Spike Train Coding

Spike Train Coding is a neural coding framework that represents sensory or motor information through the temporal patterns of action potentials in a sequence of discrete spikes over time.

203

Publications

15.9K

Citations

537

Authors

252

Institutions

Publications per year

2017–2026

29

Variants

Spike-train Coding

Authors

537

  1. WB
    William Bialek

    Princeton University, United States

    7 publications · 2K citations

    7

    h-index

  2. MJ
    Maurice J. Chacron

    McGill University, Canada

    6 publications · 390 citations

    6

    h-index

  3. CK
    Christof Koch

    California Institute of Technology, United States

    6 publications · 699 citations

    6

    h-index

  4. FG
    Fabrizio Gabbiani

    Baylor College of Medicine, United States

    5 publications · 440 citations

    5

    h-index

  5. IN
    Ilya Nemenman

    Emory University, United States

    5 publications · 334 citations

    5

    h-index

1–5 of 537

Venues

  1. Journal of Neurophysiology

    JN · 33 publications · 2.9K citations

    24

    h-index

  2. Journal of Neuroscience

    17 publications · 2.2K citations

    16

    h-index

  3. Neural Computation

    10 publications · 1.6K citations

    10

    h-index

  4. Biological Cybernetics

    8 publications · 558 citations

    8

    h-index

  5. Brain Research

    6 publications · 314 citations

    6

    h-index

1–5