Andreas Keil
Papers
1
Total Citations
16
H-Index
1
About
Andreas Keil is a leading figure in the integration of neuroimaging modalities, with a primary focus on developing advanced signal-processing techniques for EEG-fMRI fusion. His most cited work, "Functional Source Separation for EEG-fMRI Fusion: Application to Steady-State Visual Evoked Potentials" (2019, 16 citations), introduces a novel method that significantly improves the spatial and temporal resolution of brain activity mapping. This contribution is pivotal for neurorobotics and cognitive neuroscience, as it enables researchers to more precisely link neural dynamics with behavior. Keil’s research bridges the gap between biological neural systems and autonomous systems, offering tools that enhance our understanding of visual processing and brain-computer interfaces. His work is characterized by a rigorous interdisciplinary approach, combining engineering, neuroscience, and robotics. By providing a framework to disentangle overlapping neural sources, Keil has empowered studies on steady-state visual evoked potentials, advancing both fundamental science and applied neurotechnology. His impact is evident in the growing adoption of his source separation methods in labs worldwide, making him a key contributor to the future of brain-inspired autonomous systems.
Research Focus
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Top Papers
- 1