Principal Investigator: Dr Robert Constable
Yale University, USATags: 49636, biomarkers, connectome predictive modelling, functional connectivity, Machine Learning, MRI, neuroimaging
The brain is the least understood organ in the body. Much about its function, and its relation to people’s behavior and wellness, is still a mystery. Often mental and psychiatric illnesses are diagnosed in relation to symptoms rather than root causes. This makes effective treatment difficult, and preventative care near impossible.
Recent times have seen a move toward more objective measures relating these illnesses to brain images. One way to do this is to use magnetic resonance imaging. This technology gives us the ability to measure brain structures, to measure brain function, and to detect diffusion of water throughout the brain, using objective, reproducible methodologies. This opens the door to creating a biological test for a mental illness, for example depression, as opposed to having to ask a person how they are feeling, how they are functioning, which can be inaccurate or misleading and depends on the individual and their physician. This is, in essence, our aim. The biobank dataset gives us access to a massive dataset, in terms of neuroimaging, that will allow us to investigate these relationships.
Over the next five years we hope to process the data, derive neural measures from the images, and create classifications of individuals based on their brain structure and function using state of the art machine learning methods. We hope to advance the field of biological psychiatry, and in the short term provide the brain derived measures openly to our field, along with the code used in the analysis.