Effective Connectivity Modeling

Effective Connectivity Modeling is a computational framework that characterizes the causal influence one neural population exerts over another within a neural circuit, distinguishing itself from other connectivity approaches by inferring directional, dynamic interactions based on observed neurophysiological activity.

529

Publications

37K

Citations

2.2K

Authors

878

Institutions

Publications per year

2017–2026

238

Authors

2.2K

  1. KF
    Karl Friston

    University College London, United Kingdom

    64 publications · 8.9K citations

    49

    h-index

  2. AR
    Adeel Razi

    University College London, United Kingdom

    23 publications · 2.9K citations

    20

    h-index

  3. GD
    Gustavo Deco

    Universitat Pompeu Fabra, Spain

    16 publications · 1.4K citations

    16

    h-index

  4. PZ
    Peter Zeidman

    Wellcome Centre for Human Neuroimaging, United Kingdom

    16 publications · 2K citations

    15

    h-index

  5. KΕ
    Klaas Ε. Stephan

    University College London, United Kingdom

    14 publications · 2.1K citations

    14

    h-index

1–5 of 2.2K

Venues

  1. NeuroImage

    87 publications · 9.5K citations

    52

    h-index

  2. Human Brain Mapping

    37 publications · 2.2K citations

    28

    h-index

  3. Journal of Neuroscience

    27 publications · 3.5K citations

    23

    h-index

  4. PLoS ONE

    14 publications · 766 citations

    13

    h-index

  5. Frontiers in Human Neuroscience

    14 publications · 467 citations

    13

    h-index

1–5