Sonia Todorova
Papers
1
Total Citations
122
H-Index
1
About
Sonia Todorova is a leading researcher in neural engineering and brain-computer interfaces (BCIs), with a focus on improving the practical viability of neural decoding systems. Her most influential work, "To sort or not to sort: the impact of spike-sorting on neural decoding performance" (2014, 122 citations), challenges a long-standing assumption in the field by demonstrating that spike-sorting—a computationally intensive preprocessing step—may not be necessary for effective BCI performance. This finding has significant implications for the development of more efficient, real-time neural prosthetics, potentially reducing the computational burden and shortening the calibration time required for clinical BCI systems. Todorova’s research bridges fundamental neuroscience and translational engineering, aiming to restore motor function to paralyzed patients through spiking-based BCIs that have already shown promise in controlling multi-degree-of-freedom robotic devices. Her work is widely cited by both experimental and computational neuroscientists, and she is recognized for her rigorous, data-driven approach to optimizing neural signal processing. Todorova continues to explore how to streamline BCI technologies for broader clinical adoption, making her a key figure in the quest for practical, high-performance neural interfaces.
Research Focus
Key Achievements
Top Papers
- 1