Neural Decoding Algorithms

Neural Decoding Algorithms is a class of computational methods in neuroscience that belong to the broader category of neural signal processing techniques, specifically designed to infer intended motor, sensory, or cognitive states from recorded neural activity patterns by modeling the relationship between neural firing and external variables.

270

Publications

16.9K

Citations

955

Authors

398

Institutions

Publications per year

2017–2026

146

Authors

955

  1. KV
    Krishna V. Shenoy

    Stanford University, United States

    9 publications · 778 citations

    10

    h-index

  2. VG
    Vikash Gilja

    Stanford University, United States

    6 publications · 413 citations

    6

    h-index

  3. SI
    Stephen I. Ryu

    Stanford University, United States

    6 publications · 549 citations

    6

    h-index

  4. JP
    John P. Donoghue

    Brown University, United States

    5 publications · 320 citations

    5

    h-index

  5. JL
    José L. Contreras-Vidal

    University of Houston, United States

    5 publications · 398 citations

    5

    h-index

1–5 of 955

Venues

  1. Journal of Neural Engineering

    21 publications · 1K citations

    17

    h-index

  2. NeuroImage

    15 publications · 801 citations

    12

    h-index

  3. Neural Computation

    11 publications · 822 citations

    11

    h-index

  4. bioRxiv (Cold Spring Harbor Laboratory)

    Repository · 7 publications · 152 citations

    8

    h-index

  5. Journal of Neurophysiology

    JN · 8 publications · 1.2K citations

    8

    h-index

1–5