Synaptic Input Selectivity

Synaptic Input Selectivity is a neurocomputational mechanism that, as a subset of synaptic integration processes, selectively amplifies or attenuates specific incoming neural signals based on their spatial and temporal patterns, thereby enabling neurons to differentially respond to distinct synaptic inputs according to their functional relevance.

169

Publications

15.1K

Citations

538

Authors

233

Institutions

Publications per year

2017–2026

25

Authors

538

  1. BS
    Benjamin Scholl

    Max Planck Florida Institute for Neuroscience, United States

    4 publications · 574 citations

    4

    h-index

  2. SP
    Stefano Panzeri

    Italian Institute of Technology, Italy

    3 publications · 140 citations

    3

    h-index

  3. AN
    Anthony N. Burkitt

    The University of Melbourne, Australia

    3 publications · 138 citations

    3

    h-index

  4. JL
    J. Leo van Hemmen

    Technical University of Munich, Germany

    3 publications · 138 citations

    3

    h-index

  5. MG
    Matthieu Gilson

    Universitat Pompeu Fabra, Spain

    3 publications · 138 citations

    3

    h-index

1–5 of 538

Venues

  1. Journal of Neuroscience

    19 publications · 3.2K citations

    18

    h-index

  2. Journal of Neurophysiology

    JN · 19 publications · 2.6K citations

    17

    h-index

  3. The Journal of Physiology

    20 publications · 1.3K citations

    17

    h-index

  4. European Journal of Neuroscience

    EJN · 8 publications · 630 citations

    8

    h-index

  5. Nature

    7 publications · 1.1K citations

    7

    h-index

1–5