Soft Neural Interfaces

Soft Neural Interfaces is a class of neural interface technologies that, as distinguished from rigid conventional probes, are engineered from compliant materials and structures to mechanically and functionally emulate soft neural tissues, thereby minimizing biological response and enabling stable, long-term bidirectional communication with the peripheral nervous system.

62

Publications

5.2K

Citations

475

Authors

164

Institutions

Publications per year

2017–2026

41

Authors

475

  1. WV
    Walter Voit

    The University of Texas at Dallas, United States

    6 publications · 524 citations

    6

    h-index

  2. XT
    Xinyan Tracy Cui

    University of Pittsburgh, United States

    4 publications · 237 citations

    4

    h-index

  3. TD
    Takashi D.Y. Kozai

    University of Pittsburgh, United States

    4 publications · 257 citations

    4

    h-index

  4. ST
    Shoji Takeuchi

    The University of Tokyo, Japan

    3 publications · 417 citations

    3

    h-index

  5. SP
    Stéphanie P. Lacour

    École Polytechnique Fédérale de Lausanne, Switzerland

    3 publications · 213 citations

    3

    h-index

1–5 of 475

Venues

  1. Journal of Neural Engineering

    4 publications · 164 citations

    4

    h-index

  2. Nature Communications

    3 publications · 1.3K citations

    3

    h-index

  3. Journal of Neuroscience Methods

    2 publications · 59 citations

    2

    h-index

  4. MRS Bulletin

    2 publications · 82 citations

    2

    h-index

  5. ACS Applied Materials & Interfaces

    2 publications · 79 citations

    2

    h-index

1–5