Background: Functional connectivity has been associated with psychiatric problems, both in children and adults, but inconsistencies are present across studies. Prior research has mostly focused on small clinical samples with cross-sectional designs. Methods: We adopted a longitudinal design with repeated assessments to investigate associations between functional network connectivity (FNC) and psychiatric problems in youth (9- to 17-year-olds) from the general population. The largest single-site study of pediatric neurodevelopment was used: Generation R (N = 3,131). Psychiatric symptoms were measured with the Child Behavioral Checklist as broadband internalizing and externalizing problems, and its eight specific syndrome scales (e.g., anxious-depressed). FNC was assessed with two complementary approaches. First, static FNC (sFNC) was measured with graph theory-based metrics. Second, dynamic FNC (dFNC), where connectivity is allowed to vary over time, was summarized into 5 states that participants spent time in. Cross-lagged panel models were used to investigate the longitudinal bidirectional relationships of sFNC with internalizing and externalizing problems. Similar cross-lagged panel models were run for dFNC. Results: Small longitudinal relationships between dFNC and certain syndrome scales were observed, especially for baseline syndrome scales (i.e., rule-breaking, somatic complaints, thought problems, and attention problems) predicting connectivity changes. However, no association between any of the psychiatric problems (broadband and syndrome scales) with either measure of FNC survived correction for multiple testing. Conclusion: We found no or very modest evidence for longitudinal associations between psychiatric problems with dynamic and static FNC in this population-based sample. Differences in findings may stem from the population drawn, study design, developmental timing and sample sizes.

The authors have declared no competing interest.

The Generation R Study is supported by the Erasmus MC, Erasmus University Rotterdam, the Rotterdam Homecare Foundation, the Municipal Health Service Rotterdam area, the Stichting Trombosedienst en Artsenlaboratorium Rijnmond, the Netherlands Organization for Health Research and Development (ZonMw), and the Ministry of Health, Welfare and Sport. Neuroimaging informatics and image analysis were supported by the Sophia Foundation (S18-20 to RLM). Netherlands Organization for Scientific Research (Exacte Wetenschappen) and SURFsara (Snellius Compute System, www.surfsara.nl, grant 2021.042 to RLM) supported the Supercomputing resources. Authors are also supported by an NWO-VICI grant (NWO-ZonMW: 016.VICI.170.200 to HT) for HT, LDA, BX, and the Sophia Foundation S18-20, and Erasmus MC Fellowship to RLM, NSF grant 2112455 and NIH grant R01MH123610 to VDC, as well as the Spanish Ministry of Science and Innovation (RYC2021-034311-I) and Alicia Koplowitz Foundation to FEL. This project was also funded by the European Union Horizon 2020 Research and Innovation Programme under the Marie Skłodowska-Curie grant agreement no 707404 (MLV and FEL). The opinions expressed in this document reflect only the authors views. The European Commission is not responsible for any use that may be made of the information it contains.

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Ethical approval was obtained from the Medical Ethics Committee of Erasmus MC, University Medical Center Rotterdam. All parents provided written informed consent and children provided assent (younger than 12 years) or consent (12 years or older).

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Data for the Generation R Study is available upon request to Vincent Jaddoe (email: v.jaddoe@erasmusmc.nl).