Faculty Bibliography

INTRODUCTION: High 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. METHODS: A 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. RESULTS: Relevance 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. CONCLUSIONS: The combination of pattern regression models and neuroimaging can help to determine the severity of behavioral and emotional dysregulation in youth at different time points.

Schizophrenic patients have a high rate of smoking and cognitive deficits which may be related to a decreased number or responsiveness of nicotinic receptors in their brains. Varenicline is a partial nicotinic agonist which is effective as an antismoking drug in cigarette smokers, although concerns have been raised about potential psychiatric side-effects. We conducted a double-blind placebo controlled study in 87 schizophrenic smokers to evaluate the effects of varenicline (2 mg/day) on measures of smoking, cognition, psychiatric symptoms, and side-effects in schizophrenic patients who were cigarette smokers. Varenicline significantly decreased cotinine levels (P<0.001), and other objective and subjective measures of smoking (P < .01), and responses on a smoking urges scale (P = .02), more than placebo. Varenicline did not improve scores on a cognitive battery designed to test the effect of drugs on cognitive performance in schizophrenia (the MATRICS battery), either in overall MATRICS battery Composite or individual Domain scores, more than placebo. There were no significant differences between varenicline vs. placebo effects on total symptom scores on psychiatric rating scales, PANSS, SANS, or Calgary Depression scales, and there were no significant drug effects in any of these scales sub-scores when we used Benjamin-Hochberg corrected significance levels (alpha = .05). Varenicline patients did not show greater side-effects than placebo treated patients at any time point when controlled for baseline side-effect scores. Our study supports the use of varenicline as a safe drug for smoking reduction in schizophrenia but not as a cognitive enhancer. TRIAL REGISTRATION: ClinicalTrials.gov 00802919.

BACKGROUND: Autism spectrum disorder (ASD) encompasses a complex manifestation of symptoms that include deficits in social interaction and repetitive or stereotyped interests and behaviors. In keeping with the increasing recognition of the dimensional characteristics of ASD symptoms and the categorical nature of a diagnosis, we sought to delineate the neural mechanisms of ASD symptoms based on the functional connectivity of four known neural networks (i.e., default mode network, dorsal attention network, salience network, and executive control network). METHODS: We leveraged an open data resource (Autism Brain Imaging Data Exchange) providing resting-state functional magnetic resonance imaging data sets from 90 boys with ASD and 95 typically developing boys. This data set also included the Social Responsiveness Scale as a dimensional measure of ASD traits. Seed-based functional connectivity was paired with linear regression to identify functional connectivity abnormalities associated with categorical effects of ASD diagnosis, dimensional effects of ASD-like behaviors, and their interaction. RESULTS: Our results revealed the existence of dimensional mechanisms of ASD uniquely affecting each network based on the presence of connectivity-behavioral relationships; these were independent of diagnostic category. However, we also found evidence of categorical differences (i.e., diagnostic group differences) in connectivity strength for each network as well as categorical differences in connectivity-behavioral relationships (i.e., diagnosis-by-behavior interactions), supporting the coexistence of categorical mechanisms of ASD. CONCLUSIONS: Our findings support a hybrid model for ASD characterization that includes a combination of categorical and dimensional brain mechanisms and provide a novel understanding of the neural underpinnings of ASD.

OBJECTIVE: To examine rates and predictors of receiving a psychosocial service before initiating antipsychotic treatment among young people in the Medicaid program. METHOD: A retrospective new-user cohort study of 8 state Medicaid programs focused on children and adolescents 0 to 20 years, initiating antipsychotic treatment (N = 24,372). The proportion receiving a psychosocial service in the 3 months before initiating antipsychotic treatment was calculated and stratified by socio-demographic and diagnostic characteristics arranged in 9 hierarchical groups, as follows: developmental, psychotic/bipolar, disruptive, attention-deficit/hyperactivity, obsessive-compulsive, stress, major depressive, anxiety, and other disorders. RESULTS: Less than one-half of youth received a psychosocial service before initiating antipsychotic treatment (48.8%). Compared to younger adolescents (12-17 years) initiating antipsychotic treatment (51.5%), corresponding younger children (0-5 years; 39.2%) and older adolescents (18-20 years; 40.1%), but not older children (6-11 years; 51.5%), were significantly less likely to have received a psychosocial service. In relation to youth diagnosed with psychotic or bipolar disorder (52.7%), those diagnosed with attention-deficit/hyperactivity (43.3%), developmental (41.4%), depressive (46.5%), or anxiety (35.6%) disorder were significantly less likely to have received a psychosocial service during the 3 months before antipsychotic initiation. By contrast, youth diagnosed with stress disorders (61.2%) were significantly more likely than those diagnosed with psychotic or bipolar disorders (52.7%) to have received a psychosocial service before starting an antipsychotic. CONCLUSION: A majority of Medicaid-insured youth initiating antipsychotic treatment have not received a psychosocial service in the preceding 3 months. This service pattern highlights a critical gap in access to psychosocial services.

BACKGROUND: Ineffective decision making is a major source of everyday functional impairment and reduced quality of life for young people with mental disorders. However, very little is known about what distinguishes decision making by individuals with different disorders or the neuropsychological processes or brain systems underlying these. This is the focus of the current review. SCOPE AND METHODOLOGY: We first propose a neuroeconomic model of the decision-making process with separate stages for the prechoice evaluation of expected utility of future options; choice execution and postchoice management; the appraisal of outcome against expectation; and the updating of value estimates to guide future decisions. According to the proposed model, decision making is mediated by neuropsychological processes operating within three domains: (a) self-referential processes involved in autobiographical reflection on past, and prospection about future, experiences; (b) executive functions, such as working memory, inhibition, and planning, that regulate the implementation of decisions; and (c) processes involved in value estimation and outcome appraisal and learning. These processes are underpinned by the interplay of multiple brain networks, especially medial and lateralized cortical components of the default mode network, dorsal corticostriatal circuits underpinning higher order cognitive and behavioral control, and ventral frontostriatal circuits, connecting to brain regions implicated in emotion processing, that control valuation and learning processes. FINDINGS AND CONCLUSION: Based on clinical insights and considering each of the decision-making stages in turn, we outline disorder-specific hypotheses about impaired decision making in four childhood disorders: attention-deficit/hyperactivity disorder (ADHD), conduct disorder (CD), depression, and anxiety. We hypothesize that decision making in ADHD is deficient (i.e. inefficient, insufficiently reflective, and inconsistent) and impulsive (biased toward immediate over delayed alternatives). In CD, it is reckless and insensitive to negative consequences. In depression, it is disengaged, perseverative, and pessimistic, while in anxiety, it is hesitant, risk-averse, and self-deprecating. A survey of current empirical indications related to these disorder-specific hypotheses highlights the limited and fragmentary nature of the evidence base and illustrates the need for a major research initiative in decision making in childhood disorders. The final section highlights a number of important additional general themes that need to be considered in future research.

Although disrupted function of frontal and limbic areas of cerebral cortex are closely associated with major depressive disorder (MDD) and schizophrenia (SZ), cellular pathology has also been found in other brain areas, including primary sensory areas. Auditory cortex is of particular interest, given the prominence of auditory hallucinations in SZ, and sensory deficits in MDD. We used stereological sampling methods in auditory cortex to look for cellular differences between MDD, SZ and non-psychiatric subjects. Additionally, as all of our MDD subjects died of suicide, we evaluated the association of suicide with our measurements by selecting a SZ sample that was divided between suicide and non-suicide subjects. Measurements were done in primary auditory cortex (area A1) and auditory association cortex (area Tpt), two areas with distinct roles in sensory processing and obvious differences in neuron density and size. In MDD, densities of GABAergic interneurons immunolabeled for calretinin (CR) and calbindin (CB) were 23-29% lower than non-psychiatric controls in both areas. Parvalbumin (PV) interneurons (counted only in area Tpt) showed a nominally smaller (16%) reduction that was not statistically significant. Total neuron and glia densities measured in Nissl stained sections did not show corresponding reductions. Analysis of suicide in the SZ sample indicated that reduced CR cell density was associated with suicide, whereas the densities of CB and other cells were not. Our results are consistent with previous studies in MDD that found altered GABA-associated markers throughout the cerebral cortex including primary sensory areas.

OBJECTIVE: Empirical study of public behavioral health systems' use of data and their investment in evidence-based treatments (EBTs) is limited. This study describes trends in state-level EBT investment and research supports from 2001 to 2012. METHODS: Data were from National Association for State Mental Health Program Directors Research Institute (NRI) surveys, which were completed by representatives of state mental health authorities (SMHAs). Multilevel models examined change over time related to state adoption of EBTs, numbers of clients served, and penetration rates for six behavioral health EBTs for adults and children: supported housing, supported employment, assertive community treatment, therapeutic foster care, multisystemic therapy, and functional family therapy. State supports related to research, evaluation, and information management were also examined. RESULTS: Increasing percentages of states reported funding an external research center, promoting the adoption of EBTs through provider contracts, and providing financial incentives for EBTs. Decreasing percentages of states reported promoting EBT adoption through stakeholder mobilization, monitoring fidelity, and specific budget requests. There was greater reported use of adult-focused EBTs (65%-80%) compared with youth-focused EBTs (25%-50%). Overall penetration rates of EBTs were low (1%-3%) and EBT adoption by states showed flat or declining trends. SMHAs' investment in data systems and use of research showed little change. CONCLUSIONS: SMHA investment in EBTs, implementation infrastructure, and use of research has declined. More systematic measurement and examination of these metrics may provide a useful approach for setting priorities, evaluating success of health reform efforts, and making future investments.

Dropouts from system-wide evidence-based practice trainings are high; yet there are few studies on what predicts dropouts. This study examined multilevel predictors of clinician dropout from a statewide training on the Managing and Adapting Practice program. Extra-organizational structural variables, intra-organizational variables and clinician variables were examined. Using multivariable logistic regression analysis, state administrative data and prospectively collected clinician participation data were used to predict dropout. Two characteristics were predictive: younger clinicians and those practicing in upstate-rural areas compared to downstate-urban areas were less likely to drop out from training. Implications for research and policy are described.

Malformations of cortical development are found at higher rates in autism spectrum disorder (ASD) than in healthy controls on postmortem neuropathological evaluation but are more variably observed on visual review of in-vivo MRI brain scans. This may be due to the visually elusive nature of many malformations on MRI. Here, we utilize a quantitative approach to determine whether a volumetric measure of heterotopic gray matter in the white matter is elevated in people with ASD, relative to typically developing controls (TDC). Data from a primary sample of 48 children/young adults with ASD and 48 age-, and gender-matched TDCs, selected from the Autism Brain Imaging Data Exchange (ABIDE) open-access database, were analyzed to compare groups on (1) blinded review of high-resolution T1-weighted research sequences; and (2) quantitative measurement of white matter hypointensity (WMH) volume calculated from the same T1-weighted scans. Groupwise WMH volume comparisons were repeated in an independent, multi-site sample (80 ASD/80 TDC), also selected from ABIDE. Visual review resulted in equivalent proportions of imaging abnormalities in the ASD and TDC group. However, quantitative analysis revealed elevated periventricular and deep subcortical WMH volumes in ASD. This finding was replicated in the independent, multi-site sample. Periventricular WMH volume was not associated with age but was associated with greater restricted repetitive behaviors on both parent-reported and clinician-rated assessment inventories. Thus, findings demonstrate that periventricular WMH volume is elevated in ASD and associated with a higher degree of repetitive behaviors and restricted interests. Although the etiology of focal WMH clusters is unknown, the absence of age effects suggests that they may reflect a static anomaly.

Robust incorporation of new principal cells into pre-existing circuitry in the adult mammalian brain is unique to the hippocampal dentate gyrus (DG). We asked if adult-born granule cells (GCs) might act to regulate processing within the DG by modulating the substantially more abundant mature GCs. Optogenetic stimulation of a cohort of young adult-born GCs (0 to 7 weeks post-mitosis) revealed that these cells activate local GABAergic interneurons to evoke strong inhibitory input to mature GCs. Natural manipulation of neurogenesis by aging - to decrease it - and housing in an enriched environment - to increase it - strongly affected the levels of inhibition. We also demonstrated that elevating activity in adult-born GCs in awake behaving animals reduced the overall number of mature GCs activated by exploration. These data suggest that inhibitory modulation of mature GCs may be an important function of adult-born hippocampal neurons