<p>Closed-loop neural systems often need to learn an encoding model adaptively and in real time. The encoding model describes the relationship between neural recordings and the brain state. For example, the relevant brain state in motor BMIs is the intended velocity and in DBS systems is the disease state, e.g., in Parkinson’s disease. The neural system uses the learned encoding model to decode the brain state. This decoded brain state is then used, for example, to move a prosthetic in motor BMIs while providing visual feedback to the subject, or to control the stimulation pattern applied to the brain in DBS systems. A critical parameter for any adaptive learning algorithm is the learning rate, which dictates how fast the encoding model par...
Abstract—The vision behind our project is a closed-loop system for continuous deep brain stimulation...
Brain-machine interfaces (BMIs) are an emerging field of research that seeks to interface the brain ...
Brain-machine interface (BMI) systems give users direct neural control of robotic, communication, or...
Closed-loop neurotechnologies often need to adaptively learn an encoding model that relates the neur...
in the statistical properties of neural signals recorded at the brain-machine interface (BMI) pose s...
Brain-machine interfaces (BMIs) aim to assist patients suffering from neurological injuries and dise...
The brain has an incredible capacity to learn how to control various effectors, ranging from those e...
Brain-machine interface (BMI) systems show great promise for restoring motor function to patients wi...
Recent physiological measurements have provided clear evidence about scale-free avalanche brain acti...
Precision adaptive control has been accomplished using a neural network to generate the required sys...
The closed-loop operation of brain-machine interfaces (BMI) provides a context to discover foundatio...
Brain-machine interfaces (BMIs) promise to improve the quality of life of patients suffering from se...
Thesis (Ph.D.)--University of Washington, 2017-06The spiking activity of neurons encodes information...
Adaptive Model Theory (AMT) proposes that the brain forms and adaptively maintains inverse models of...
SummaryNeuroplasticity may play a critical role in developing robust, naturally controlled neuropros...
Abstract—The vision behind our project is a closed-loop system for continuous deep brain stimulation...
Brain-machine interfaces (BMIs) are an emerging field of research that seeks to interface the brain ...
Brain-machine interface (BMI) systems give users direct neural control of robotic, communication, or...
Closed-loop neurotechnologies often need to adaptively learn an encoding model that relates the neur...
in the statistical properties of neural signals recorded at the brain-machine interface (BMI) pose s...
Brain-machine interfaces (BMIs) aim to assist patients suffering from neurological injuries and dise...
The brain has an incredible capacity to learn how to control various effectors, ranging from those e...
Brain-machine interface (BMI) systems show great promise for restoring motor function to patients wi...
Recent physiological measurements have provided clear evidence about scale-free avalanche brain acti...
Precision adaptive control has been accomplished using a neural network to generate the required sys...
The closed-loop operation of brain-machine interfaces (BMI) provides a context to discover foundatio...
Brain-machine interfaces (BMIs) promise to improve the quality of life of patients suffering from se...
Thesis (Ph.D.)--University of Washington, 2017-06The spiking activity of neurons encodes information...
Adaptive Model Theory (AMT) proposes that the brain forms and adaptively maintains inverse models of...
SummaryNeuroplasticity may play a critical role in developing robust, naturally controlled neuropros...
Abstract—The vision behind our project is a closed-loop system for continuous deep brain stimulation...
Brain-machine interfaces (BMIs) are an emerging field of research that seeks to interface the brain ...
Brain-machine interface (BMI) systems give users direct neural control of robotic, communication, or...