Faculty Bibliography

A major challenge in designing large-scale, multi-site studies is developing a core, scalable protocol that retains the innovation of scientific advances while also lending itself to the variability in experience and resources across sites. In the development of a common Healthy Brain and Child Development (HBCD) protocol, one of the chief questions is "is fetal MRI ready for prime-time?" While there is agreement about the value of prenatal data obtained non-invasively through MRI, questions about practicality abound. There has been rapid progress over the past years in fetal and placental MRI methodology but there is uncertainty about whether the gains afforded outweigh the challenges in supporting fetal MRI protocols at scale. Here, we will define challenges inherent in building a common protocol across sites with variable expertise and will propose a tentative framework for evaluation of design decisions. We will compare and contrast various design considerations for both normative and high-risk populations, in the setting of the post-COVID era. We will conclude with articulation of the benefits of overcoming these challenges and would lend to the primary questions articulated in the HBCD initiative.

Local translation can provide a rapid, spatially targeted supply of new proteins in distal dendrites to support synaptic changes that underlie learning. Learning and memory are especially sensitive to manipulations of translational control mechanisms, particularly those that target the initiation step, and translation initiation at synapses could be a means of maintaining synapse specificity during plasticity. Initiation predominantly occurs via recruitment of ribosomes to the 5' mRNA cap by complexes of eukaryotic initiation factors (eIFs), and the interaction between eIF4E and eIF4G1 is a particularly important target of translational control pathways. Pharmacological inhibition of eIF4E-eIF4G1 binding impairs formation of memory for aversive Pavlovian conditioning as well as the accompanying increase in polyribosomes in the heads of dendritic spines in the lateral amygdala (LA). This is consistent with a role for initiation at synapses in memory formation, but whether eIFs are even present near synapses is unknown. To determine whether dendritic spines contain eIFs and whether eIF distribution is affected by learning, we combined immunolabeling with serial section transmission electron microscopy (ssTEM) volume reconstructions of LA dendrites after Pavlovian conditioning. Labeling for eIF4E, eIF4G1, and eIF2α - another key target of regulation - occurred in roughly half of dendritic spines, but learning effects were only found for eIF4E, which was upregulated in the heads of dendritic spines. Our results support the possibility of regulated translation initiation as a means of synapse-specific protein targeting during learning and are consistent with the model of eIF4E availability as a central point of control. This article is protected by copyright. All rights reserved.

The purpose of this study was to develop a greater understanding of the factors influencing the adoption of evidence-based interventions in outpatient mental health clinics serving youth. An improved understanding of these factors can potentially improve efforts to ensure effective adoption, implementation, and sustainment of evidence-based interventions, and thus improve treatment for youth in mental health settings. This explanatory cross-sectional study involves secondary data analysis of a longitudinal randomized control intervention trial. The SEM- based model that was tested supported the primary hypothesis that a more supportive organizational climate with greater readiness for change is more likely to improve the chances for the adoption of evidence-based interventions in outpatient mental health clinics serving youths.

Major depressive disorder (MDD) causes great decrements in health and quality of life with increments in healthcare costs, but the causes and pathogenesis of depression remain largely unknown, which greatly prevent its early detection and effective treatment. With the advancement of neuroimaging approaches, numerous functional and structural alterations in the brain have been detected in MDD and more recently attempts have been made to apply these findings to clinical practice. In this review, we provide an updated summary of the progress in translational application of psychoradiological findings in MDD with a specified focus on potential clinical usage. The foreseeable clinical applications for different MRI modalities were introduced according to their role in disorder classification, subtyping, and prediction. While evidence of cerebral structural and functional changes associated with MDD classification and subtyping was heterogeneous and/or sparse, the ACC and hippocampus have been consistently suggested to be important biomarkers in predicting treatment selection and treatment response. These findings underlined the potential utility of brain biomarkers for clinical practice.

[This corrects the article DOI: 10.1007/s40670-021-01320-z.].

Investments in autism spectrum disorder (ASD) research, guided by the Interagency Autism Coordinating Committee (IACC), have focused disproportionately on etiology over a well-established stakeholder priority area: research to improve accessibility and quality of community-based services. This study analyzed National Institutes of Health ASD services research funding from 2008 to 2018 to examine funding patterns, evaluate the impact of IACC objectives, and identify future directions. Approximately 9% of total funds were allocated to services research. This investment remained relatively stable across time and lacked diversity across domains (e.g., area of focus, ages sampled, implementation strategies used). While advancements were observed, including increased prevalence of projects focused on adult samples and on dissemination/implementation and prevention areas, greater investment in service research is critically needed.

The default mode network (DMN) is a prominent intrinsic network that is observable in many mammalian brains. However, few studies have investigated the temporal dynamics of this network based on direct physiological recordings. Herein, we addressed this issue by characterizing the dynamics of local field potentials (LFPs) from the rat DMN during wakefulness and sleep with an exploratory analysis. We constructed a novel coactive micropattern (CAMP) algorithm to evaluate the configurations of rat DMN dynamics and further revealed the relationship between DMN dynamics with different wakefulness and alertness levels. From the gamma activity (40-80 Hz) in the DMN across wakefulness and sleep, three spatially stable CAMPs were detected: a common low-activity level micropattern (cDMN), an anterior high-activity level micropattern (aDMN) and a posterior high-activity level micropattern (pDMN). A dynamic balance across CAMPs emerged during wakefulness and was disrupted in sleep stages. In the slow-wave sleep (SWS) stage, cDMN became the primary activity pattern, whereas aDMN and pDMN were the major activity patterns in the rapid eye movement sleep (REM) stage. Additionally, further investigation revealed phasic relationships between CAMPs and the up-down states of the slow DMN activity in the SWS stage. Our study revealed that the dynamic configurations of CAMPs were highly associated with different stages of wakefulness and provided a potential three-state model to describe the DMN dynamics for wakefulness and alertness.