Claire Gillan brings expertise in computational modeling and large web-based cognitive research to GBHI, where she leverages these techniques to better understand and treat mental health problems in older adults. One of the key challenges in treating mental health problems is the high degree of variability in therapy response. Because it is difficult to determine which individual will respond to which treatment, clinicians must rely on trial and error to find something that works. This lack of precision means that people remain symptomatic for longer than necessary and suffer physical side effects that can be particularly serious in older adults. A key goal of the Gillan lab is to identify cognitive and neural markers of treatment response using baseline measurements in prospective studies. Given the size and scope of the problem worldwide, even a moderate improvement in treatment allocation would have an enormous impact on health services and patient wellbeing. Gillan uses machine learning, computational modeling, brain imaging, and large online studies to achieve these aims.
Before joining GBHI, Gillan earned her doctorate degree at the University of Cambridge where her thesis work focused on delineating the neurocognitive basis of obsessive-compulsive disorder (OCD). Her work has led to a shift in thinking away from the traditional view of OCD as a disorder of anxiety and obsession toward one that centers on compulsivity. She was awarded a Sir Henry Wellcome Postdoctoral Fellowship to work at New York University on computational approaches to understanding psychiatry. There she developed a novel approach to psychiatric research that leverages the efficiencies of large-scale data collection and used this approach to define psychiatric dimensions in a data-driven way, based on their relationship to well-defined neurocognitive processes.
As part of GBHI, Gillan will focus on developing scalable interventions and methods for predicting treatment response and disease course using computational modeling and novel experimentation in large heterogeneous samples.
Bio: Claire Gillan is a cognitive psychologist and assistant professor of psychology at Trinity College Dublin. She received a first-class honors degree in psychology from University College Dublin and a doctorate degree in psychology from the University of Cambridge. In 2015, Gillan was awarded the British Association for Psychopharmacology Junior Investigator Award for her work on goal-directed learning in people with obsessive-compulsive disorder, and in 2017, she was awarded a prestigious fellowship from MQ to use machine learning to identify predictors of antidepressant response in psychiatric disorders.