Visual Contrast Coding

Visual Contrast Coding is a computational framework in retinal neuroscience that characterizes how neurons encode differences in light intensity relative to background levels, distinguishing itself by modeling the transformation of spatial and temporal contrast signals into neural responses through nonlinear gain control mechanisms.

207

Publications

18.5K

Citations

487

Authors

247

Institutions

Publications per year

2017–2026

31

Authors

487

  1. RS
    Robert Shapley

    New York University, United States

    8 publications · 1.3K citations

    8

    h-index

  2. JD
    Jonathan D. Victor

    Cornell University, United States

    8 publications · 1.1K citations

    8

    h-index

  3. DT
    D.J. Tolhurst

    University of Cambridge, United Kingdom

    6 publications · 494 citations

    6

    h-index

  4. HN
    Heiko Neumann

    Universität Ulm, Germany

    5 publications · 96 citations

    5

    h-index

  5. JB
    Jonathan B. Demb

    Yale University, United States

    4 publications · 681 citations

    4

    h-index

1–5 of 487

Venues

  1. Vision Research

    25 publications · 2.6K citations

    20

    h-index

  2. Journal of Neuroscience

    18 publications · 1.4K citations

    16

    h-index

  3. The Journal of Physiology

    13 publications · 900 citations

    13

    h-index

  4. Journal of Neurophysiology

    JN · 13 publications · 1.3K citations

    12

    h-index

  5. Visual Neuroscience

    VMS · 11 publications · 2.7K citations

    11

    h-index

1–5