The following group of researchers (brain NRG) represents the union of computational, cognitive and clinical neuroscience dedicated to the application of neural network theory to understanding the damaged brain. In normal mental function, this theory purports that all behavior and cognitive functions are the result of dynamic interactions among large-scale neural networks. If damaged, the ensuing behavioral deficits represent a combination of the loss of important nodes and the attempt of the networks to recover. Our group's research efforts in computational neuroscience will focus on the development of network models that capture the critical anatomical and physiological properties of the brain. This will determine how structure constraints function and how structure and function interact during recovery from damage. In parallel, we will develop and refine mathematical tools to quantify network dynamics. These tools will be applied to data from intensive neuroimaging studies of the healthy brain in tasks ranging from simple to complex, capturing the range of network dynamics in an individual brain. Similar imaging protocols will be applied to three patient groups - patients with moderate brain damage, severe brain damage leading to the minimally conscious state, and patients with mild cognitive impairment - to determine how dynamical range is affected by particular lesions, how it changes longitudinally, and whether it predicts recovery. The realization of our research vision has exciting theoretical and practical implications by providing a unified framework to understand normal and pathological brain function, and revealing mechanisms that may facilitate network dynamics to improve functional outcome.

Coming soon!