Spike Train Dynamics

Spike Train Dynamics is a theoretical framework within computational neuroscience that characterizes the temporal evolution and statistical structure of sequences of action potentials generated by neurons, distinguishing itself through the modeling of spiking patterns as dynamic processes governed by intrinsic and extrinsic neural mechanisms.

1K

Publications

71.1K

Citations

2.6K

Authors

874

Institutions

Publications per year

2017–2026

160

Variants

Spike-train Dynamics

Authors

2.6K

  1. WG
    Wulfram Gerstner

    École Polytechnique Fédérale de Lausanne, Switzerland

    14 publications · 2.1K citations

    14

    h-index

  2. MJ
    Michael J. Ward

    University of British Columbia, Canada

    9 publications · 568 citations

    9

    h-index

  3. BL
    Benjamin Lindner

    Bernstein Center for Computational Neuroscience Berlin, Germany

    9 publications · 773 citations

    9

    h-index

  4. EN
    Emery N. Brown

    Massachusetts General Hospital, United States

    9 publications · 868 citations

    9

    h-index

  5. AA
    Ad Aertsen

    University of Freiburg, Germany

    9 publications · 1.6K citations

    9

    h-index

1–5 of 2.6K

Venues

  1. Journal of Neurophysiology

    JN · 79 publications · 8.8K citations

    44

    h-index

  2. Journal of Neuroscience

    52 publications · 5.2K citations

    38

    h-index

  3. Neural Computation

    40 publications · 4K citations

    30

    h-index

  4. Journal of Neuroscience Methods

    39 publications · 2.1K citations

    25

    h-index

  5. Biological Cybernetics

    47 publications · 2.2K citations

    25

    h-index

1–5