Danielle Rager, a first-year doctoral student in the CNBC’s Program in Neural Computation, has been awarded a Department of Energy Computational Science Graduate Fellowship (DOE GSGF). The DOE CSGF provides Danielle with four years of graduate funding as well as the opportunity to do a research practicum at a DOE laboratory using a high-performance computing cluster. With this award, Danielle plans to analyze multi-electrode array recordings of neural activity in primary motor and somatosensory cortices and develop large-scale computational models of the sensorimotor system to determine the task-dependent role of proprioception in motor control. The goals of this research are to understand able-bodied reaching and grasping movements and to develop a closed-loop, proprioceptive feedback mechanism for brain-machine-interface users. Danielle is co-advised by Dr. Valérie Ventura of the CMU Statistics Department and Dr. Douglas Weber of the University of Pittsburgh Department of Bioengineering.