Faculty Bibliography

Translation in dendrites is believed to support synaptic changes during memory consolidation. Although translational control mechanisms are fundamental mediators of memory, little is known about their role in local translation. We previously found that polyribosomes accumulate in dendritic spines of the adult rat lateral amygdala (LA) during consolidation of aversive pavlovian conditioning and that this memory requires cap-dependent initiation, a primary point of translational control in eukaryotic cells. Here we used serial electron microscopy reconstructions to quantify polyribosomes in LA dendrites when consolidation was blocked by the cap-dependent initiation inhibitor 4EGI-1. We found that 4EGI-1 depleted polyribosomes in dendritic shafts and selectively prevented their upregulation in spine heads, but not bases and necks, during consolidation. Cap-independent upregulation was specific to spines with small, astrocyte-associated synapses. Our results reveal that cap-dependent initiation is involved in local translation during learning and that local translational control varies with synapse type.SIGNIFICANCE STATEMENT Translation initiation is a central regulator of long-term memory formation. Local translation in dendrites supports memory by providing necessary proteins at synaptic sites, but it is unknown whether this requires initiation or bypasses it. We used serial electron microscopy reconstructions to examine polyribosomes in dendrites when memory formation was blocked by an inhibitor of translation initiation. This revealed two major pools of polyribosomes that were upregulated during memory formation: one pool in dendritic spine heads that was initiation dependent and another pool in the bases and necks of small spines that was initiation independent. Thus, translation regulation differs between spine types and locations, and translation that occurs closest to individual synapses during memory formation is initiation dependent.

Resting-state functional Magnetic Resonance Imaging (R-fMRI) holds the promise to reveal functional biomarkers of neuropsychiatric disorders. However, extracting such biomarkers is challenging for complex multi-faceted neuropathologies, such as autism spectrum disorders. Large multi-site datasets increase sample sizes to compensate for this complexity, at the cost of uncontrolled heterogeneity. This heterogeneity raises new challenges, akin to those face in realistic diagnostic applications. Here, we demonstrate the feasibility of inter-site classification of neuropsychiatric status, with an application to the Autism Brain Imaging Data Exchange (ABIDE) database, a large (N=871) multi-site autism dataset. For this purpose, we investigate pipelines that extract the most predictive biomarkers from the data. These R-fMRI pipelines build participant-specific connectomes from functionally-defined brain areas. Connectomes are then compared across participants to learn patterns of connectivity that differentiate typical controls from individuals with autism. We predict this neuropsychiatric status for participants from the same acquisition sites or different, unseen, ones. Good choices of methods for the various steps of the pipeline lead to 67% prediction accuracy on the full ABIDE data, which is significantly better than previously reported results. We perform extensive validation on multiple subsets of the data defined by different inclusion criteria. These enables detailed analysis of the factors contributing to successful connectome-based prediction. First, prediction accuracy improves as we include more subjects, up to the maximum amount of subjects available. Second, the definition of functional brain areas is of paramount importance for biomarker discovery: brain areas extracted from large R-fMRI datasets outperform reference atlases in the classification tasks.

BACKGROUND:Under the Affordable Care Act, States have obtained Medicaid waivers to overhaul their behavioral health service systems to improve quality and reduce costs. Critical to implementation of broad service delivery reforms has been the preparation of organizations responsible for service delivery. This study focused on one large-scale initiative to overhaul its service system with the goal of improving service quality and reducing costs. The study examined the participation of behavioral health organizations in technical assistance efforts and the extent to which organizational factors related to their participation. METHODS:This study matched two datasets to examine the organizational characteristics and training participation for 196 behavioral health organizations. Organizational characteristics were drawn from the Substance Abuse and Mental Health Services Administration National Mental Health Services Survey (N-MHSS). Training variables were drawn from the Clinical Technical Assistance Center's master training database. Chi-square analyses and multivariate logistic regression models were used to examine the proportion of organizations that participated in training, the organizational characteristics (size, population served, service quality, infrastructure) that predicted participation in training, and for those who participated, the type (clinical or business) and intensity of training (webinar, learning collaborative, in-person) they received. RESULTS:Overall 142 (72. 4%) of the sample participated in training. Organizations who pursued training were more likely to be large in size (p = .02), serve children in addition to adults (p < .01), provide child evidence-based practices (p = .01), and use computerized scheduling (p = .01). Of those trained, 95% participated in webinars, 64% participated in learning collaboratives and 35% participated in in-person trainings. More organizations participated in business trainings than clinical (63.8 vs. 59.2%). Organizations serving children had higher odds of participating in both clinical training (OR = 5.91, p < .01) and business training (OR = 4.24, p < .01) than those that did not serve children. CONCLUSIONS:The majority of organizations participated in trainings indicating desire for technical assistance to prepare for health care reform. Larger organizations and organizations serving children were more likely to participate potentially indicating increased interest in preparation. Over half participated in business trainings highlighting interest in learning to improve efficiency. Further understanding is needed to support organizational readiness for health care reform initiatives among behavioral health organizations.

Traumatic experiences early in life predispose animals and humans to later cognitive-behavioral, emotional, and somatic problems. In humans, traumatic experiences are strong predictors of psychiatric illness. A growing body of research has emphasized alterations in neurological structure and function that underscore phenotypic changes following trauma. However, results are mixed and imprecise. We argue that future translation of neurological findings to clinical practice will require: (1) discovery of neurobehavioral associations within a longitudinal context, (2) dissociation of trauma types and of trauma versus chronic stress, and (3) better localization of neural sequelae considerate of the fine resolution of neural circuitry. We provide a brief overview of early brain development and highlight the role of longitudinal research in unearthing brain-behavior relations in youth. We relay an emergent framework in which dissociable trauma types are hypothesized to impact distinct, rationally informed neural systems. In line with this, we discuss the long-standing challenge of separating effects of chronic stress and trauma, as these are often intertwined. We bring to light inconsistencies in localization of neural correlates of trauma, emphasizing results in medial prefrontal regions. We assert that more precise spatial brain localization will help to advance prevailing models of trauma pathways and inform future research.

Although the search for quantitative trait loci for behaviour remains a considerable challenge, the complicated genetic architecture of quantitative traits is beginning to be understood. The current project utilised heterogeneous stock (HS) male mice (n = 580) to investigate the genetic basis for brain weights, activity, anxiety and cognitive phenotypes. We identified 126 single nucleotide polymorphisms (SNPs) in genes involved in regulation of neurotransmitter systems, nerve growth/death and gene expression, and subsequently investigated their associations with changes in behaviour and/or brain weights in our sample. We found significant associations between four SNP-phenotype pairs, after controlling for multiple testing. Specificity protein 2 (Sp2, rs3708840), tryptophan hydroxylase 1 (Tph1, rs262731280) and serotonin receptor 3A (Htr3a, rs50670893) were associated with activity/anxiety behaviours, and microtubule-associated protein 2 (Map2, rs13475902) was associated with cognitive performance. All these genes except for Tph1 were expressed in the brain above the array median, and remained significantly associated with relevant behaviours after controlling for the family structure. Additionally, we found evidence for a correlation between Htr3a expression and activity. We discuss our findings in the light of the advantages and limitations of currently available mouse genetic tools, suggesting further directions for association studies in rodents.

OBJECTIVE: The study examined state variation in rates of Supplemental Security Income (SSI) determinations, allowances, and receipt of benefits for ten selected child mental disabilities in 2013. METHODS: SSI administrative and U.S. Census Bureau data collected by a multidisciplinary consensus committee convened by the National Academies of Science, Engineering, and Medicine in 2015 were examined. RESULTS: Less than 1% of children in 2013 were recipients of SSI for mental disabilities. Determination rates ranged from 1,441 to 251 per 100,000 low-income children, an almost sixfold difference. Allowance rates varied from 16% to 78%, a fivefold difference. Receipt of benefits ranged from .7% to 5.3%, a sevenfold difference. CONCLUSIONS: Large unexplained discrepancies across states were found in review and receipt of SSI benefits for low-income children with mental disabilities. Inequities that cannot be explained by disability severity or financial need violate the ethos of equitable access to federally entitled services.

This data descriptor describes a repository of openly shared data from an experiment to assess inter-individual differences in default mode network (DMN) activity. This repository includes cross-sectional functional magnetic resonance imaging (fMRI) data from the Multi Source Interference Task, to assess DMN deactivation, the Moral Dilemma Task, to assess DMN activation, a resting state fMRI scan, and a DMN neurofeedback paradigm, to assess DMN modulation, along with accompanying behavioral and cognitive measures. We report technical validation from n=125 participants of the final targeted sample of 180 participants. Each session includes acquisition of one whole-brain anatomical scan and whole-brain echo-planar imaging (EPI) scans, acquired during the aforementioned tasks and resting state. The data includes several self-report measures related to perseverative thinking, emotion regulation, and imaginative processes, along with a behavioral measure of rapid visual information processing. Technical validation of the data confirms that the tasks deactivate and activate the DMN as expected. Group level analysis of the neurofeedback data indicates that the participants are able to modulate their DMN with considerable inter-subject variability. Preliminary analysis of behavioral responses and specifically self-reported sleep indicate that as many as 73 participants may need to be excluded from an analysis depending on the hypothesis being tested. The present data are linked to the enhanced Nathan Kline Institute, Rockland Sample and builds on the comprehensive neuroimaging and deep phenotyping available therein. As limited information is presently available about individual differences in the capacity to directly modulate the default mode network, these data provide a unique opportunity to examine DMN modulation ability in relation to numerous phenotypic characteristics.