Jiaming Li

Beijing University of Technology, Shantou University

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About

Jiaming Li is a researcher at the intersection of cognitive modeling and neurorobotic rehabilitation, whose work bridges fundamental learning theory with practical clinical applications. Their key research areas include neuromodulated plasticity, associative learning models, and brain-computer interface (BCI)-driven rehabilitation systems. Li’s most notable contribution is the development of a unified cognitive model that integrates classical and operant conditioning—a long-standing challenge in computational neuroscience. This model, detailed in their 2016 paper (11 citations), explains how neuromodulatory systems enable flexible, adaptive learning, offering a framework for understanding both biological and artificial intelligence. More recently, Li has pioneered a novel stroke rehabilitation system that incorporates error-related negativity (ERN) signals from the patient’s brain into the control loop, moving beyond conventional fixed-program therapy. Their 2022 proof-of-concept study (3 citations) demonstrates how real-time neural feedback can personalize motor recovery, effectively “closing the loop” between the brain and the robotic system. This work represents a significant step toward patient-centered neurorehabilitation, where the brain’s own error-detection mechanisms guide therapy. Li’s research uniquely combines theoretical depth with translational impact, making them a rising voice in cognitive robotics and assistive technology.