Trauma Affects Prospective Relationships Between Reward-Related Ventral Striatal and Amygdala Activation and 1-Year Future Hypo/Mania Trajectories.

BACKGROUND: Trauma exposure is associated with a more severe, persistent course of affective and anxiety symptoms. Markers of reward neural circuitry function, specifically activation to reward prediction error (RPE), are impacted by trauma and predict the future course of affective symptoms. This study's purpose was to determine how lifetime trauma exposure influences relationships between reward neural circuitry function and the course of future affective and anxiety symptoms in a naturalistic, transdiagnostic observational context. METHODS: A total of 59 young adults aged 18-25 (48 female and 11 male participants, mean ± SD = 21.5 ± 2.0 years) experiencing psychological distress completed the study. Participants were evaluated at baseline, 6, and 12 months. At baseline, the participants reported lifetime trauma events and completed a monetary reward functional magnetic resonance imaging task. Affective and anxiety symptoms were reported at each visit, and trajectories were calculated using MPlus. Neural activation during RPE and other phases of reward processing were determined using SPM8. Trauma and reward neural activation were entered as predictors of symptom trajectories. RESULTS: Trauma exposure moderated prospective relationships between left ventral striatum (ß = -1.29, p = .02) and right amygdala (ß = 0.58, p = .04) activation to RPE and future hypo/mania severity trajectory: the interaction between greater trauma and greater left ventral striatum activation to RPE was associated with a shallower increase in hypo/mania severity, whereas the interaction between greater trauma and greater right amygdala activation to RPE was associated with increasing hypo/mania severity. CONCLUSIONS: Trauma exposure affects prospective relationships between markers of reward circuitry function and affective symptom trajectories. Evaluating trauma exposure is thus crucial in naturalistic and treatment studies aiming to identify neural predictors of future affective symptom course.

Unstable wakefulness during resting-state fMRI and its associations with network connectivity and affective psychopathology in young adults.

BACKGROUND: Drifts between wakefulness and sleep are common during resting state functional MRI (rsfMRI). Among healthy adults, within-scanner sleep can impact functional connectivity of default mode (DMN), task-positive (TPN), and thalamo-cortical networks. Because dysfunctional arousal states (i.e., sleepiness, sleep disturbance) are common in affective disorders, individuals with affective psychopathology may be more prone to unstable wakefulness during rsfMRI, hampering the estimation of clinically meaningful functional connectivity biomarkers. METHODS: A transdiagnostic sample of 150 young adults (68 psychologically distressed; 82 psychiatrically healthy) completed rsfMRI and reported whether they experienced within-scanner sleep. Symptom scales were reduced into depression/anxiety and mania proneness dimensions using principal component analysis. We evaluated associations between within-scanner sleep, clinical status, and functional connectivity of the DMN, TPN, and thalamus. RESULTS: Within-scanner sleep during rsfMRI was reported by 44% of participants (n = 66) but was unrelated to psychiatric diagnoses or mood symptom severity (p-values > 0.05). Across all participants, self-reported within-scanner sleep was associated with connectivity signatures akin to objectively-assessed sleep, including lower within-DMN connectivity, lower DMN-TPN anti-correlation, and altered thalamo-cortical connectivity (p < 0.05, corrected). Among participants reporting sustained wakefulness (n = 84), depression/anxiety severity positively associated with averaged DMN-TPN connectivity and mania proneness negatively associated with averaged thalamus-DMN connectivity (p-values < 0.05). Both relationships were attenuated and became non-significant when participants reporting within-scanner sleep were included (p-values > 0.05). LIMITATIONS: Subjective report of within-scanner sleep. CONCLUSIONS: Findings implicate within-scanner sleep as a source of variance in network connectivity; careful monitoring and correction for within-scanner sleep may enhance our ability to characterize network signatures underlying affective psychopathology.

Anhedonia Reduction and the Association Between Left Ventral Striatal Reward Response and 6-Month Improvement in Life Satisfaction Among Young Adults.

Importance: Anhedonia is a symptom of multiple psychiatric conditions in young adults that is associated with poorer mental health and psychosocial function and abnormal ventral striatum reward processing. Aberrant function of neural reward circuitry is well documented in anhedonia and other psychiatric disorders. Longitudinal studies to identify potential biomarkers associated with a reduction in anhedonia are necessary for the development of novel treatment targets. Objective: To identify neural reward-processing factors associated with improved psychiatric symptoms and psychosocial function in a naturalistic, observational context. Design, Setting, and Participants: A longitudinal cohort follow-up study was conducted from March 1, 2014, to June 5, 2018, at the University of Pittsburgh Medical Center after baseline functional magnetic resonance imaging in 52 participants between the ages of 18 and 25 years who were experiencing psychological distress. Main Outcomes and Measures: Participants were evaluated at baseline and 6 months. At baseline, participants underwent functional magnetic resonance imaging during a card-guessing monetary reward task. Participants completed measures of affective symptoms and psychosocial function at each visit. Neural activation during reward prediction error (RPE), a measure of reward learning, was determined using Statistical Parametric Mapping software. Neural reward regions with significant RPE activation were entered as regions associated with future symptoms in multiple linear regression models. Results: A total of 52 young adults (42 women and 10 men; mean [SD] age, 21.4 [2.2] years) completed the study. Greater RPE activation in the left ventral striatum was associated with a decrease in anhedonia symptoms during a 6-month period (ß = -6.152; 95% CI, -11.870 to -0.433; P = .04). The decrease in anhedonia between baseline and 6 months mediated the association between left ventral striatum activation to RPE and improvement in life satisfaction between baseline and 6 months (total [c path] association: ß = 0.245; P = .01; direct [c' path] association: ß = 0.133; P = .16; and indirect [ab path] association: 95% CI, 0.026-0.262). Results were not associated with psychotropic medication use. Conclusions and Relevance: Greater left ventral striatum responsiveness to RPE may serve as a biomarker or potential target for novel treatments to improve the severity of anhedonia, overall mental health, and psychosocial function.

Predicting anxiety from wholebrain activity patterns to emotional faces in young adults: a machine learning approach.

BACKGROUND: It is becoming increasingly clear that pathophysiological processes underlying psychiatric disorders categories are heterogeneous on many levels, including symptoms, disease course, comorbidity and biological underpinnings. This heterogeneity poses challenges for identifying biological markers associated with dimensions of symptoms and behaviour that could provide targets to guide treatment choice and novel treatment. In response, the research domain criteria (RDoC) (Insel et al., 2010) was developed to advocate a dimensional approach which omits any disease definitions, disorder thresholds, or cut-points for various levels of psychopathology to understanding the pathophysiological processes underlying psychiatry disorders. In the present study we aimed to apply pattern regression analysis to identify brain signatures during dynamic emotional face processing that are predictive of anxiety and depression symptoms in a continuum that ranges from normal to pathological levels, cutting across categorically-defined diagnoses. METHODS: The sample was composed of one-hundred and fifty-four young adults (mean age=21.6 and s.d.=2.0, 103 females) consisting of eighty-two young adults seeking treatment for psychological distress that cut across categorically-defined diagnoses and 72 matched healthy young adults. Participants performed a dynamic face task involving fearful, angry and happy faces (and geometric shapes) while undergoing functional Magnetic Resonance Imaging (fMRI). Pattern regression analyses consisted of Gaussian Process Regression (GPR) implemented in the Pattern Recognition for Neuroimaging toolbox (PRoNTo). Predicted and actual clinical scores were compared using Pearson's correlation coefficient (r) and normalized mean squared error (MSE) to evaluate the models' performance. Permutation test was applied to estimate significance levels. RESULTS: GPR identified patterns of neural activity to dynamic emotional face processing predictive of self-report anxiety in the whole sample, which covered a continuum that ranged from healthy to different levels of distress, including subthreshold to fully-syndromal psychiatric diagnoses. Results were significant using two different cross validation strategies (two-fold: r=0.28 (p-value=0.001), MSE=4.47 (p-value=0.001) and five fold r=0.28 (p-value=0.002), MSE=4.62 (p-value=0.003). The contributions of individual regions to the predictive model were very small, demonstrating that predictions were based on the overall pattern rather than on a small combination of regions. CONCLUSIONS: These findings represent early evidence that neuroimaging techniques may inform clinical assessment of young adults irrespective of diagnoses by allowing accurate and objective quantitative estimation of psychopathology.

Trauma-associated anterior cingulate connectivity during reward learning predicts affective and anxiety states in young adults.

BACKGROUND: Trauma exposure is associated with development of depression and anxiety; yet, some individuals are resilient to these trauma-associated effects. Differentiating mechanisms underlying development of negative affect and resilience following trauma is critical for developing effective interventions. One pathway through which trauma could exert its effects on negative affect is reward-learning networks. In this study, we examined relationships among lifetime trauma, reward-learning network function, and emotional states in young adults. METHODS: One hundred eleven young adults self-reported trauma and emotional states and underwent functional magnetic resonance imaging during a monetary reward task. Trauma-associated neural activation and functional connectivity were analyzed during reward prediction error (RPE). Relationships between trauma-associated neural functioning and affective and anxiety symptoms were examined. RESULTS: Number of traumatic events was associated with greater ventral anterior cingulate cortex (vACC) activation, and lower vACC connectivity with the right insula, frontopolar, inferior parietal, and temporoparietal regions, during RPE. Lower trauma-associated vACC connectivity with frontoparietal regions implicated in regulatory and decision-making processes was associated with heightened affective and anxiety symptoms; lower vACC connectivity with insular regions implicated in interoception was associated with lower affective and anxiety symptoms. CONCLUSIONS: In a young adult sample, two pathways linked the impact of trauma on reward-learning networks with higher v. lower negative affective and anxiety symptoms. The disconnection between vACC and regions implicated in decision-making and self-referential processes may reflect aberrant regulatory but appropriate self-focused mechanisms, respectively, conferring risk for v. resilience against negative affective and anxiety symptoms.