Innovative research has uncovered a groundbreaking connection between functional network connectivity (FNC) in adolescent brains and cognitive development, as well as psychiatric risks. The study, published in Nature Mental Health, involved the analysis of FNC from brain scans of over 9,000 children, leading to the discovery of consistent patterns in the FNC that researchers believe serve as individual fingerprints.
Principal investigator Zening Fu explained that the study demonstrates that FNC variability can predict a wide range of behaviors, including cognition, mental health, and even sleep conditions. The research team found that the variability of individualized FNC across scans conveys psychological and physiological information underlying distinct behavioral phenotypes in children. With advanced machine learning techniques, the team was able to predict a number of conditions and outcomes, including cognitive performance, mental health problems, sleep conditions, and even screen usage based on FNC stability.
Moreover, the study unveiled the potential of FNC as a valuable neuroimaging feature to draw inferences on early cognitive and psychiatric behaviors in children. This has significant implications for early intervention in children who are most at risk for cognitive or psychiatric problems.
A second study, published in Biological Psychiatry and conducted by researchers at the TReNDS Center, developed a brain-wide risk score (BRS) using FNC to assess psychiatric risks. The BRS revealed a distinct, repeatable gradient of FNC patterns for each psychiatric disorder in over 8,000 unaffected teenagers, ranging from low to high risk. This new image-based tool has the potential to serve as a biomarker that facilitates early screening and monitoring interventions.
Both studies were conducted using a multimodal database known as the Adolescent Brain Cognitive Development (ABCD) Study, which contains a wide range of measurements of mental health, cognition, and other health-related factors. The Translational Research in Neuroimaging and Data Science Center (TReNDS) at Georgia State University played a crucial role in these groundbreaking discoveries by developing and applying advanced analytic approaches and neuroinformatic tools.
This innovative research provides new insights into the potential of FNC to not only predict cognitive developments and psychiatric risks in adolescent brains but also to serve as a tool for early intervention and monitoring. The implications for identifying at-risk individuals and implementing proactive interventions are substantial, marking a significant advance in the field of neurodevelopment and mental health research.