4 papers
Robust Neural Stimulation Response Modeling Through Meta-Learning and Pretraining
Matthew J Bryan, Daniel C Muir, Felix Schwock +2
Objective: Model-based closed-loop neural stimulation holds promise for therapeutic applications ranging from Parkinson's disease to sensory restoration, but deployment has been li…
Supervised Stochastic Gradient Algorithms for Multi-Trial Source Separation
Ronak Mehta, Mateus Piovezan Otto, Noah Stanis +2
We develop a stochastic algorithm for independent component analysis that incorporates multi-trial supervision, which is available in many scientific contexts. The method blends a…
Temporal Basis Function Models for Closed-Loop Neural Stimulation
Matthew J. Bryan, Felix Schwock, Azadeh Yazdan-Shahmorad +1
Closed-loop neural stimulation provides novel therapies for neurological diseases such as Parkinson's disease (PD), but it is not yet clear whether artificial intelligence (AI) tec…
Estimating and Analyzing Neural Information Flow Using Signal Processing on Graphs
Felix Schwock, Julien Bloch, Les Atlas +2
Correlating neural communication in brain networks with behavior and cognition can provide fundamental insights into the functionality of both healthy and diseased brains. We demon…