Quantification of brain networks in healthy and diseased adolescents using neuroimaging processing techniques.

In the last decades, neuroimaging, and particularly functional magnetic resonance, have lead to a high number of findings on brain organization that have helped the scientific community to better understand brain function. Despite these advances, the foundations of neural activity and connectivity are not yet understood, and little is known about its role in the etiology of psychiatric disorders. A vast amount of literature on neuroimaging demonstrates the presence of abnormal and dysfunctional brain patterns of activity, revealed by a wide number of different analytical approaches. However, the establishment of consistent relations between abnormal connectivity patterns and symptoms or diagnoses is still not confirmed. For this reason, the present project studied these relations in young individuals suffering from First Episode Psychosis (FEP) and healthy control participants by implementing a model-dependent atlas-based approach using the publicly available Seven Network Atlas. The statistical analysis of preprocessed images revealed various tendencies consistent with previous results from literature as well as new findings. Youth in psychosis presented hyperconnectivity in most resting-state networks when compared to controls, being significantly enhanced in Fronto-Parietal network (FPN) and Default Mode network (DMN). Also, within patients hyperconnectivity was negatively related to general cognitive performance and positively linked to clinical symptom severity. We estimate that the results of this work will eventually contribute to a better understanding of the early stages of psychosis in children and adolescents, critical for optimizing current interventions and treatments.