Miguel Nicolelis

Miguel Nicolelis, M.D., Ph.D., is the Duke School of Medicine Distinguished Professor of Neuroscience, Duke University Professor of Neurobiology, Biomedical Engineering and Psychology and Neuroscience, and founder of Duke’s Center for Neuroengineering. He is the founder and Scientific Director of the Edmond and Lily Safra International Institute for Neuroscience of Natal.  Dr. Nicolelis is also founder of the Walk Again Project, an international consortium of scientists and engineers, dedicated to the development of an exoskeleton device to assist severely paralyzed patients in regaining full body mobility.

Dr. Nicolelis has dedicated his career to investigate how the brains of freely behaving animals encode sensory and motor information. As a result of his studies, Dr. Nicolelis was first to propose and demonstrate that animals and human subjects can utilize their electrical brain activity to directly control neuroprosthetic devices via brain-machine interfaces (BMI).

Over the past 25 years, Dr. Nicolelis pioneered and perfected the development of a new neurophysiological method, known today as chronic, multi-site, multi-electrode recordings. Using this approach in a variety of animal species, as well as in intra-operative procedures in human patients, Dr. Nicolelis launched a new field of investigation, which aims at measuring the concurrent activity and interactions of large populations of single neurons throughout the brain. Through his work, Dr. Nicolelis has discovered a series of key physiological principles that govern the operation of mammalian brain circuits.

Dr. Nicolelis pioneering BMI studies have become extremely influential since they offer new potential therapies for patients suffering from severe levels of paralysis, Parkinson’s disease, and epilepsy. Today, numerous neuroscience laboratories in the US, Europe, Asia, and Latin America have incorporated Dr. Nicolelis’ experimental paradigm to study a variety of mammalian neuronal systems. His research has influenced basic and applied research in computer science, robotics, and biomedical engineering.