Conductance-based Neuron Models

Conductance-Based Neuron Model is a type of mathematical neuron model in computational neuroscience that describes the dynamics of membrane potential by explicitly accounting for the flow of ionic currents through voltage- or ligand-gated conductances, thereby distinguishing it from simpler models that rely on phenomenological or current-based approximations.

379

Publications

27.6K

Citations

902

Authors

390

Institutions

Publications per year

2017–2026

84

Authors

902

  1. EM
    Eve Marder

    Brandeis University, United States

    19 publications · 3.5K citations

    17

    h-index

  2. AD
    Alain Destexhe

    Centre National de la Recherche Scientifique, France

    16 publications · 1.2K citations

    14

    h-index

  3. RN
    Rishikesh Narayanan

    Indian Institute of Science Bangalore, India

    13 publications · 547 citations

    13

    h-index

  4. IS
    Idan Segev

    Hebrew University of Jerusalem, Israel

    8 publications · 913 citations

    8

    h-index

  5. SR
    Sylvie Renaud

    Université de Bordeaux, France

    6 publications · 1.9K citations

    6

    h-index

1–5 of 902

Venues

  1. Journal of Neurophysiology

    JN · 42 publications · 4.9K citations

    30

    h-index

  2. Neural Computation

    28 publications · 2.7K citations

    21

    h-index

  3. Journal of Neuroscience

    18 publications · 2.9K citations

    18

    h-index

  4. PLoS Computational Biology

    15 publications · 1.1K citations

    15

    h-index

  5. PLoS ONE

    16 publications · 478 citations

    14

    h-index

1–5