Adaptive Neural Decoding

Adaptive Neural Decoding is a neural decoding framework that dynamically updates its decoding model parameters in response to changes in neural signal properties or behavioral contexts to maintain accurate interpretation of neural activity over time.

19

Publications

1.8K

Citations

60

Authors

36

Institutions

Publications per year

2017–2026

8

Authors

60

  1. JM
    Jose M. Carmena

    University of California, Berkeley, United States

    3 publications · 399 citations

    3

    h-index

  2. AD
    Adrià de Gispert

    University of Cambridge, United Kingdom

    2 publications · 36 citations

    2

    h-index

  3. BB
    Bill Byrne

    University of Cambridge, United Kingdom

    2 publications · 36 citations

    2

    h-index

  4. KV
    Krishna V. Shenoy

    Stanford University, United States

    2 publications · 223 citations

    2

    h-index

  5. JP
    John P. Donoghue

    Brown University, United States

    2 publications · 45 citations

    2

    h-index

1–5 of 60

Venues

  1. Journal of Neural Engineering

    2 publications · 126 citations

    2

    h-index

  2. Apollo (University of Cambridge)

    Repository · 1 publications · 20 citations

    1

    h-index

  3. Cognitive Neurodynamics

    1 publications · 23 citations

    1

    h-index

  4. Journal of Neuroscience

    1 publications · 50 citations

    1

    h-index

  5. arXiv (Cornell University)

    Repository · 1 publications · 13 citations

    1

    h-index

1–5