Connectome-based Modeling

Connectome-Based Modeling is a computational neuroscience framework that uses the brain's empirically derived structural connectivity—the connectome—as the foundational architecture to simulate and predict large-scale neural dynamics, thereby distinguishing it from models based on functional or theoretical connectivity alone.

206

Publications

14.5K

Citations

1.4K

Authors

517

Institutions

Publications per year

2017–2026

167

Authors

1.4K

  1. DS
    Dustin Scheinost

    Yale University, United States

    16 publications · 2.7K citations

    15

    h-index

  2. MD
    Monica D. Rosenberg

    University of Chicago, United States

    15 publications · 3.3K citations

    13

    h-index

  3. VJ
    Viktor Jirsa

    Institut de Neurosciences des Systèmes, France

    14 publications · 1.4K citations

    13

    h-index

  4. RT
    R. Todd Constable

    Yale University, United States

    10 publications · 2.1K citations

    10

    h-index

  5. AR
    Anthony R. McIntosh

    Baycrest Hospital, Canada

    10 publications · 660 citations

    10

    h-index

1–5 of 1.4K

Venues

  1. NeuroImage

    26 publications · 1.9K citations

    22

    h-index

  2. bioRxiv (Cold Spring Harbor Laboratory)

    Repository · 11 publications · 311 citations

    10

    h-index

  3. NeuroImage Clinical

    7 publications · 217 citations

    7

    h-index

  4. Cerebral Cortex

    7 publications · 232 citations

    7

    h-index

  5. Scientific Reports

    7 publications · 786 citations

    7

    h-index

1–5