Abstract
Adolescence is a period of rapid brain development when psychiatric symptoms often first emerge. Studying adolescents may therefore facilitate the identification of neural alterations early in the course of psychiatric conditions. Here, we sought to utilize new, high-quality brain parcellations and data-driven graph theory approaches to characterize associations between resting-state networks and the severity of depression, anxiety, and anhedonia symptoms—salient features across psychiatric conditions. As reward circuitry matures considerably during adolescence, we examined both Whole Brain and three task-derived reward networks. Subjects were 87 psychotropic-medication-free adolescents (age = 12–20) with diverse psychiatric conditions (n = 68) and healthy controls (n = 19). All completed diagnostic interviews, dimensional clinical assessments, and 3T resting-state fMRI (10 min/2.3 mm/TR = 1 s). Following high-quality Human Connectome Project-style preprocessing, multimodal surface matching (MSMAll) alignment, and parcellation via the Cole-Anticevic Brain-wide Network Partition, weighted graph theoretical metrics (Strength Centrality = CStr; Eigenvector Centrality = CEig; Local Efficiency = ELoc) were estimated within each network. Associations with symptom severity and clinical status were assessed non-parametrically (two-tailed pFWE < 0.05). Across subjects, depression scores correlated with ventral striatum CStr within the Reward Attainment network, while anticipatory anhedonia correlated with CStr and ELoc in the subgenual anterior cingulate, dorsal anterior cingulate, orbitofrontal cortex, caudate, and ventral striatum across multiple networks. Group differences and associations with anxiety were not detected. Using detailed functional and clinical measures, we found that adolescent depression and anhedonia involve increased influence and communication efficiency in prefrontal and limbic reward areas. Resting-state network properties thus reflect positive valence system anomalies related to discrete reward sub-systems and processing phases early in the course of illness.
Highlights
Adolescence represents a critical period of development during which many prodromal psychiatric symptoms and conditions first emerge, including depression, anxiety, and substance abuse[1]
Group differences No significant differences in graph theoretical metrics were observed between adolescents with psychiatric symptoms and healthy controls for any network in the main analysis
In addition to Whole Brain analyses, we examined graph theoretical metrics within specific Reward Anticipation, Reward Attainment, and Reward Prediction Error networks, which we defined empirically using task fMRI data collected in the same subjects
Summary
Adolescence represents a critical period of development during which many prodromal psychiatric symptoms and conditions first emerge, including depression, anxiety, and substance abuse[1]. This increased incidence has been attributed to rapid maturational changes in the brain during adolescence, which involve synaptic pruning, myelination, neurotransmission, and the formation of mature intrinsic functional circuits found in adults[2,3,4]. Our group and others have increasingly focused on specific symptoms[7,8,9], which represent narrowly defined clinical features with potentially distinct etiologies, rather than broad categorical diagnoses. We sought to utilize such a dimensional approach to examine the neural correlates of anxiety, anhedonia, and overall depression severity in adolescents with diverse psychiatric conditions
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
