A5010000825- Mental Health Research Topics
- Anxiety, Depression, Psychometrics, Treatment, Cognitive Processes
- Functional Brain Connectivity Studies
- Neural and Behavioral Psychology Studies
- Mental Health and Psychiatry
- Health, Environment, Cognitive Aging
- Advanced MRI Techniques and Applications
- Behavioral and Psychological Studies
- Treatment of Major Depression
- Mental Health Treatment and Access
- Suicide and Self-Harm Studies
- Attention Deficit Hyperactivity Disorder
- Personality Disorders and Psychopathology
- Stress Responses and Cortisol
- Electromagnetic Launch and Propulsion Technology
- Memory and Neural Mechanisms
- Heart Rate Variability and Autonomic Control
- Resilience and Mental Health
- Educational and Psychological Assessments
- Child and Adolescent Psychosocial and Emotional Development
- Digital Mental Health Interventions
- Face Recognition and Perception
- Psychological Testing and Assessment
- Child and Animal Learning Development
Laureate Institute for Brain Research
2020-2024
University of Tulsa
2021-2022
University of Michigan
2022
Neurobehavioral Systems
2022
University of California, Los Angeles
2022
Twin Cities Orthopedics
2022
University of Minnesota
2022
Imbalances in approach-avoidance conflict (AAC) decision-making (e.g., sacrificing rewards to avoid negative outcomes) are considered central multiple psychiatric disorders. We used computational modelling examine 2 factors that often not distinguished descriptive analyses of AAC: decision uncertainty and sensitivity outcomes versus (emotional conflict).A previously validated AAC task was completed by 478 participants, including healthy controls (n = 59), people with substance use disorders...
Maladaptive behavior during approach-avoidance conflict (AAC) is common to multiple psychiatric disorders. Using computational modeling, we previously reported that individuals with depression, anxiety, and substance use disorders (DEP/ANX; SUDs) exhibited differences in decision uncertainty sensitivity negative outcomes versus reward (emotional conflict) relative healthy controls (HCs). However, it remains unknown whether these parameters group are stable over time. We analyzed 1-year...
Functional magnetic resonance imaging studies frequently use emotional face processing tasks to probe neural circuitry related psychiatric disorders and treatments with an emphasis on regions within the salience network (e.g., amygdala). Findings across previous test-retest reliability of have shown high variability, potentially due differences in data analytic approaches. The present study comprehensively examined faces task utilizing multiple approaches region interest (ROI) analysis by...
<h3>Background:</h3> We have previously reported activation in reward, salience and executive control regions during functional MRI (fMRI) using an approach–avoidance conflict (AAC) decision-making task with healthy adults. Further investigations into how anxiety depressive disorders relate to differences neural responses AAC can inform their understanding treatment. tested the hypothesis that people or depression altered AAC. <h3>Methods:</h3> compared 118 treatment-seeking adults 58 linear...
Although patient history is essential for informing mental health assessment, diagnosis, and prognosis, there a dearth of standardized instruments measuring time-dependent factors relevant to psychiatric disorders. Previous research has demonstrated the potential utility graphical representations, termed life charts, depicting complexity course illness. However, implementation these assessments limited by exclusive focus on specific illnesses (ie, bipolar disorder) lack intuitive interfaces...
Abstract Neural and behavioral mechanisms during approach‐avoidance conflict decision‐making are relevant across various psychiatric disorders, particularly anxiety disorders. Studies using paradigms in healthy adults have identified preliminary neural mechanisms, but findings must be replicated demonstrated as reliable before further application. This study sought to replicate previous examine test–retest reliability of (approach behavior, reaction time) (regions interest [ROIs]) responses...
Objective To identify robust and reproducible factors associated with suicidal thoughts behaviors (STBs) in college students.Methods 356 first-year university students completed a large battery of demographic clinically-relevant self-report measures during the first semester end-of-year (n = 228). Suicide Behaviors Questionnaire-Revised (SBQ-R) assessed STBs. A machine learning (ML) pipeline using stacking nested cross-validation examined correlates SBQ-R scores.Results 9.6% were identified...
Neuroscience studies require considerable bioinformatic support and expertise. Numerous high-dimensional multimodal datasets must be preprocessed integrated to create robust reproducible analysis pipelines. We describe a common data elements scalable management infrastructure that allows multiple analytics workflows facilitate preprocessing, sharing of large-scale multi-level data. The process uses the Brain Imaging Data Structure (BIDS) format supports MRI, fMRI, EEG, clinical, laboratory...
Background: Imbalances in approach-avoidance conflict (AAC) decision-making (e.g. sacrificing rewards to avoid negative outcomes) are considered central multiple psychiatric disorders. We used computational modeling examine two factors often not distinguished within model-free analyses of AAC: decision uncertainty (DU) and sensitivity outcomes vs. reward (emotional conflict; EC).Methods: A previously-validated AAC task was completed by 477 participants, including healthy controls (HCs;...
Dysregulation of fear learning has been associated with psychiatric disorders that have altered positive and negative valence domain function. While amygdala-insula-prefrontal circuitry is considered important for learning, there inconsistencies in neural findings healthy clinical human samples. This study aimed to delineate the substrates behavioral responses during a large, transdiagnostic sample predominantly depressive and/or anxious dysfunction.Two-hundred eighty-two individuals (52...
Maladaptive behavior during approach-avoidance conflict (AAC) is common to multiple psychiatric disorders. Using computational modeling, we previously reported that individuals with depression, anxiety, and substance use disorders (DEP/ANX; SUDs) exhibited differences in decision uncertainty sensitivity negative outcomes vs. reward (emotional conflict) relative healthy controls (HCs). However, it remains unknown whether these parameters group are stable over time. We analyzed 1-year...
Abstract Mobile technologies can be used for behavioral assessments to associate changes in behavior with environmental context and its influence on mental health disease. Research real-time motor control a joystick, analyzed using computational proportion-derivative (PD) modeling approach, has shown that model parameters estimated high reliability are related both self-reported fear brain structures important affective regulation, such as the anterior cingulate cortex. Here we introduce...
Background: An estimated 1100 college students die by suicide each year. Our ability to predict who is at risk for suicide, as well our knowledge of resilience factors protecting against it, remains limited. We used a machine learning (ML) framework in conjunction with large battery self-report and demographic measures select features contributing most observed variability suicidal thoughts behaviors (STBs) college.Method: First-year university completed clinically-relevant the beginning...
Background: Sacrificing rewarding aspects of one’s life due to potential aversive outcomes is an important characteristic multiple psychiatric disorders. Such decisions occur during approach-avoidance conflict (AAC), which has become the topic a growing number behavioral and neuroimaging studies. Here we describe novel computational modeling approach studying AAC.Methods: A previously-validated AAC task was completed by 479 participants including healthy controls (HCs), individuals with...
1. Abstract Neuroscience studies require considerable bioinformatic support and expertise. Numerous high-dimensional multimodal datasets must be preprocessed integrated to create robust reproducible analysis pipelines. We describe a common data elements scalable management infrastructure that allows multiple analytics workflows facilitate preprocessing, sharing of large-scale multi-level data. The process uses the Brain Imaging Data Structure (BIDS) format supports MRI, fMRI, EEG, clinical...