Mallar Chakravarty’s research group has developed new algorithms to help analyze large quantities of mental-health data, in the hopes of better understanding how the anatomy of the brain changes shape as a result of disorders such as Alzheimer’s. Its goal is to be able to identify new risk genes early, so treatment for high-risk individuals can begin sooner and the disease can be prevented.
The work from our group is focused on understanding how the anatomy of the brain changes shape through the course of neuropsychiatric disorders and how an individual’s specific genetic architecture confers risk for these disorders by compromising brain anatomy. Our goal is to identify individuals at highest risk for specific brain disorders (such as Alzheimer’s disease and schizophrenia) at a stage where complete prevention or limiting disease severity is still possible. Compute Canada infrastructure is used for testing and validating our novel algorithms, and subsequently using them for analysis of large cohorts of subjects. We would simply not be able to keep up with the demands of our research and our collaborations without having access to the Compute Canada infrastructure; this would include the performance of basic imaging processing tasks and analyses on the volume of data with which we work. Our research has been, and will be, presented at international conferences such as the Organization for Human Brain Mapping (Seattle, 2013), Society for Neuroscience (San Diego, 2013), and published in scientific journals such as NeuroImage, Human Brain Mapping and the Journal of Neuroscience. The results of this research have the potential to impact Canadians by: 1. Advancing understanding of structural changes in psychiatric illness and aging; 2. Identifying new risk genes for altered brain structure and their effect on disease progression, and; 3. Aiding in early identification and treatment of individuals at high-risk for developing mental illness.