Faculty Bibliography

Hurricane Irma was the most powerful Atlantic hurricane in recorded history, displacing 6 million and killing over 120 people in the state of Florida alone. Unpredictable disasters like Irma are associated with poor cognitive and health outcomes that can disproportionately impact children. This study examined the effects of Hurricane Irma on the hippocampus and memory processes previously related to unpredictable stress. We used an innovative application of an advanced diffusion-weighted imaging technique, restriction spectrum imaging (RSI), to characterize hippocampal microstructure (i.e., cell density) in 9- to 10-year-old children who were exposed to Hurricane Irma relative to a non-exposed control group (i.e., assessed the year before Hurricane Irma). We tested the hypotheses that the experience of Hurricane Irma would be associated with decreases in: (a) hippocampal cellularity (e.g., neurogenesis), based on known associations between unpredictable stress and hippocampal alterations; and (b) hippocampal-related memory function as indexed by delayed recall. We show an association between decreased hippocampal cellularity and delayed recall memory in children who experienced Hurricane Irma relative to those who did not. These findings suggest an important role of RSI for assessing subtle microstructural changes related to functionally significant changes in the developing brain in response to environmental events.

Functional brain networks have been shown to undergo fundamental changes associated with aging or schizophrenia. However, the mechanism of how these factors exert influences jointly or interactively on brain networks remains elusive. A unified recognition of connectomic alteration patterns was also hampered by heterogeneities in network construction and thresholding methods. Recently, an unbiased network representation method regardless of network thresholding, so called minimal spanning tree algorithm, has been applied to study the critical skeleton of the brain network. In this study, we aimed to use minimum spanning tree (MST) as an unbiased network reconstruction and employed structural equation modeling (SEM) to unravel intertwined relationships among multiple phenotypic and connectomic variables in schizophrenia. First, we examined global and local brain network properties in 40 healthy subjects and 40 schizophrenic patients aged 21-55 using resting-state functional magnetic resonance imaging (rs-fMRI). Global network alterations are measured by graph theoretical metrics of MSTs and a connectivity-transitivity two-dimensional approach was proposed to characterize nodal roles. We found that networks of schizophrenic patients exhibited a more star-like global structure compared to controls, indicating excessive integration, and a loss of regional transitivity in the dorsal frontal cortex (corrected p <.05). Regional analysis of MST network topology revealed that schizophrenia patients had more network hubs in frontal regions, which may be linked to the "overloading" hypothesis. Furthermore, using SEM, we found that the level of MST integration mediated the influence of age on negative symptom severity (indirect effect 95% CI [0.026, 0.449]). These findings highlighted an altered network skeleton in schizophrenia and suggested that aging-related enhancement of network integration may undermine functional specialization of distinct neural systems and result in aggravated schizophrenic symptoms.

BACKGROUND:We analyzed the relationship between the prevalence of schizophrenia and the season of birth and gestation during a period of an influenza pandemic. METHODS:Cross-sectional analysis of a prospective population-based cohort of 470,942 adults. We fitted multivariant logistic regression models to determine whether the season of birth and birth in an influenza-pandemic year (1957, 1968, 1977) was associated with schizophrenia. RESULTS:2077 subjects had been diagnosed with schizophrenia. Logistic regression identified a significantly greater prevalence of schizophrenia in men than in women (OR = 1.516, CI 95% = 1.388-1.665); in those born in the winter or spring than in those born in the summer or autumn (OR = 1.112, CI 95% = 1.020-1.212); and in those born in a period of an influenza pandemic (OR = 1.335, CI 95% = 1.199-1.486). The increase in risk was also significant when each influenza pandemic year was analyzed separately. However, neither month of birth nor season of birth, when each of the four were studied individually, were associated with a statistically significant increase in that risk. CONCLUSIONS:The winter-spring period and the influenza pandemics are independent risk factors for developing schizophrenia. This study contradicts many previous studies and thus revitalizes a locked debate in understanding the neurodevelopmental hypothesis of this disorder.

Individuals with autism spectrum disorder (ASD) and their first-degree relatives demonstrate automaticity deficits reflected in reduced eye-voice coordination during rapid automatized naming (RAN), suggesting that RAN deficits may be a genetically meaningful marker of ASD language-related impairments. This study investigated whether RAN deficits in ASD extend to a language typologically distinct from English. Participants included 23 Cantonese-speaking individuals with ASD and 39 controls from Hong Kong (HK), and age- and IQ-comparable groups of previously-studied English-speaking individuals with ASD (n = 45) and controls (n = 44) from the US. Participants completed RAN on an eye tracker. Analyses examined naming time, error rate, measures of eye movement reflecting language automaticity, including eye-voice span (EVS; location of eyes versus the named item) and refixations. The HK-ASD group exhibited longer naming times and more refixations than HK-Controls, in a pattern similar to that observed in the US-ASD group. Cultural effects revealed that both HK groups showed longer EVS and more fixations than US groups. Naming time and refixation differences may be ASD-specific impairments spanning cultures/languages, whereas EVS and fixation frequency may be more variably impacted. A potential underlying mechanism of visual "stickiness" may be contributing to this breakdown in language automaticity in ASD.

OBJECTIVE/UNASSIGNED:There was no evidence that 90-days outcomes differed for veterans based on medication received, and there were more similarities than differences in clinical characteristics. Additional research is needed, including larger sample size and prospective randomized control trial to evaluate VA patients' treatment outcomes receiving BUP-NX or XR-NTX for OUD.

BACKGROUND:As mobile technologies become ever more sensor-rich, portable, and ubiquitous, data captured by smart devices are lending rich insights into users' daily lives with unprecedented comprehensiveness and ecological validity. A number of human-subject studies have been conducted to examine the use of mobile sensing to uncover individual behavioral patterns and health outcomes, yet minimal attention has been placed on measuring living environments together with other human-centered sensing data. Moreover, the participant sample size in most existing studies falls well below a few hundred, leaving questions open about the reliability of findings on the relations between mobile sensing signals and human outcomes. RESULTS:To address these limitations, we developed a home environment sensor kit for continuous indoor air quality tracking and deployed it in conjunction with smartphones, Fitbits, and ecological momentary assessments in a cohort study of up to 1,584 college student participants per data type for 3 weeks. We propose a conceptual framework that systematically organizes human-centric data modalities by their temporal coverage and spatial freedom. Then we report our study procedure, technologies and methods deployed, and descriptive statistics of the collected data that reflect the participants' mood, sleep, behavior, and living environment. CONCLUSIONS:We were able to collect from a large participant cohort satisfactorily complete multi-modal sensing and survey data in terms of both data continuity and participant adherence. Our novel data and conceptual development provide important guidance for data collection and hypothesis generation in future human-centered sensing studies.

OBJECTIVE/UNASSIGNED:Strategies are needed to improve policy makers' evidence-informed decision making and the availability of evidence-based, state-supported services. This study examined whether academic-policy partnerships could promote these outcomes. METHODS/UNASSIGNED:Data from two national surveys of state mental health agency representatives were used to compare barriers to implementation of evidence-based practices (EBPs) and policy makers' use of child mental health research in states with strong academic-policy partnerships in workforce training or in program implementation/evaluation (IE) with barriers in states with no or limited partnerships in these areas. RESULTS/UNASSIGNED:Strong IE partnerships were associated with more confidence in research use and fewer issues with provider readiness and capacity but with more issues with EBP fidelity. Strong training partnerships were associated with fewer endorsements of lack of time as a barrier to research use. CONCLUSIONS/UNASSIGNED:Academic-policy partnerships had some benefit for states' research use and EBP implementation. Because these partnerships may reduce barriers, further research should explore characteristics of effective collaborations.