Supervisor Database Search
Search for supervisors below. You can filter your search using the options and select
multiple fields by holding CTRL (Cmd on Mac) + clicking multiple options in a list.
Full NameDr Claire Gillan
Department:Trinity College Institute of Neuroscience
Organisation:Trinity College Dublin
- neuroscience and mental health
- Public Health
The Gillan Lab at Trinity College Dublin uses cognitive neuroscience to better understand, predict and treat mental health problems, tackling issues that are psychiatric, developmental, neurological and associated with advancing age. We aim to understand mental health problems in terms of their underlying biological mechanisms. While some issues might best understood in terms of clusters or categories, others may reflect dimensions that are observable in the general population. We use cognitive neuroscience to test these opposing possibilities, seeking to empirically validate new and improved mental health phenotypes. The fundamental premise being that any brain health taxonomy should be biologically plausible, that the defining characteristics of a cluster or dimension should relatively homogenous and discrete. We believe that reforming nosology in this way is essential for identifying robust biomarkers, reliable genetic associations and appropriate animal models of mental health problems.
Read a write-up about our work in this area in Scientific American: https://medium.com/health-and-disease/taking-mental-health-research-to-a-new-dimension-c9ed58f059bf#.z2b6iay29
A key goal of the Gillan lab is to identify neural and cognitive biomarkers of brain health problems that can be used to predict who will get sick in the future. The hope is that by identifying risk factors, we can intervene earlier, prevent progression to disease or at least keep people healthy for longer. The lab recently received funding to pursue this question in the area of Alzheimer’s Disease detection and we are simultaneously applying this method to track disorders of mental health longitudinally. This project uses a smartphone application to engage brain science volunteers from all over the world in our research – thanks to their commitment, we are working to leverage moment by moment smartphone data with state-of-the-art 'gamified' cognitive tests to train algorithms to detect individuals who are most at risk for Alzheimer’s Disease. We believe that developing scalable detection tools is crucial for supporting intervention-based research to tackle the rise of dementia and mental health problems worldwide.
A second key strand of research is concerned with improving treatment allocation in mental health. However good our treatments are, be they pharmacological or behavioural, they can only be as effective as the precision with which we can administer them. A key challenge in treating mental health problems is that treatment response is heterogeneous; we typically do not know which individual will respond to which medicine or behavioural therapy. A key goal of the Gillan Lab is to identify cognitive and neural markers of treatment response using baseline measurements in prospective studies. Ongoing work in this area aims to predict individual responses to cognitive behavioural therapy (CBT) for OCD in collaboration with researchers at Columbia University. More recently, the lab has received funding from MQ to study antidepressant response using an innovative web-based methodology. Read about this project in the Guardian: https://www.theguardian.com/society/2017/dec/25/online-test-aims-to-predict-best-antidepressants-for-individual-patients
Other work in the lab concerns the smaller scale study of brain mechanisms that give rise to obsessive-compulsive disorder and other disorders of compulsion. In particular, we have published a lot in the area of habit formation - check out the lab website for further information: www.gillanlab.com
The lab particularly welcomes applications from students interested in what 'big data' can do for disorders of brain health. There are opportunities to collect new data, either in-person or via a smartphone app, in addition to taking on sophisticated data analytic projects with pre-existing data.