sample. Longitudinal canonical-score slopes were not significantly correlated; in autoregressive cross-lag models, however, neuroimaging CCA1 scores predicted microbiome CCA1 scores 1\u20136 months later. These results indicate cross-domain covariance and temporal ordering within the measured windows but do not establish causality.<\/jats:p>","DOI":"10.64898\/2026.09.23.753825","type":"posted-content","created":{"date-parts":[[2026,9,25]],"date-time":"2026-09-25T00:21:08Z","timestamp":1790295668000},"source":"Crossref","is-referenced-by-count":0,"title":["Microbes on the Mind: Multi-modal Neuroimaging Reveals Gut-Brain Axes in Infants"],"prefix":"10.64898","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-6142-3865","authenticated-orcid":false,"given":"Tengfei","family":"Li","sequence":"first","affiliation":[{"name":"Department of Radiology, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States"},{"name":"Biomedical Research Imaging Center, University of North Carolina at Chapel Hill, North Carolina, Chapel Hill, United 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