Neuronal Input Integration

Neuronal Input Integration is a theoretical construct in neuroscience that characterizes the process by which a single neuron combines multiple synaptic inputs—both excitatory and inhibitory—across spatial and temporal domains to determine the likelihood of action potential generation.

82

Publications

9.5K

Citations

282

Authors

133

Institutions

Publications per year

2017–2026

18

Authors

282

  1. RY
    Rafael Yuste

    Columbia University, United States

    3 publications · 1.2K citations

    3

    h-index

  2. BD
    Brett D. Mensh

    Janelia Research Campus, United States

    3 publications · 326 citations

    3

    h-index

  3. DC
    Diego Contreras

    University of Pennsylvania, United States

    3 publications · 250 citations

    3

    h-index

  4. WL
    William L. Kath

    Northwestern University, United States

    2 publications · 182 citations

    2

    h-index

  5. GF
    Gidon Felsen

    University of Colorado Denver, United States

    2 publications · 64 citations

    2

    h-index

1–5 of 282

Venues

  1. Neuron

    8 publications · 1.9K citations

    8

    h-index

  2. Journal of Neuroscience

    8 publications · 1.3K citations

    8

    h-index

  3. Journal of Computational Neuroscience

    5 publications · 273 citations

    5

    h-index

  4. Nature Neuroscience

    4 publications · 630 citations

    4

    h-index

  5. PubMed

    Repository · 3 publications · 176 citations

    3

    h-index

1–5