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We introduce Critical Network Lesion\u2010Symptom Mapping (CN\u2010LSM), a neuroanatomical atlas\u2010based method that uses low\u2010dimensional regression models and out\u2010of\u2010sample prediction to identify brain regions that contribute significantly to the prediction of clinical behavioral scores. Rather than focusing on a single most\u2010predictive model, CN\u2010LSM identifies a set of plausible models analyzed as an ensemble. CN\u2010LSM offers three primary advantages over existing approaches: (1) greater robustness to analytical decisions that should be (but often are not) inconsequential to results; (2) holistic quantification of uncertainty across the entire statistical map rather than at individual voxels or regions; and (3) explicit accommodation of multiple plausible explanations, reducing false negatives while preserving stringent control over false positive rates.<\/jats:p>","DOI":"10.1002\/hbm.70644","type":"journal-article","created":{"date-parts":[[2026,9,15]],"date-time":"2026-09-15T02:34:16Z","timestamp":1789439656000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Critical\u2010Network Lesion\u2010Symptom Mapping"],"prefix":"10.1002","volume":"47","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-3521-9355","authenticated-orcid":false,"given":"Grant M.","family":"Walker","sequence":"first","affiliation":[{"name":"Department of Cognitive Sciences University of California  Irvine California USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5800-546X","authenticated-orcid":false,"given":"G. 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