Affective Disorders & Precision Psychiatry

Neurobiological Mechanisms of Treatment-Resistant Depression

This research investigates the distinct neural circuitry, genetic polymorphisms, and inflammatory biomarkers that differentiate treatment-resistant depression from responsive major depressive disorder. Findings establish novel therapeutic targets and predictive biomarkers for personalized intervention strategies in refractory populations.

Computational Phenotyping and Stratification in Bipolar Spectrum Disorders

Research applies machine learning and multimodal neuroimaging data to identify distinct biological subtypes within the heterogeneous bipolar spectrum rather than treating it as a monolithic diagnosis. This approach reveals latent disease dimensions and enables precision medicine interventions tailored to individual neurobiology.

Inflammatory Cytokine Profiling and Psychotic Spectrum Vulnerability

This investigation examines peripheral and central inflammatory markers as biological risk factors and state-dependent signatures across the psychosis continuum from prodromal to established psychotic disorders. Results identify immune-mediated pathophysiology and inflammation-targeting therapeutics for precision intervention.

Multisite Brain Connectomics and Anxiety Disorder Network Heterogeneity

Research leverages large-scale functional and structural connectome datasets to map disrupted neural network organization across distinct anxiety disorders and identify connectivity-based subtypes. This work reveals how different network dysfunction patterns predict differential treatment response and prognosis.

Longitudinal Neuroimaging Trajectories of Affective Disorder Progression

This research tracks temporal neurobiological changes using repeated structural and functional neuroimaging to characterize disease progression, remission, and relapse patterns in affective disorders. Findings establish neuroprogressive biomarkers that predict illness course and intervention timing.

Polygenic Risk Scores and Gene-Environment Interactions in Depression

Investigation integrates polygenic risk prediction with detailed environmental exposure assessment to model how genetic vulnerability interacts with specific stressors in depression etiology and treatment response. Results advance mechanistic understanding of gene-by-environment pathways for stratified prevention.

Neurochemical Imaging and Monoamine Dysfunction in Affective Disorders

Research applies positron emission tomography and other neurochemical imaging techniques to directly measure serotonin, dopamine, and norepinephrine system function across affective diagnoses. This work elucidates neurochemical heterogeneity underlying affective symptoms and predicts pharmacological treatment efficacy.

Computational Emotion Modeling and Reward System Dysfunction

This research uses computational psychiatry and reinforcement learning models to characterize anhedonia and reward processing deficits in depression and related conditions at mechanistic levels. Findings reveal computational signatures of hedonic dysfunction that inform biological treatment development.

Digital Phenotyping and Real-World Affective Symptom Dynamics

Investigation leverages passive smartphone sensing, wearable biosensors, and ecological momentary assessment to characterize fine-grained affective symptom fluctuations and environmental triggers in naturalistic settings. This produces granular phenotypic data enabling precision monitoring and intervention personalization.

Neuroplasticity Mechanisms and Psychotherapy Response Prediction Models

Research investigates brain structural and functional changes underlying psychotherapy efficacy and identifies baseline neuroimaging and cognitive markers predicting treatment response. This work establishes neurobiology-informed models for precision psychological intervention selection.