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Silk-enabled conformal intraventricular interfaces for minimally invasive neural recordings

Author

Listed:
  • Jizhi Liang

    (Chinese Academy of Sciences
    University of Chinese Academy of Sciences)

  • Xiner Wang

    (Chinese Academy of Sciences
    University of Chinese Academy of Sciences)

  • Zhaohan Chen

    (Ltd)

  • Xiaoling Wei

    (University of Chinese Academy of Sciences
    Chinese Academy of Sciences)

  • Liuyang Sun

    (Chinese Academy of Sciences
    University of Chinese Academy of Sciences)

  • Keyin Liu

    (University of Chinese Academy of Sciences
    Chinese Academy of Sciences)

  • Zhifeng Shi

    (Huashan Hospital of Fudan University)

  • Tiger H. Tao

    (Chinese Academy of Sciences
    University of Chinese Academy of Sciences
    Ltd
    Chinese Academy of Sciences)

  • Zhitao Zhou

    (University of Chinese Academy of Sciences
    Chinese Academy of Sciences)

Abstract

Flexible neural interfaces capable of monitoring subcortical neuronal activity facilitate the study of deep brain neural circuits and their interactions with the cortex. However, there exists a paucity of translational tools for interfacing subcortical nuclei surfaces within the intraventricular cerebrospinal fluid. Here, we developed a flexible and conformal intraventricular interface (IVI) featuring a deformable microelectrode array paired with a silk scaffold. The IVI can be minimally invasively implanted into the lateral ventricles with the assistance of commonly used clinical catheters, self-unfolding in the cerebrospinal fluid environment to conformally attach to the surfaces of periventricular neural structures, and capturing high-quality signals by virtue of the microelectrode’s in-plane shielding. In parkinsonian ewes, the IVI detects deep brain abnormalities and achieves stable, biocompatible in vivo recordings for four weeks. This platform enables chronic monitoring and circuit analysis of healthy and diseased deep brain regions, facilitating studies of neural circuits between periventricular surface neurons and distant brain areas.

Suggested Citation

  • Jizhi Liang & Xiner Wang & Zhaohan Chen & Xiaoling Wei & Liuyang Sun & Keyin Liu & Zhifeng Shi & Tiger H. Tao & Zhitao Zhou, 2025. "Silk-enabled conformal intraventricular interfaces for minimally invasive neural recordings," Nature Communications, Nature, vol. 16(1), pages 1-14, December.
  • Handle: RePEc:nat:natcom:v:16:y:2025:i:1:d:10.1038_s41467-025-64397-9
    DOI: 10.1038/s41467-025-64397-9
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