A Year in the Life Study
Bryce Gillis presents poster ‘Leveraging ecological assessments to derive robust predictors of mania, psychosis, and depression’ at the 2023 Technology in Psychiatry Summit (TIPS) Annual Meeting in Tampa, FL. See abstract below:
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Bryce received his Bachelor’s in psychology from Wesleyan University in 2022 after studying experimental psychopathology using behavioral and electrophysiological methods. Working in two research labs, he helped with data acquisition and analysis for cognitive, judgment and decision-making tasks and auditory oddball tasks using EEG. Now, he is a clinical RA in the Baker Lab working on longitudinal deep phenotyping studies involving functional neuroimaging and clinical interviewing of patients with major depression, bipolar disorder, schizophrenia, obsessive-compulsive disorder, and related mental illnesses. Bryce plans to pursue a PhD in Clinical Psychology following his time at McLean.
Research on affective disorders, such as bipolar disorder, and on psychotic disorders is hampered by a lack of basic understanding of the course of dynamic circuit properties that might underlie fluctuations in mood and cognition.Bipolar and psychotic disorders at its core are unstable clinical conditions: at its extremes, it can result in periods of profound changes in mood and cognition (i.e., mania, major depression, and psychosis). And yet, remarkably little has been done to understand the basic mechanisms underlying the fluctuating course common to these individuals. We hope to better understand and characterize the natural course of changes in mood and cognition and associated environmental variables in individuals with severe affective and psychotic disorders using mobile behavioral technology. We believe that this will further enable advances in our understanding of how these disorders develop, paving the way for the development and evaluation of new treatment strategies.
Eric received both his BS in Psychobiology and MD from UCLA. His psychiatry residency and research training were respectively at Yale University School of Medicine and Yale’s Neuroscience Research Training Program. His work has been in applied machine learning with a focus on applying natural language processing to patient interviews for diagnostic support, clinical risk stratification, and identifying predictors in the hopes of improving clinical nosology for personality disorders. Currently, he is on the Deep Phenotyping in Borderline Personality Disorder study. Eric is in VA Boston’s Medical Informatics Fellowship; he splits his time between this lab and the VA’s machine learning group at MAVERIC.
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Michaela is a year 4 PhD student in the Harvard Program in Neuroscience, and previously received an M.Eng and B.S. in Electrical Engineering and Computer Science from MIT. She is investigating machine learning techniques to predict behavior from wrist actigraphy, in particular detecting rituals in OCD. She also works on software development for data cleaning and visualization tools across lab projects.
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Dr. Holstein is a postdoc at the Neurogenomics and Translational Bioinformatics Laboratory (NG-TBL) at McLean Hospital since January 2023. He is interested in the extraction of features from actigraphy data and using psychometrics and biomarkers to predict treatment responses in diverse psychiatric populations.
