Adaptive Neural Interfaces

Adaptive Neural Interface is a neural interface that dynamically modifies its decoding, encoding, or stimulation strategies based on real-time changes in neural signals or user behavior to maintain or improve performance in closed-loop neural systems.

28

Publications

2.1K

Citations

129

Authors

46

Institutions

Publications per year

2017–2026

10

Variants

Adaptive Neural Interface

Authors

129

  1. JM
    Jose M. Carmena

    University of California, Berkeley, United States

    5 publications · 401 citations

    5

    h-index

  2. AL
    Amy L. Orsborn

    University of California, Berkeley, United States

    3 publications · 173 citations

    3

    h-index

  3. SG
    Suraj Gowda

    University of California, Berkeley, United States

    3 publications · 109 citations

    3

    h-index

  4. SD
    Siddharth Dangi

    University of California, Berkeley, United States

    3 publications · 187 citations

    3

    h-index

  5. HG
    Helene G. Moorman

    University of California, Berkeley, United States

    3 publications · 173 citations

    3

    h-index

1–5 of 129

Venues

  1. Frontiers in Neurorobotics

    2 publications · 92 citations

    2

    h-index

  2. Neural Networks

    2 publications · 90 citations

    2

    h-index

  3. IEEE Transactions on Biomedical Engineering

    2 publications · 355 citations

    2

    h-index

  4. Neural Computation

    2 publications · 148 citations

    2

    h-index

  5. International Conference on Human-Computer Interaction

    Conference · 1 publications · 46 citations

    1

    h-index

1–5