Shape-changing electrode array for minimally invasive large-scale intracranial brain activity mapping

Shiyuan Wei, Anqi Jiang, Hongji Sun, Jingjun Zhu, Shengyi Jia, Xiaojun Liu, Zheng Xu, Jing Zhang, Yuanyuan Shang, Xuefeng Fu, Gen Li, Puxin Wang, Zhiyuan Xia, Tianzi Jiang, Anyuan Cao and Xiaojie Duan ()
Additional contact information
Shiyuan Wei: Peking University
Anqi Jiang: Peking University
Hongji Sun: Peking University
Jingjun Zhu: Peking University
Shengyi Jia: Peking University
Xiaojun Liu: Peking University
Zheng Xu: Peking University
Jing Zhang: Peking University
Yuanyuan Shang: Zhengzhou University
Xuefeng Fu: Peking University
Gen Li: Peking University
Puxin Wang: Peking University
Zhiyuan Xia: Peking University
Tianzi Jiang: Chinese Academy of Sciences (CAS)
Anyuan Cao: Peking University
Xiaojie Duan: Peking University

Nature Communications, 2024, vol. 15, issue 1, 1-16

Abstract: Abstract Large-scale brain activity mapping is important for understanding the neural basis of behaviour. Electrocorticograms (ECoGs) have high spatiotemporal resolution, bandwidth, and signal quality. However, the invasiveness and surgical risks of electrode array implantation limit its application scope. We developed an ultrathin, flexible shape-changing electrode array (SCEA) for large-scale ECoG mapping with minimal invasiveness. SCEAs were inserted into cortical surfaces in compressed states through small openings in the skull or dura and fully expanded to cover large cortical areas. MRI and histological studies on rats proved the minimal invasiveness of the implantation process and the high chronic biocompatibility of the SCEAs. High-quality micro-ECoG activities mapped with SCEAs from male rodent brains during seizures and canine brains during the emergence period revealed the spatiotemporal organization of different brain states with resolution and bandwidth that cannot be achieved using existing noninvasive techniques. The biocompatibility and ability to map large-scale physiological and pathological cortical activities with high spatiotemporal resolution, bandwidth, and signal quality in a minimally invasive manner offer SCEAs as a superior tool for applications ranging from fundamental brain research to brain-machine interfaces.

Date: 2024
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Citations: View citations in EconPapers (2)

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DOI: 10.1038/s41467-024-44805-2

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