1. Resting-state functional connectivity between several brain regions may serve as a useful biomarker to predict future neuropsychiatric symptoms such as attention deficits, anxiety, and depression in children.
Evidence Rating Level: 2 (Good)
Neurodevelopment has become an important area of focus as it relates to mapping psychiatric and neurocognitive trajectories. There is also increasing interest in biomarkers that may allow for prediction of and early intervention for attention difficulties, anxiety, depression, and other conditions. Many cognitive processes are top-down, such that the prefrontal cortex (PFC) and higher-order regions inform other areas, notably the dorsolateral PFC (DLPFC) and anterior cingulate cortex (ACC) through their connections, resting-state networks and connectivity, rather than localization, are the critical components for determining outcomes. In this cohort study, 94 children who were enrolled in another developmental longitudinal study related to the prediction of reading disabilities were studied to assess whether specific brain connectivity patterns are associated with longitudinal changes in scores on the Child Behavior Checklist (CBCL), a parental-report assessment used to screen for emotional, behavioral, and social problems and to predict psychiatric illnesses. As part of the study, resting-state fMRI (rs-fMRI) connectivity at seven years of age was measured, and reassessed yearly for four years. After four years of follow-up, data was available for 54 of the original 94 children. Researchers found that reduced positive coupling between the medial PFC and DLPFC at 7 years of age was associated with a decrease in attention symptoms four years later (p=0.01, β=0.32). Further, reduced coupling between the subgenual ACC and DLPFC at 7 years of age was associated with increased mood symptoms (i.e. anxiety and depression) within the following four years (p=0.01, β=0.30). Interestingly, subgenual ACC-DLPFC connectivity was a stronger predictor of symptoms transitioning from subclinical to clinical levels than baseline CBCL scores. The findings of this study therefore highlight the importance of functional connectivity in not only predicting future symptoms but determining those who may be at-risk and in need of early intervention.
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