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BackgroundNeuroimaging measures of behavioral and emotional dysregulation can yield biomarkers denoting developmental trajectories of psychiatric pathology in youth. We aimed to identify functional abnormalities in emotion regulation (ER) neural circuitry associated with different behavioral and emotional dysregulation trajectories using latent class growth analysis (LCGA) and neuroimaging.MethodA total of 61 youth (9–17 years) from the Longitudinal Assessment of Manic Symptoms study, and 24 healthy control youth, completed an emotional face n-back ER task during scanning. LCGA was performed on 12 biannual reports completed over 5 years of the Parent General Behavior Inventory 10-Item Mania Scale (PGBI-10M), a parental report of the child's difficulty regulating positive mood and energy.ResultsThere were two latent classes of PGBI-10M trajectories: high and decreasing (HighD; n = 22) and low and decreasing (LowD; n = 39) course of behavioral and emotional dysregulation over the 12 time points. Task performance was >89% in all youth, but more accurate in healthy controls and LowD versus HighD (p p's ConclusionsPatterns of function in lateral prefrontal cortical–amygdala circuitry in youth denote the severity of the developmental trajectory of behavioral and emotional dysregulation over time, and may be biological targets to guide differential treatment and novel treatment development for different levels of behavioral and emotional dysregulation in youth.

IntroductionHigh comorbidity among pediatric disorders characterized by behavioral and emotional dysregulation poses problems for diagnosis and treatment, and suggests that these disorders may be better conceptualized as dimensions of abnormal behaviors. Furthermore, identifying neuroimaging biomarkers related to dimensional measures of behavior may provide targets to guide individualized treatment. We aimed to use functional neuroimaging and pattern regression techniques to determine whether patterns of brain activity could accurately decode individual-level severity on a dimensional scale measuring behavioural and emotional dysregulation at two different time points.MethodsA sample of fifty-seven youth (mean age: 14.5 years; 32 males) was selected from a multi-site study of youth with parent-reported behavioral and emotional dysregulation. Participants performed a block-design reward paradigm during functional Magnetic Resonance Imaging (fMRI). Pattern regression analyses consisted of Relevance Vector Regression (RVR) and two cross-validation strategies implemented in the Pattern Recognition for Neuroimaging toolbox (PRoNTo). Medication was treated as a binary confounding variable. Decoded and actual clinical scores were compared using Pearson's correlation coefficient (r) and mean squared error (MSE) to evaluate the models. Permutation test was applied to estimate significance levels.ResultsRelevance Vector Regression identified patterns of neural activity associated with symptoms of behavioral and emotional dysregulation at the initial study screen and close to the fMRI scanning session. The correlation and the mean squared error between actual and decoded symptoms were significant at the initial study screen and close to the fMRI scanning session. However, after controlling for potential medication effects, results remained significant only for decoding symptoms at the initial study screen. Neural regions with the highest contribution to the pattern regression model included cerebellum, sensory-motor and fronto-limbic areas.ConclusionsThe combination of pattern regression models and neuroimaging can help to determine the severity of behavioral and emotional dysregulation in youth at different time points.

IMPORTANCE: Pediatric disorders characterized by behavioral and emotional dysregulation pose diagnostic and treatment challenges because of high comorbidity, suggesting that they may be better conceptualized dimensionally rather than categorically. Identifying neuroimaging measures associated with behavioral and emotional dysregulation in youth may inform understanding of underlying dimensional vs disorder-specific pathophysiologic features. OBJECTIVE: To identify, in a large cohort of behaviorally and emotionally dysregulated youth, neuroimaging measures that (1) are associated with behavioral and emotional dysregulation pathologic dimensions (behavioral and emotional dysregulation measured with the Parent General Behavior Inventory 10-Item Mania Scale [PGBI-10M], mania, depression, and anxiety) or (2) differentiate diagnostic categories (bipolar spectrum disorders, attention-deficit/hyperactivity disorder, anxiety, and disruptive behavior disorders). DESIGN, SETTING, AND PARTICIPANTS: A multisite neuroimaging study was conducted from February 1, 2011, to April 15, 2012, at 3 academic medical centers: University Hospitals Case Medical Center, Cincinnati Children's Hospital Medical Center, and University of Pittsburgh Medical Center. Participants included a referred sample of behaviorally and emotionally dysregulated youth from the Longitudinal Assessment of Manic Symptoms (LAMS) study (n = 85) and healthy youth (n = 20). MAIN OUTCOMES AND MEASURES: Region-of-interest analyses examined relationships among prefrontal-ventral striatal reward circuitry during a reward paradigm (win, loss, and control conditions), symptom dimensions, and diagnostic categories. RESULTS: Regardless of diagnosis, higher PGBI-10M scores were associated with greater left middle prefrontal cortical activity (r = 0.28) and anxiety with greater right dorsal anterior cingulate cortical (r = 0.27) activity to win. The 20 highest (t = 2.75) and 20 lowest (t = 2.42) PGBI-10M-scoring youth showed significantly greater left middle prefrontal cortical activity to win compared with 20 healthy youth. Disruptive behavior disorders were associated with lower left ventrolateral prefrontal cortex activity to win (t = 2.68) (all P

Objective Pediatric bipolar disorder involves poor social functioning, but the neural mechanisms underlying these deficits are not well understood. Previous neuroimaging studies have found deficits in emotional face processing localized to emotional brain regions. However, few studies have examined dysfunction in other regions of the face processing circuit. This study assessed hypoactivation in key face processing regions of the brain in pediatric bipolar disorder. Method Youth with a bipolar spectrum diagnosis (n = 20) were matched to a nonbipolar clinical group (n = 20), with similar demographics and comorbid diagnoses, and a healthy control group (n = 20). Youth participated in a functional magnetic resonance imaging (fMRI) scanning which employed a task-irrelevant emotion processing design in which processing of facial emotions was not germane to task performance. Results Hypoactivation, isolated to the fusiform gyrus, was found when viewing animated, emerging facial expressions of happiness, sadness, fearfulness, and especially anger in pediatric bipolar participants relative to matched clinical and healthy control groups. Conclusions The results of the study imply that differences exist in visual regions of the brain's face processing system and are not solely isolated to emotional brain regions such as the amygdala. Findings are discussed in relation to facial emotion recognition and fusiform gyrus deficits previously reported in the autism literature. Behavioral interventions targeting attention to facial stimuli might be explored as possible treatments for bipolar disorder in youth.