Approved research

Unlocking the Clinical Utility of Brain Connectomics via Latent Structure Modeling

Lay summary

The human brain is a network of about 1 quadrillion connections, and some consider it the most complex object in the known universe. Without these connections, we would not be capable of thinking, forming memories, or even breathing. Some of society's most mysterious and burdensome medical conditions, including Alzheimer's disease (AD) and major depressive disorder (MDD), are thought to affect parts of the brain network. In AD, researchers have already measured widespread degeneration of physical connections in the brain. There is some evidence that MDD involves dysfunction of the brain chemical serotonin, but it is still unknown where in the expansive serotonin network this dysfunction occurs, and why serotonin related therapies take so long to produce an effect. With MRI, neuroscientists can measure the connections in the brain to try to understand these medical issues. Investigating the many connections in the brain has been facilitated by advances in computation and refinement of biomedical models. These models can represent connection data in a simpler, more interpretable form where a researcher could, for example, pinpoint a set of connections that differ between groups of patients. In our research, we will use cutting-edge models that exhibit a number of favorable properties. Our research project has ambitious goals. During the first few months, we will process the twenty thousand brain images. The rest of the first year will be spent investigating previously studied topics such as how aging affects brain connections. The second year will focus on how brain connections are associated with mood disorders such as depression, neurodegenerative disease such as Alzheimer's, and variation in cognitive ability. If some findings warrant deeper investigation, we will use our remaining time to ensure our research is as clinically useful as possible. Currently, the only way to achieve a definitive diagnosis of Alzheimer's disease, is by examining the brain after death. Mood disorders are also difficult to diagnose, they can only be identified through psychiatric evaluation. Our research could help develop tools that standardize and expedite diagnosis of these conditions. Additionally, our research could help elucidate how these conditions develop through their impact on brain connections, leading to more targeted and effective treatment.