Research Projects
Cutting-edge research at the intersection of neuroscience and artificial intelligence
Current Research Initiatives
At BRAIN Lab @ UTA, our research spans multiple domains at the intersection of computational methods, neuroscience, and psychiatry. We employ cutting-edge techniques from machine learning and artificial intelligence to better understand brain function and mental health conditions.
Explore our ongoing projects below to learn more about our research directions and how they contribute to advancing our understanding of the brain and psychiatric disorders.
Predicting Treatment Response to GCMRT in Social Anxiety Disorder
This project focuses on developing predictive models for treatment response to Guided Cognitive-Motivational Response Training (GCMRT) in individuals with Social Anxiety Disorder.
Reverse Engineering for Robust MDD Biomarkers
This project aims to identify novel neural biotypes for Major Depressive Disorder (MDD) using advanced computational approaches and digital phenotyping.
ACEs and Brain Development in Adolescence
Investigating the role of Adverse Childhood Experiences (ACEs) and sex differences in brain development during adolescence using data from the ABCD Study.
Explainable AI for PTSD Biotypes
Using Explainable AI (XAI) approaches to identify PTSD biotypes and develop personalized treatment strategies.
Neural Correlates of Obesity in Adolescents
A systematic review investigating the neural correlates of obesity in adolescent populations.
PTSD Subtypes and Neural Biomarkers
A systematic review examining PTSD subtypes and their underlying neural biomarkers.
Personalized Treatment for PTSD
Leveraging trait-like and state-like biomarkers in prediction of prolonged exposure therapy treatment outcomes.
Female Endocrine Modulation in PTSD
Investigating the role of female endocrine modulation in PTSD.
Functional Brain Connectivity in Trauma
This research investigates how traumatic experiences affect brain network connectivity and function, using advanced neuroimaging techniques to understand the neural mechanisms underlying trauma response and recovery.
Biotypes of OCD
This research aims to identify distinct biological subtypes of Obsessive-Compulsive Disorder using advanced machine learning techniques and neuroimaging data. By understanding these different subtypes, we can develop more targeted and effective treatments.