{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,5]],"date-time":"2025-11-05T21:06:44Z","timestamp":1762376804542,"version":"3.41.2"},"reference-count":45,"publisher":"Wiley","issue":"12","license":[{"start":{"date-parts":[[2020,9,17]],"date-time":"2020-09-17T00:00:00Z","timestamp":1600300800000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Brain and Behavior"],"published-print":{"date-parts":[[2020,12]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:sec><jats:title>Background<\/jats:title><jats:p>Defining reliable brain markers for the prediction of abnormal behavioral outcomes remains an urgent but extremely challenging task in neuroscience research. This is particularly important for infant studies given the most dramatic brain and behavioral growth during infancy.<\/jats:p><\/jats:sec><jats:sec><jats:title>Methods<\/jats:title><jats:p>In this study, we proposed a novel prediction scheme through abstracting individual newborn's whole\u2010brain functional connectivity pattern to three outlier measures (Triple O) and tested the hypothesis that neonates identified as \u201cbrain outliers\u201d based on Triple O were more likely to develop as IQ outliers at 4\u00a0years of age. Without need for training with behavioral data, Triple O represents a novel proof\u2010of\u2010concept approach to predict later IQ outcomes based on neonatal brain data.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>Triple O correctly identified 42.1% true IQ outliers among a mixed cohort of 175 newborns with different term, twin, and maternal disorder statuses. Triple O also reached a high level of specificity (96.2%) and overall accuracy (90.3%). Further incorporating a demographic information indicator, the enhanced Triple O+ could further differentiate between high and low 4YR IQ outliers. Validation tests against seven independent reference samples revealed highly consistent results and a minimum sample size of ~50 for robust performance.<\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusions<\/jats:title><jats:p>Considering that postnatal brain growth and various environmental factors likely also contribute to 4YR IQ, the fact that Triple O, based purely on neonatal functional connectivity data, could identify &gt;40% of 4YR IQ outliers is striking. Together with the very high level of specificity, each outlier predicted by Triple O represents a meaningful risk but future efforts are needed to explore ways to identify the rest of outliers. Overall, with no need for training, a high level of robustness, and a minimal requirement on sample size, the proposed Triple O approach demonstrates great potential to predict later outlying IQ performances using neonatal functional connectivity data.<\/jats:p><\/jats:sec>","DOI":"10.1002\/brb3.1846","type":"journal-article","created":{"date-parts":[[2020,9,18]],"date-time":"2020-09-18T02:19:23Z","timestamp":1600395563000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":10,"title":["Neonatal brain connectivity outliers identify over forty percent of IQ outliers at 4\u00a0years of age"],"prefix":"10.1002","volume":"10","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-9260-2601","authenticated-orcid":false,"given":"Wei","family":"Gao","sequence":"first","affiliation":[{"name":"Department of Biomedical Sciences and Imaging Biomedical Imaging Research Institute (BIRI) Cedars\u2010Sinai Medical Center Los Angeles CA USA"},{"name":"Department of Medicine University of California at Los Angeles Los Angeles CA USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yuanyuan","family":"Chen","sequence":"additional","affiliation":[{"name":"Department of Biomedical Sciences and Imaging Biomedical Imaging Research Institute (BIRI) Cedars\u2010Sinai Medical Center Los Angeles CA USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Emil","family":"Cornea","sequence":"additional","affiliation":[{"name":"Department of Psychiatry University of North Carolina Chapel Hill Chapel Hill NC USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Barbara D.","family":"Goldman","sequence":"additional","affiliation":[{"name":"Department of Psychology and Neuroscience FPG Child Development Institute University of North Carolina Chapel Hill Chapel Hill NC USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"John H.","family":"Gilmore","sequence":"additional","affiliation":[{"name":"Department of Psychiatry University of North Carolina Chapel Hill Chapel Hill NC USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"311","published-online":{"date-parts":[[2020,9,17]]},"reference":[{"key":"e_1_2_10_2_1","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pcbi.0030017"},{"key":"e_1_2_10_3_1","doi-asserted-by":"crossref","first-page":"40","DOI":"10.1016\/j.dcn.2014.10.004","article-title":"Frequency of spontaneous BOLD signal shifts during infancy and correlates with cognitive performance","volume":"12","author":"Alcauter S.","year":"2014","journal-title":"Developmental Cognitive Neuroscience"},{"key":"e_1_2_10_4_1","doi-asserted-by":"publisher","DOI":"10.1523\/JNEUROSCI.0796-14.2014"},{"key":"e_1_2_10_5_1","doi-asserted-by":"publisher","DOI":"10.1038\/s41562-018-0384-6"},{"key":"e_1_2_10_6_1","doi-asserted-by":"publisher","DOI":"10.1093\/scan\/nst105"},{"key":"e_1_2_10_7_1","doi-asserted-by":"publisher","DOI":"10.1093\/jpepsy\/23.3.197"},{"key":"e_1_2_10_8_1","doi-asserted-by":"publisher","DOI":"10.1093\/cercor\/bhu331"},{"key":"e_1_2_10_9_1","doi-asserted-by":"publisher","DOI":"10.1002\/mrm.1910340409"},{"key":"e_1_2_10_10_1","doi-asserted-by":"publisher","DOI":"10.1016\/0165-0173(94)00016-I"},{"key":"e_1_2_10_11_1","article-title":"The subgrouping structure of newborns with heterogenous brain\u2010behavior relationships","author":"Chen Y.","year":"2020","journal-title":"Cerebral Cortex"},{"key":"e_1_2_10_12_1","doi-asserted-by":"publisher","DOI":"10.1006\/cbmr.1996.0014"},{"key":"e_1_2_10_13_1","doi-asserted-by":"publisher","DOI":"10.1073\/pnas.1007921107"},{"key":"e_1_2_10_14_1","doi-asserted-by":"publisher","DOI":"10.1016\/S0887-8994(03)00211-X"},{"key":"e_1_2_10_15_1","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0079200"},{"key":"e_1_2_10_16_1","doi-asserted-by":"publisher","DOI":"10.1093\/cercor\/bhq071"},{"key":"e_1_2_10_17_1","doi-asserted-by":"publisher","DOI":"10.1177\/1073858416635986"},{"key":"e_1_2_10_18_1","doi-asserted-by":"publisher","DOI":"10.1177\/1073858416635986"},{"key":"e_1_2_10_19_1","doi-asserted-by":"publisher","DOI":"10.1073\/pnas.0811221106"},{"key":"e_1_2_10_20_1","doi-asserted-by":"publisher","DOI":"10.1038\/nrn.2018.1"},{"key":"e_1_2_10_21_1","doi-asserted-by":"publisher","DOI":"10.3389\/fnhum.2019.00044"},{"key":"e_1_2_10_22_1","article-title":"Functional connectivity disruption in neonates with prenatal marijuana exposure","author":"Grewen K. 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