Faculty Bibliography

OBJECTIVE: To document the persistence and predictors of mental health problems in children aged 12 to 18 months investigated for alleged maltreatment. METHODS: Data came from the second National Survey of Child and Adolescent Well-being (NSCAW II), a longitudinal study of youth 0 to 17.5 years referred to US child welfare agencies. These analyses involved children 12 to 18 months. Baseline sociodemographic, social services, developmental data, and health data were collected on children and caregivers. Potential social-emotional problems at baseline were assessed with the Brief Infant-Toddler Social and Emotional (BITSEA) scales. Outcomes were scores over the clinical cutoff on the Child Behavior Checklist (CBCL) 1.5-5 assessed at 18 months after study entry. RESULTS: The multivariable analyses showed that an elevated BITSEA score at baseline (odds ratio 9.18, 95% confidence interval 1.49, 56.64; P = .018) and living with a depressed caregiver (odds ratio 13.54, 95% confidence interval 2.50, 73.46; P = .003) were associated with CBCL scores in the clinical range at the 18-month follow-up. For children who scored both positive on the BITSEA and lived with a depressed caregiver, 62.5% scored positive on the CBCL compared to 10.7% of the children with one risk factor and 3.8% of the children with neither risk factor. Only 23.9% of children and/or their caregivers received any service. CONCLUSIONS: Data show considerable persistence of mental health problems in very young children that 2 factors could identify. Lack of services to these children is a tremendous missed opportunity for identification and treatment that could potentially prevent more serious mental health problems.

The last decades of neuroscience research have produced immense progress in the methods available to understand brain structure and function. Social, cognitive, clinical, affective, economic, communication, and developmental neurosciences have begun to map the relationships between neuro-psychological processes and behavioral outcomes, yielding a new understanding of human behavior and promising interventions. However, a limitation of this fast moving research is that most findings are based on small samples of convenience. Furthermore, our understanding of individual differences may be distorted by unrepresentative samples, undermining findings regarding brain-behavior mechanisms. These limitations are issues that social demographers, epidemiologists, and other population scientists have tackled, with solutions that can be applied to neuroscience. By contrast, nearly all social science disciplines, including social demography, sociology, political science, economics, communication science, and psychology, make assumptions about processes that involve the brain, but have incorporated neural measures to differing, and often limited, degrees; many still treat the brain as a black box. In this article, we describe and promote a perspective--population neuroscience--that leverages interdisciplinary expertise to (i) emphasize the importance of sampling to more clearly define the relevant populations and sampling strategies needed when using neuroscience methods to address such questions; and (ii) deepen understanding of mechanisms within population science by providing insight regarding underlying neural mechanisms. Doing so will increase our confidence in the generalizability of the findings. We provide examples to illustrate the population neuroscience approach for specific types of research questions and discuss the potential for theoretical and applied advances from this approach across areas.

As researchers increase their efforts to characterize variations in the functional connectome across studies and individuals, concerns about the many sources of nuisance variation present and their impact on resting state fMRI (R-fMRI) measures continue to grow. Although substantial within-site variation can exist, efforts to aggregate data across multiple sites such as the 1000 Functional Connectomes Project (FCP) and International Neuroimaging Data-sharing Initiative (INDI) datasets amplify these concerns. The present work draws upon standardization approaches commonly used in the microarray gene expression literature, and to a lesser extent recent imaging studies, and compares them with respect to their impact on relationships between common R-fMRI measures and nuisance variables (e.g., imaging site, motion), as well as phenotypic variables of interest (age, sex). Standardization approaches differed with regard to whether they were applied post-hoc vs. during pre-processing, and at the individual vs. group level; additionally they varied in whether they addressed additive effects vs. additive+multiplicative effects, and were parametric vs. non-parametric. While all standardization approaches were effective at reducing undesirable relationships with nuisance variables, post-hoc approaches were generally more effective than global signal regression (GSR). Across approaches, correction for additive effects (global mean) appeared to be more important than for multiplicative effects (global SD) for all R-fMRI measures, with the exception of amplitude of low frequency fluctuations (ALFF). Group-level post-hoc standardizations for mean-centering and variance-standardization were found to be advantageous in their ability to avoid the introduction of artifactual relationships with standardization parameters; though results between individual and group-level post-hoc approaches were highly similar overall. While post-hoc standardization procedures drastically increased test-retest (TRT) reliability for ALFF, modest reductions were observed for other measures after post-hoc standardizations-a phenomena likely attributable to the separation of voxel-wise from global differences among subjects (global mean and SD demonstrated moderate TRT reliability for these measures). Finally, the present work calls into question previous observations of increased anatomical specificity for GSR over mean centering, and draws attention to the near equivalence of global and gray matter signal regression.

BACKGROUND:Childhood attention-deficit/hyperactivity disorder (ADHD) persists into adulthood in around half of those affected, constituting a major public health challenge. No known demographic, clinical, or neuropsychological factors robustly explain the clinical course, directing our focus to the brain. Herein, we link the trajectories of cerebral cortical development during childhood and adolescence with the severity of adult ADHD. METHODS:Using a longitudinal study design, 92 participants with ADHD had childhood (mean 10.7 years, SD 3.3) and adult clinical assessments (mean 23.8 years, SD 4.3) with repeated neuroanatomic magnetic resonance imaging. Contrast was made against 184 matched typically developing volunteers. RESULTS:Attention-deficit/hyperactivity disorder persisted in 37 (40%) subjects and adult symptom severity was linked to cortical trajectories. Specifically, as the number of adult symptoms increased, particularly inattentive symptoms, so did the rate of cortical thinning in the medial and dorsolateral prefrontal cortex. For each increase of one symptom of adult ADHD, the rate of cortical thinning increased by .0018 mm (SE = .0004, t = 4.2, p < .0001), representing a 5.6% change over the mean rate of thinning for the entire group. These differing trajectories resulted in a convergence toward typical dimensions among those who remitted and a fixed, nonprogressive deficit in persistent ADHD. Notably, cortical thickening or minimal thinning (greater than -.007 mm/year) was found exclusively among individuals who remitted. CONCLUSIONS:Adult ADHD status is linked with the developmental trajectories of cortical components of networks supporting attention, cognitive control, and the default mode network. This informs our understanding of the developmental pathways to adult ADHD.

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.

BACKGROUND: Attention-deficit/hyperactivity disorder (ADHD) is increasingly conceived as reflecting altered functional and structural brain connectivity. The latter can be addressed with diffusion tensor imaging (DTI). We examined fractional anisotropy (FA), a DTI index related to white matter structural properties, in adult male subjects diagnosed with ADHD in childhood (probands) and matched control subjects without childhood ADHD. Additionally, we contrasted FA among probands with and without current ADHD in adulthood and control subjects. METHODS: Participants were from an original cohort of 207 boys and 178 male control subjects. At 33-year follow-up, analyzable DTI scans were obtained in 51 probands (41.3+/-2.8 yrs) and 66 control subjects (41.2+/-3.1 yrs). Voxel-based FA was computed with tract-based spatial statistics, controlling for multiple comparisons. RESULTS: Probands with childhood ADHD exhibited significantly lower FA than control subjects without childhood ADHD in the right superior and posterior corona radiata, right superior longitudinal fasciculus, and in a left cluster including the posterior thalamic radiation, the retrolenticular part of the internal capsule, and the sagittal stratum (p<.05, corrected). Fractional anisotropy was significantly decreased relative to control subjects in several tracts in both probands with current and remitted ADHD, who did not differ significantly from each other. Fractional anisotropy was not significantly increased in probands in any region. CONCLUSIONS: Decreased FA in adults with childhood ADHD regardless of current ADHD might be an enduring trait of ADHD. White matter tracts with decreased FA connect regions involved in high-level as well as sensorimotor functions, suggesting that both types of processes are involved in the pathophysiology of ADHD.

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.

BACKGROUND: This study examined the effects of lisdexamfetamine dimesylate (LDX) on quality of life (QOL) in adults with attention-deficit/hyperactivity disorder (ADHD) and clinically significant executive function deficits (EFD). METHODS: This report highlights QOL findings from a 10-week randomized placebo-controlled trial of LDX (30-70 mg/d) in adults (18-55 years) with ADHD and EFD (Behavior Rating Inventory of EF-Adult, Global Executive Composite [BRIEF-A GEC] >/=65). The primary efficacy measure was the self-reported BRIEF-A; a key secondary measure was self-reported QOL on the Adult ADHD Impact Module (AIM-A). The clinician-completed ADHD Rating Scale version IV (ADHD-RS-IV) with adult prompts and Clinical Global Impressions-Severity (CGI-S) were also employed. The Adult ADHD QoL (AAQoL) was added while the study was in progress. A post hoc analysis examined the subgroup having evaluable results from both AIM-A and AAQoL. RESULTS: Of 161 randomized (placebo, 81; LDX, 80), 159 were included in the safety population. LDX improved AIM-A multi-item domain scores versus placebo; LS mean difference for Performance and Daily Functioning was 21.6 (ES, 0.93, P<.0001); Impact of Symptoms: Daily Interference was 14.9 (ES, 0.62, P<.0001); Impact of Symptoms: Bother/Concern was 13.5 (ES, 0.57, P=.0003); Relationships/Communication was 7.8 (ES, 0.31, P=.0302); Living With ADHD was 9.1 (ES, 0.79, P<.0001); and General Well-Being was 10.8 (ES, 0.70, P<.0001). AAQoL LS mean difference for total score was 21.0; for subscale: Life Productivity was 21.0; Psychological Health was 12.1; Life Outlook was 12.5; and Relationships was 7.3. In a post hoc analysis of participants with both AIM-A and AAQoL scores, AIM-A multi-item subgroup analysis scores numerically improved with LDX, with smaller difference for Impact of Symptoms: Daily Interference. The safety profile of LDX was consistent with amphetamine use in previous studies. CONCLUSIONS: Overall, adults with ADHD/EFD exhibited self-reported improvement on QOL, using the AIM-A and AAQoL scales in line with medium/large ES; these improvements were paralleled by improvements in EF and ADHD symptoms. The safety profile of LDX was similar to previous studies. TRIAL REGISTRATION: ClinicalTrials.gov, NCT01101022.