We leverage neuroplasticity, machine learning, and neurotechnology to ask how the brain learns and controls movement, and to develop smart prosthetics and neurotherapies.
Neurophysiologically Informed Brain-Machine Interface Systems
We use brain-machine interfaces as a powerful tool to elucidate the neural basis of skill learning and voluntary motor control.
We integrate across disciplines to develop innovative closed-loop brain-machine interfaces for research and clinical applications.
Latest News and Research Discoveries
Neuroscientists trained neurons that normally process visual input to control a computer-generated tone. Learn more, including Q&A with co-first author... read more →March 13, 2018
New study in mice shows how the brain learns to reproduce patterns of brain activity that lead to reward; provides... read more →March 1, 2018
Neuroscientists have demonstrated the astounding flexibility of the brain by training neurons that normally process input from the eyes to... read more →March 1, 2018
Artificial intelligence and brain–computer interfaces must respect and preserve people’s privacy, identity, agency and equality Consider the following scenario. A... read more →November 8, 2017
Value-based decision-making involves an assessment of the value of items available and the actions required to obtain them. The basal... read more →November 6, 2017
Jose Carmena and Michel Maharbiz receive McKnight Technological Innovations in Neuroscience Award for Neural Dust
Today the McKnight Endowment Fund for Neuroscience announced their selection of three research projects to receive $200,000 in funding, with... read more →July 14, 2017
University of California, Berkeley engineers have built the first dust-sized, wireless sensors that can be implanted in the body, bringing... read more →August 4, 2016