Publications by authors named "Geoffrey B Hall"

Clinical studies of major depression (MD) generally focus on group effects, yet interindividual differences in brain function are increasingly recognized as important and may even impact effect sizes related to group effects. Here, we examine the magnitude of individual differences in relation to group differences that are commonly investigated (e.g.

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Neural network-level changes underlying symptom remission in major depressive disorder (MDD) are often studied from a single perspective. Multimodal approaches to assess neuropsychiatric disorders are evolving, as they offer richer information about brain networks. A pipeline was developed to integrate a computationally intense data fusion method with a toolbox, to produce a faster and more intuitive pipeline for combining functional connectivity with structural connectivity (denoted as anatomically weighted functional connectivity ()).

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Vocational programs typically focus on building the skills of autistic youth. However, there is growing recognition that the supportive environment (or ecosystem) around an individual plays an important role in finding and maintaining work. Programs at the ecosystem-level can be established by coordinating support before high school ends.

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In utero, the developing brain is highly susceptible to the environment. For example, adverse maternal experiences during the prenatal period are associated with outcomes such as altered neurodevelopment and emotion dysregulation. Yet, the underlying biological mechanisms remain unclear.

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Introduction: Environmental perturbations during critical periods can have pervasive, organizational effects on neurodevelopment. To date, the literature examining the long-term impact of early life adversity has largely investigated structural and functional imaging data outcomes independently. However, emerging research points to a relationship between functional connectivity and the brain's underlying structural architecture.

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Many previous intervention studies have used functional magnetic resonance imaging (fMRI) data to predict the antidepressant response of patients with major depressive disorder (MDD); however, practical constraints have limited many of those attempts to small, single centre studies which may not adequately reflect how these models will generalize when used in clinical practice. Not only does the act of collecting data at multiple sites generally increase sample sizes (a critical point in machine learning development) it also generates a more heterogeneous dataset due to systematic differences in scanners at different sites, and geographical differences in patient populations. As part of the Canadian Biomarker Integration Network in Depression (CAN-BIND-1) study, 144 MDD patients from six sites underwent resting state fMRI prior to starting escitalopram treatment, and again two weeks after the start.

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Although associations among borderline personality disorder (BPD), social rejection, and frontal EEG alpha asymmetry scores (FAA, a neural correlate of emotion regulation and approach-withdrawal motivations) have been explored in different studies, relatively little work has examined these relations during adolescence in the same study. We examined whether FAA moderated the relation between BPD features and rejection sensitivity following a validated social exclusion paradigm, Cyberball. A mixed, clinical-community sample of 64 adolescents (females = 62.

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Clinically oriented studies commonly acquire diffusion MRI (dMRI) data with a single non-zero-value (i.e. single-shell) and diffusion weighting of= 1000 s mm.

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Executive functions (EF) deficits are hypothesized to be a core contributor to hoarding symptoms. EF have been studied in adult hoarding populations, but studies in youth are lacking. The current study compared multiple EF subdomains between youth with obsessive-compulsive disorder (OCD) and youth with OCD and hoarding symptoms.

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Understanding the neural underpinnings of major depressive disorder (MDD) and its treatment could improve treatment outcomes. So far, findings are variable and large sample replications scarce. We aimed to replicate and extend altered functional connectivity associated with MDD and pharmacotherapy outcomes in a large, multisite sample.

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There is a growing interest in examining the wealth of data generated by fusing functional and structural imaging information sources. These approaches may have clinical utility in identifying disruptions in the brain networks that underlie major depressive disorder (MDD). We combined an existing software toolbox with a mathematically dense statistical method to produce a novel processing pipeline for the fast and easy implementation of data fusion analysis (FATCAT-awFC).

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In the United States, approximately 2.53 million people sustain a concussion each year. Relative to adults, youth show greater cognitive deficits following concussion and a longer recovery.

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Quality assurance (QA) is crucial in longitudinal and/or multi-site studies, which involve the collection of data from a group of subjects over time and/or at different locations. It is important to regularly monitor the performance of the scanners over time and at different locations to detect and control for intrinsic differences (e.g.

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Identifying biomarkers of serious mental illness, such as altered white matter microstructure, can aid in early diagnosis and treatment. White matter microstructure was assessed using constrained spherical deconvolution of diffusion imaging data in a sample of 219 youth (age 12-25 years, 64.84% female) across 8 sites.

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Concussions are a major health concern due to the unpredictable onset and resolution of debilitating post-concussion symptoms. This review discusses physiological, structural and functional brain changes post-concussion, novel non-invasive medical imaging techniques to improve diagnosis, and the role exercise could play in concussion recovery. After sustaining a concussion, about 50% of youth and 20% of adults have symptoms that last for more than a month.

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Background: Obesity and major depressive disorder (MDD) independently contribute to memory impairment. Little is known about shared neural mechanisms that may result in the cognitive impairment experienced by these populations. This study's aim was to determine how obesity impacts neural activity during a verbal recognition memory task in individuals both with and without MDD.

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Background: Genetic risk factors that contribute to obsessive-compulsive disorder (OCD) have yet to be elucidated. Historically, serotonergic dysfunction has been implicated. Evidence from the literature points towards the serotonin receptor 2A gene (HTR2A) as a primary candidate.

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Article Synopsis
  • The study compares ADHD, ASD, and OCD using brain imaging data from over 5,000 healthy controls and numerous patients across different age groups, focusing on structural differences in the brain.
  • No consistent differences were observed across all three disorders, with some specific findings like smaller hippocampal volumes in children with ADHD compared to OCD.
  • The results highlight that while subtle differences exist between these disorders, the distinctions are most apparent in specific age groups, emphasizing ADHD's unique brain volume differences in younger individuals and ASD's cortical thickness variations in adults.
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A key objective in the field of translational psychiatry over the past few decades has been to identify the brain correlates of major depressive disorder (MDD). Identifying measurable indicators of brain processes associated with MDD could facilitate the detection of individuals at risk, and the development of novel treatments, the monitoring of treatment effects, and predicting who might benefit most from treatments that target specific brain mechanisms. However, despite intensive neuroimaging research towards this effort, underpowered studies and a lack of reproducible findings have hindered progress.

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Major depressive disorder (MDD) is associated with an increased risk of brain atrophy, aging-related diseases, and mortality. We examined potential advanced brain aging in adult MDD patients, and whether this process is associated with clinical characteristics in a large multicenter international dataset. We performed a mega-analysis by pooling brain measures derived from T1-weighted MRI scans from 19 samples worldwide.

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: Post-concussive depression describes an elevation of depressive symptoms following concussion that occurs in conjunction with other symptoms of concussion. Children with concussion are more likely to diagnosed with depression. The overlapping symptoms between clinical depression and concussion make the diagnosis of depression difficult.

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Major depressive disorder (MDD) is considered a highly heterogeneous clinical and neurobiological mental disorder. We employed a novel layered treatment design to investigate whether cortical thickness features at baseline differentiated treatment responders from non-responders after 8 and 16 weeks of a standardized sequential antidepressant treatment. Secondary analyses examined baseline differences between MDD and controls as a replication analysis and longitudinal changes in thickness after 8 weeks of escitalopram treatment.

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Objective: The need to have a pediatric-specific concussion management protocol on Return to School (RTS) and Return to Activity (RTA) after concussion has been recognized internationally. The first step to evaluate the protocol effectiveness is to establish whether children and youth are adhering to these recommendations. The objective of this study was to explore the prevalence and predictors of adherence to RTS and RTA concussion management protocols for children/youth.

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Task-based functional neuroimaging methods are increasingly being used to identify biomarkers of treatment response in psychiatric disorders. To facilitate meaningful interpretation of neural correlates of tasks and their potential changes with treatment over time, understanding the reliability of the blood-oxygen-level dependent (BOLD) signal of such tasks is essential. We assessed test-retest reliability of an emotional conflict task in healthy participants collected as part of the Canadian Biomarker Integration Network in Depression.

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Background: Identifying objective biomarkers can assist in predicting remission/non-remission to treatment, improving remission rates, and reducing illness burden in major depressive disorder (MDD).

Methods: Sixteen MDD 8-week remitters (MDD-8), twelve 16-week remitters (MDD-16), 14 non-remitters (MDD-NR) and 30 healthy comparison participants (HC) completed a functional magnetic resonance imaging emotional conflict task at baseline, prior to treatment with escitalopram, and 8 weeks after treatment initiation. Patients were followed 16 weeks to assess remitter status.

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