Faculty Bibliography

Attention-deficit/hyperactivity disorder (ADHD) and Asperger's Syndrome (AS) share a heterogeneous cognitive profile. Studies assessing executive functions (EF) and social cognition in both groups have found preserved and impaired performances. These inconsistent findings would be partially explained by the cognitive variability reported in these disorders. First, the present study explored the inter-individual variability in EF and social cognition in both patient groups. Second, we compared differential characteristics and commonalities in the cognitive profiles of EF and social cognition between ADHD, AS and control adults. We assessed 22 patients with ADHD, 23 adults with AS and 21 matched typically developing subjects using different measures of EF (working memory, cognitive flexibility and multitasking) and social cognition (theory of mind and decision-making). Group comparisons and multiple case series analyses (MCSA) were conducted. The between-group comparisons showed an EF deficit in working memory in ADHD and a theory of mind (ToM) impairment in AS. The MCSA evidenced that, compared to controls, ADHD patients had a higher inter-individual variability in EF, while individuals with AS had a more heterogeneous profile in social cognition tasks compared to both groups. Finally, the AS and ADHD groups presented higher task-related variability compared to controls and shared a common heterogeneous profile in EF. This is the first study to compare variability in EF and social cognition profiles of ADHD and AS. We propose that heterogeneity in EF performance is a link between ADHD and AS which may explain the overlap of symptomatology between both diagnoses. In addition, patients with AS seem to show a unique heterogeneous profile in ToM which may explain the low probability of finding AS symptoms in patients with ADHD.

OBJECTIVES: The purpose of this study is to examine the use of prescribed psychoactive medications in a prospective cohort of children shortly after they entered foster homes; and to identify demographics, maltreatment history, psychiatric diagnoses including ADHD comorbidity, and level of aggression that contribute to prescribed use of stimulant and atypical antipsychotic medication over time. METHODS: The sample included N = 252 children (nested in 95 sibling groups) followed for three years up to 4 yearly waves. RESULTS: Nearly all (89%) met criteria for at least one of eight psychiatric diagnoses and 31% (75/252) used one or more prescribed psychoactive medications. Over half (55%) were diagnosed with Attention Deficit Hyperactivity Disorder (ADHD); of these 38% used stimulants and 36% used atypical antipsychotics. Of the 75 medicated children, 19% received >/=3 different classes of drugs over the course of the study. Stimulants (69%) and atypical antipsychotics (65%) were the most frequently used drugs among medicated children. Adjusted odds ratios (AOR) showed that male gender (AOR = 3.2; 95% CI = 1.5-9.3), African American vs Latino ethnicity (AOR = 5.4; 95% CI = 2.1-14.2), ADHD regardless of Oppositional Defiant (ODD) or Conduct (CD) comorbidity (AOR = 6.0, 95% CI = 1.3-27.5), ODD or CD (AOR = 11.1, 95% CI = 2.1-58.6), and Separation Anxiety (AOR = 2.0, 95% CI = 1.0-4.0) psychiatric disorders were associated with the use of prescribed stimulants; while male gender (AOR = 3.8, 95% CI = 1.5-9.3), African American vs Latino (AOR = 5.1, 95% CI = 1.2-9.2) or Mixed/Other ethnicity (AOR = 3.3, 95% CI = 1.9-13.7), ADHD regardless of ODD or CD comorbidity (AOR = 5.8, 95% CI = 1.2-28.7), ODD or CD (AOR = 13.9, 95% CI = 3.3-58.5), Major Depression/Dysthymia (AOR = 2.8, 95% CI = 1.1-6.7) psychiatric disorders, and history of sexual abuse (AOR = 4.6, 95% CI = 1.3-18.4) were associated with the use of prescribed atypical antipsychotics. CONCLUSION: The aggressive use of atypical antipsychotics, which has unknown metabolic risks, suggests that the efficacy and safety of such treatment strategies for psychiatrically ill children in foster care should be monitored.

BACKGROUND: Individuals with autism spectrum disorders (ASD) often exhibit symptoms of attention-deficit/hyperactivity disorder (ADHD). Across both disorders, observations of distributed functional abnormalities suggest aberrant large-scale brain network connectivity. Yet, common and distinct network correlates of ASD and ADHD remain unidentified. Here, we aimed to examine patterns of dysconnection in school-age children with ASD and ADHD and typically developing children who completed a resting state functional magnetic resonance imaging scan. METHODS: We measured voxelwise network centrality, functional connectivity metrics indexing local (degree centrality [DC]) and global (eigenvector centrality) functional relationships across the entire brain connectome, in resting state functional magnetic resonance imaging data from 56 children with ASD, 45 children with ADHD, and 50 typically developing children. A one-way analysis of covariance, with group as fixed factor (whole-brain corrected), was followed by post hoc pairwise comparisons. RESULTS: Cortical and subcortical areas exhibited centrality abnormalities, some common to both ADHD and ASD, such as in precuneus. Others were disorder-specific and included ADHD-related increases in DC in right striatum/pallidum, in contrast with ASD-related increases in bilateral temporolimbic areas. Secondary analyses differentiating children with ASD into those with or without ADHD-like comorbidity (ASD+ and ASD-, respectively) revealed that the ASD+ group shared ADHD-specific abnormalities in basal ganglia. By contrast, centrality increases in temporolimbic areas characterized children with ASD regardless of ADHD-like comorbidity. At the cluster level, eigenvector centrality group patterns were similar to DC. CONCLUSIONS: ADHD and ASD are neurodevelopmental disorders with distinct and overlapping clinical presentations. This work provides evidence for both shared and distinct underlying mechanisms at the large-scale network level.

Central to the development of clinical applications of functional connectomics for neurology and psychiatry is the discovery and validation of biomarkers. Resting state fMRI (R-fMRI) is emerging as a mainstream approach for imaging-based biomarker identification, detecting variations in the functional connectome that can be attributed to clinical variables (e.g., diagnostic status). Despite growing enthusiasm, many challenges remain. Here, we assess evidence of the readiness of R-fMRI based functional connectomics to lead to clinically meaningful biomarker identification through the lens of the criteria used to evaluate clinical tests (i.e., validity, reliability, sensitivity, specificity, and applicability). We focus on current R-fMRI-based prediction efforts, and survey R-fMRI used for neurosurgical planning. We identify gaps and needs for R-fMRI-based biomarker identification, highlighting the potential of emerging conceptual, analytical and cultural innovations (e.g., the Research Domain Criteria Project (RDoC), open science initiatives, and Big Data) to address them. Additionally, we note the need to expand future efforts beyond identification of biomarkers for disease status alone to include clinical variables related to risk, expected treatment response and prognosis.

A consolidated memory can be transiently destabilized by memory retrieval, after which memories are reconsolidated within a few hours; however, the molecular substrates underlying this destabilization process remain essentially unknown. Here we show that at lateral amygdala synapses, fear memory consolidation correlates with increased surface expression of calcium-impermeable AMPA receptors (CI-AMPARs), which are known to be more stable at the synapse, whereas memory retrieval induces an abrupt exchange of CI-AMPARs to calcium-permeable AMPARs (CP-AMPARs), which are known to be less stable at the synapse. We found that blockade of either CI-AMPAR endocytosis or NMDA receptor activity during memory retrieval, both of which blocked the exchange to CP-AMPARs, prevented memory destabilization, indicating that this transient exchange of AMPARs may underlie the transformation of a stable memory into an unstable memory. These newly inserted CP-AMPARs gradually exchanged back to CI-AMPARs within hours, which coincided with the course of reconsolidation. Furthermore, blocking the activity of these newly inserted CP-AMPARs after retrieval impaired reconsolidation, suggesting that they serve as synaptic "tags" that support synapse-specific reconsolidation. Taken together, our results reveal unexpected physiological roles of CI-AMPARs and CP-AMPARs in transforming a consolidated memory into an unstable memory and subsequently guiding reconsolidation.

We report the first application of a novel diffusion-based MRI method, called diffusional kurtosis imaging (DKI), to investigate changes in brain tissue microstructure in patients with mild cognitive impairment (MCI) and AD and in cognitively intact controls. The subject groups were characterized and compared in terms of DKI-derived metrics for selected brain regions using analysis of covariance with a Tukey multiple comparison correction. Receiver operating characteristic (ROC) and binary logistic regression analyses were used to assess the utility of regional diffusion measures, alone and in combination, to discriminate each pair of subject groups. ROC analyses identified mean and radial kurtoses in the anterior corona radiata as the best individual discriminators of MCI from controls, with the measures having an area under the ROC curve (AUC) of 0.80 and 0.82, respectively. The next best discriminators of MCI from controls were diffusivity and kurtosis (both mean and radial) in the prefrontal white matter (WM), with each measure having an AUC between 0.77 and 0.79. Finally, the axial diffusivity in the hippocampus was the best overall discriminator of MCI from AD, having an AUC of 0.90. These preliminary results suggest that non-Gaussian diffusion MRI may be beneficial in the assessment of microstructural tissue damage at the early stage of MCI and may be useful in developing biomarkers for the clinical staging of AD.