Vladislav Royter
Papers
2
Total Citations
55
H-Index
2
About
Vladislav Royter is a neuroscientist whose research lies at the intersection of brain-computer interfaces, neurofeedback, and motor learning. His most impactful work, "Closed-loop adaptation of neurofeedback based on mental effort facilitates reinforcement learning of brain self-regulation" (2016, 36 citations), introduced a novel framework that dynamically adjusts neurofeedback difficulty based on a user’s mental effort. This closed-loop approach significantly improved how individuals learn to self-regulate their own brain activity, offering a more intuitive and effective training paradigm for both clinical and cognitive enhancement applications. Royter has also made important contributions to understanding hemispheric specialization, as shown in his study on oscillatory entrainment during motor imagery and neurofeedback in right and left handers (2019, 19 citations). By revealing how handedness shapes cortical network dynamics, his work provides critical insights for designing personalized neurofeedback protocols. Through these studies, Royter has advanced the practical use of real-time brain monitoring, demonstrating how adaptive algorithms can accelerate learning and improve outcomes in brain self-regulation.
Research Focus
Key Achievements
Top Papers
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- 2