The human brain is a myriad of interconnected pathways and complex dynamical interactions. Modern-day imaging provides an imperfect glimpse into the anatomical and functional organization of the brain. Augmenting the wealth of imaging data are behavioral characteristics and genetic markers. However, fusing information across these different data streams presents a unique set of challenges, which are often ill-suited to current data mining and machine learning techniques.
The Neural Systems Analysis Laboratory (NSA Lab) at Johns Hopkins University focuses on building a comprehensive and system-level understanding of the brain by strategically integrating computational methods, such as network theory, signal processing and probabilistic inference, with application-driven hypotheses about the brain. Our work will yield new insights into debilitating neurological disorders, such as autism, epilepsy and stroke, with the long-term goal of improving patient care.