Conductance-based Models

Conductance-Based Model is a mathematical framework in computational neurobiophysics that describes the electrical dynamics of neurons by modeling ion channel conductances as variable parameters governed by voltage-dependent activation and inactivation kinetics, distinguishing it from simpler models that treat conductance as fixed or current as the primary dynamic variable.

482

Publications

39.7K

Citations

1.2K

Authors

499

Institutions

Publications per year

2017–2026

106

Authors

1.2K

  1. EM
    Eve Marder

    Brandeis University, United States

    22 publications · 3.7K citations

    20

    h-index

  2. RN
    Rishikesh Narayanan

    Indian Institute of Science Bangalore, India

    16 publications · 687 citations

    16

    h-index

  3. AD
    Alain Destexhe

    Centre National de la Recherche Scientifique, France

    17 publications · 1.4K citations

    14

    h-index

  4. AV
    Anton V. Chizhov

    Ioffe Institute, Russia

    10 publications · 320 citations

    10

    h-index

  5. IS
    Idan Segev

    Hebrew University of Jerusalem, Israel

    7 publications · 804 citations

    7

    h-index

1–5 of 1.2K

Venues

  1. Journal of Neurophysiology

    JN · 49 publications · 5.4K citations

    33

    h-index

  2. Journal of Neuroscience

    28 publications · 3.7K citations

    23

    h-index

  3. Neural Computation

    29 publications · 2.9K citations

    22

    h-index

  4. PLoS Computational Biology

    25 publications · 1.7K citations

    21

    h-index

  5. PLoS ONE

    19 publications · 592 citations

    16

    h-index

1–5