Insufficient sleep, as well as the incidence of anxiety disorders, both peak during adolescence. While both conditions present perturbations in fear-processing-related neurocircuitry, it is unknown whether these neurofunctional alterations directly link anxiety and compromised sleep in adolescents. Fourteen anxious adolescents (AAs) and 19 healthy adolescents (HAs) were compared on a measure of sleep amount and neural responses to negatively valenced faces during fMRI. Group differences in neural response to negative faces emerged in the dorsal anterior cingulate cortex (dACC) and the hippocampus. In both regions, correlation of sleep amount with BOLD activation was positive in AAs, but negative in HAs. Follow-up psychophysiological interaction (PPI) analyses indicated positive connectivity between dACC and dorsomedial prefrontal cortex, and between hippocampus and insula. This connectivity was correlated negatively with sleep amount in AAs, but positively in HAs. In conclusion, the presence of clinical anxiety modulated the effects of sleep-amount on neural reactivity to negative faces differently among this group of adolescents, which may contribute to different clinical significance and outcomes of sleep disturbances in healthy adolescents and patients with anxiety disorders.

This study examines the effect of contingency on reward function in anxiety. We define contingency as the aspect of a situation in which the outcome is determined by one's action-that is, when there is a direct link between one's action and the outcome of the action. Past findings in adolescents with anxiety or at risk for anxiety have revealed hypersensitive behavioral and neural responses to higher value rewards with correct performance. This hypersensitivity to highly valued (salient) actions suggests that the value of actions is determined not only by outcome magnitude, but also by the degree to which the outcome is contingent on correct performance. Thus, contingency and incentive value might each modulate reward responses in unique ways in anxiety. Using fMRI with a monetary reward task, striatal response to cue anticipation is compared in 18 clinically anxious and 20 healthy adolescents. This task manipulates orthogonally reward contingency and incentive value. Findings suggest that contingency modulates the neural response to incentive magnitude differently in the two groups. Specifically, during the contingent condition, right-striatal response tracks incentive value in anxious, but not healthy, adolescents. During the noncontingent condition, striatal response is bilaterally stronger to low than to high incentive in anxious adolescents, while healthy adolescents exhibit the expected opposite pattern. Both contingency and reward magnitude differentiate striatal activation in anxious versus healthy adolescents. These findings may reflect exaggerated concern about performance and/or alterations of striatal coding of reward value in anxious adolescents. Abnormalities in reward function in anxiety may have treatment implications.

Adolescence is the time of peak onset for many anxiety disorders, particularly Social Anxiety Disorder. Research using simulated social interactions consistently finds differential activation in several brain regions in anxious (vs non-anxious) youth, including amygdala, striatum and medial prefrontal cortex. However, few studies examined the anticipation of peer interactions, a key component in the etiology and maintenance of anxiety disorders. Youth completed the Chatroom Task while undergoing functional magnetic resonance imaging. Patterns of neural activation were assessed in anxious and non-anxious youth as they were cued to anticipate social feedback from peers. Anxious participants evidenced greater amygdala activation and rostral anterior cingulate (rACC)↔amygdala coupling than non-anxious participants during anticipation of feedback from peers they had previously rejected; anxious participants also evidenced less nucleus accumbens activation during anticipation of feedback from selected peers. Finally, anxiety interacted with age in rACC: in anxious participants, age was positively associated with activation to anticipated feedback from rejected peers and negatively for selected peers, whereas the opposite pattern emerged for non-anxious youth. Overall, anxious youth showed greater reactivity in anticipation of feedback from rejected peers and thus may ascribe greater salience to these potential interactions and increase the likelihood of avoidance behavior.

Objective

Relapse rates are consistently high for stimulant user disorders. In order to obtain prognostic information about individuals in treatment, machine learning models have been applied to neuroimaging and clinical data. Yet few efforts have been made to test these models in independent samples or show that they can outperform linear models. In this exploratory study, we examine whether machine learning models relative to linear models provide greater predictive accuracy and less overfitting.

Method

This longitudinal study included 63 methamphetamine-dependent (training sample) and 29 cocaine-dependent (test sample) individuals who completed an MRI scan during residential treatment. Linear and machine learning models predicting relapse at a one-year follow up that were previously developed in the methamphetamine-dependent sample using neuroimaging and clinical variables were applied to the cocaine-dependent sample. Receiver operating characteristic analysis was used to assess performance using area under the curve (AUC) as the primary outcome.

Results

Twelve individuals in the cocaine-dependent sample remained abstinent, and 17 relapsed. The linear models produced more accurate prediction in the training sample than the machine learning models but showed reduced performance in the testing sample, with AUC decreasing by 0.18. The machine learning models produced similar predictive performance in the training and test samples, with AUC changing by 0.03. In the test sample, neither the linear nor the machine learning model predicted relapse at rates above chance.

Conclusions

Although machine learning algorithms may have advantages, in this study neither model's performance was sufficient to be clinically useful. In order to improve predictive models, stronger predictor variables and larger samples are needed.

Behavioral inhibition, a temperament identifiable in infancy, is associated with heightened withdrawal from social encounters. Prior studies raise particular interest in the striatum, which responds uniquely to monetary gains in behaviorally inhibited children followed into adolescence. Although behavioral manifestations of inhibition are expressed primarily in the social domain, it remains unclear whether observed striatal alterations to monetary incentives also extend to social contexts. In the current study, imaging data were acquired from 39 participants (17 males, 22 females; ages 16-18 years) characterized since infancy on measures of behavioral inhibition. A social evaluation task was used to assess neural response to anticipation and receipt of positive and negative feedback from novel peers, classified by participants as being of high or low interest. As with monetary rewards, striatal response patterns differed during both anticipation and receipt of social reward between behaviorally inhibited and noninhibited adolescents. The current results, when combined with prior findings, suggest that early-life temperament predicts altered striatal response in both social and nonsocial contexts and provide support for continuity between temperament measured in early childhood and neural response to social signals measured in late adolescence and early adulthood.

The goal of this study was to compare brain structure between individuals with generalized anxiety disorder (GAD) and healthy controls. Previous studies have generated inconsistent findings, possibly due to small sample sizes, or clinical/analytic heterogeneity. To address these concerns, we combined data from 28 research sites worldwide through the ENIGMA-Anxiety Working Group, using a single, pre-registered mega-analysis. Structural magnetic resonance imaging data from children and adults (5-90 years) were processed using FreeSurfer. The main analysis included the regional and vertex-wise cortical thickness, cortical surface area, and subcortical volume as dependent variables, and GAD, age, age-squared, sex, and their interactions as independent variables. Nuisance variables included IQ, years of education, medication use, comorbidities, and global brain measures. The main analysis (1020 individuals with GAD and 2999 healthy controls) included random slopes per site and random intercepts per scanner. A secondary analysis (1112 individuals with GAD and 3282 healthy controls) included fixed slopes and random intercepts per scanner with the same variables. The main analysis showed no effect of GAD on brain structure, nor interactions involving GAD, age, or sex. The secondary analysis showed increased volume in the right ventral diencephalon in male individuals with GAD compared to male healthy controls, whereas female individuals with GAD did not differ from female healthy controls. This mega-analysis combining worldwide data showed that differences in brain structure related to GAD are small, possibly reflecting heterogeneity or those structural alterations are not a major component of its pathophysiology.