Data-driven parcellation and graph theory analyses to study adolescent mood and anxiety symptoms

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 = C_Str; Eigenvector Centrality = C_Eig; Local Efficiency = E_Loc) were estimated within each network. Associations with symptom severity and clinical status were assessed non-parametrically (two-tailed p_FWE < 0.05). Across subjects, depression scores correlated with ventral striatum C_Str within the Reward Attainment network, while anticipatory anhedonia correlated with C_Str and E_Loc 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.

Fig. 1. Reward network masks.

Nodes from the Whole Brain network corresponding to Reward Anticipation (green), Reward Attainment (blue), and Reward Prediction Error (red) networks derived from the Reward Flanker Task (RFT). Nodes included in multiple networks are indicated by additive color mixing, as shown at the top.

Fig. 2. Depression severity correlation results.

Across all adolescents, overall depression severity positively correlated with: a Whole Brain C_Str in the left medullary brainstem and left cerebellum; b Whole Brain E_Loc in the left lateral temporal cortex and left cerebellum; c Reward Attainment network C_Str in the left lateral temporal cortex, right ventral striatum, and right pallidum; and d Reward Prediction Error network C_Str in the left dorsolateral prefrontal cortex (dlPFC). Maps show effect size (Pearson’s r) adjusted for age and sex. Significant nodes (two-tailed p_FWE < 0.05) are indicated by white outlines and labels; non-significant nodes are displayed at 50% saturation.

Fig. 3. Anhedonia severity correlation results.

Across all adolescents, anticipatory anhedonia positively correlated with: a Whole Brain E_Loc in the left lateral and superior parietal cortices, bilateral lateral temporal cortex, right temporal pole, right lateral occipital cortex, left subgenual anterior cingulate cortex (sgACC), and right parahippocampus; b Reward Anticipation network E_Loc in the bilateral caudate; c Reward Attainment network C_Str in the left lateral temporal cortex; d Reward Attainment network E_Loc in the left sgACC, right orbitofrontal cortex (OFC), and right dorsal anterior cingulate cortex (dACC); e Reward Prediction Error network C_Str in the left superior parietal cortex and bilateral caudate; and f Reward Prediction Error network E_Loc in the right dorsolateral prefrontal cortex (dlPFC), right dACC, bilateral caudate, right ventral striatum, and right thalamus. Total anhedonia positively correlated with: g Whole Brain E_Loc in the left lateral temporal cortex, right parahippocampus, and bilateral hippocampus; and h Reward Prediction Error network E_Loc in the right caudate. Maps show effect size (Pearson’s r) adjusted for age and sex. Significant (two-tailed p_FWE < 0.05) nodes are indicated by white outlines and labels; non-significant nodes are displayed at 50% saturation.