Mei-Hua Hall, PhD

Dr. Hall’s Psychosis Neurobiology Laboratory was founded in 2013. Dr. Hall is currently conducting several projects. One project uses an integrative approach, combining neurophysiological, neurochemical, genetics, clinical and behavioral measures, to understand the neurobiological mechanisms underlying schizophrenia and bipolar disorders. This project also aims to clarify how genetic and environmental risk factors influence psychopathology, neurocognitive traits, and brain function.

Robust genomewide genetic studies have identified many risk genes and variations within those genes associated with schizophrenia and bipolar disorder, though their effects on the brain are largely unknown. The lab collects a variety of neurophysiological, clinical, and cognitive functioning data on patients with these disorders. The goal is to link genetic risk factors associated with psychosis disorders to brain neurophysiological characteristics.

Another project of the lab uses multimodal approaches to stratify patients who experience their first episode psychosis into homogeneous subgroups based on patients’ unique neurobiological profiles and to relate these profiles to later functional recovery outcomes. This study longitudinally follows-up with patients with first episode of psychosis every six months for two years. An expanded biomarker panel (cognition, MRI, EEG, clinical symptoms) and functional outcome measures are collected in each patient. The goals are to identify and better characterize individual longitudinal patterns of functioning recovery, and to explore the potential risk and protective factors associated with functioning outcome.

In addition, the lab uses a computerized cognitive training program for patients with schizophrenia and bipolar disorder with the goal of improving certain cognitive functions (such as memory and attention) and psychosocial outcomes. In recent years, training programs based on learning-induced neuroplasticity have shown promising improvement effects on cognitive function. This suggests that cognitive rehabilitation training induces neurobiological remodeling in brain circuitry relevant to a range of cognitive functions. This project examines brain changes induced by cognitive training to reveal the underlying mechanisms mediating these changes.

A new line of research project, in collaboration with McLean OnTrack, focuses on using natural language processing (NLP) and machine learning techniques and aims to create tools for evaluating and predicting psychosis patient readmission risk as well as risk of harm. The project is currently creating a data analysis pipeline that extracts meaningful information from unstructured clinical narratives in patient electronic health records (EHR) and converts these data to features for use in training our machine learning models. This project includes experts in the fields of psychiatry and computational linguistics. Some of the questions this project aims to address include what are specific risk factors for readmission?, how to quantify these risk factors?, which machine learning models and feature representations exhibit the greatest compatibility with our unique sources of psychiatric EHR data?, how to accurately determine whether a patient’s condition is improving or deteriorating over time? Gaining knowledge toward answering these questions will inform the selection of treatment interventions and implement appropriate preventive measures.

Dr. Hall is collaborating with scientists internationally. She is involved in a project entitled “The Global Research Initiative on the Neurophysiology of Schizophrenia (GRINS)”, and a project entitled “Collaborations in Psychiatry: Fostering Research Opportunities Between McLean Hospital and China.”