脑机接口新突破！科学家研发“动态电极”，可在颅内“游走”

Core Viewpoint - The research team from Shenzhen Institute of Advanced Technology has developed a new type of neural electrode called NeuroWorm, which represents a paradigm shift in brain-machine interface technology by introducing a "dynamic electrode" that can move and adapt within biological tissues, overcoming the limitations of traditional static electrodes [1][5][10]. Group 1: Research and Development - The NeuroWorm is a soft, stretchable neural fiber electrode with a diameter of approximately 196 micrometers, featuring up to 60 independent electrode channels along its length [6][9]. - The development process took over five years and involved collaboration among multiple research teams, including contributions from academicians and researchers from various institutions [4][10]. Group 2: Technical Innovations - The electrode incorporates a small magnetic head at one end, allowing it to autonomously navigate within the body using a high-precision magnetic control system and real-time imaging technology [6][10]. - The research team successfully demonstrated the long-term stability of the NeuroWorm in the muscle of rats for over 43 weeks, showcasing its potential for dynamic monitoring and control [10]. Group 3: Applications and Implications - The NeuroWorm's applications extend beyond brain interfaces to include long-term implantation and stable operation in peripheral muscles, addressing the challenges posed by muscle movement and deformation [9][10]. - This innovation opens new possibilities for exoskeleton control, rehabilitation assistance, and human-machine collaboration in everyday environments [9][10]. Group 4: Industry Impact - The breakthrough in dynamic electrode technology signifies a major advancement in the field of bioelectronics, moving from passive fixed implants to actively controlled, intelligent responses that can work in tandem with biological tissues [10]. - The integration of AI, materials science, electronic engineering, and neuroscience is essential for the future development of brain-machine interface technologies, highlighting the need for interdisciplinary collaboration [10].