Zixuan Wei
Papers
2
Total Citations
21
H-Index
2
About
Zixuan Wei is a neuroscientist and brain-machine interface (BMI) researcher whose work focuses on decoding complex hand movements from intracranial neural signals. Their primary research area lies at the intersection of motor neuroscience and neuroengineering, specifically targeting the posterior parietal cortex (PPC) as a rich source of movement-related information. Wei’s major contribution is demonstrating that stereo-electroencephalography (SEEG) signals recorded from the PPC can significantly enhance gesture decoding performance compared to traditional motor cortex approaches. Their seminal 2020 study, which has garnered 19 citations, showed that PPC signals provide more robust and discriminative neural features for classifying individual finger movements and hand gestures, offering a promising alternative pathway for controlling robotic prosthetics. This work addresses a critical challenge in clinical BMI: achieving fine, intuitive control for severely paralyzed individuals. By systematically comparing decoding accuracy across cortical regions, Wei has helped shift the field’s focus toward higher-order motor planning areas. Their research has direct implications for developing next-generation neural prosthetics that can restore functional independence, making their contributions both scientifically rigorous and deeply translational.
Research Focus
Key Achievements
Top Papers
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- 2