Optimization of neuroprosthetic vision via end-to-end deep reinforcement learning

B Küçükoğlu, B Rueckauer, N Ahmad… - … Journal of Neural …, 2022 - World Scientific
Visual neuroprostheses are a promising approach to restore basic sight in visually impaired
people. A major challenge is to condense the sensory information contained in a complex …

Perspectives of implementation of closed-Loop Deep Brain Stimulation: from neurological to Psychiatric disorders

S Groppa, G Gonzalez-Escamilla, G Tinkhauser… - 2023 - karger.com
Background: Deep brain stimulation (DBS) is a highly efficient, evidence-based therapy to
alleviate symptoms and improve quality of life in movement disorders such as ParkinsonLs …

An in-silico framework for modeling optimal control of neural systems

B Rueckauer, M van Gerven - Frontiers in Neuroscience, 2023 - frontiersin.org
Introduction Brain-machine interfaces have reached an unprecedented capacity to measure
and drive activity in the brain, allowing restoration of impaired sensory, cognitive or motor …

Optimal Control of Neural Systems

B Rueckauer, M van Gerven - bioRxiv, 2022 - biorxiv.org
Brain-machine interfaces have reached an unprecedented capacity to measure and drive
activity in the brain, allowing restoration of impaired sensory, cognitive or motor function …

[PDF][PDF] Optimization of Neuroprosthetic Vision via End-to-end Deep Reinforcement Learning

BKB Rueckauer, N Ahmad, JR van Steveninck… - academia.edu
Visual neuroprostheses are a promising approach to restore basic sight in visually impaired
people. A major challenge is to condense the sensory information contained in a complex …

[引用][C] Machine learning methods for motor performance decoding in adaptive deep brain stimulation

S Castaño-Candamil - 2020 - Dissertation, Universität Freiburg …