Information-theoretic Neural Coding

Information-Theoretic Neural Coding is a theoretical framework within neural encoding that employs principles of information theory to quantify and analyze how neurons represent, transmit, and process sensory or cognitive information through patterns of neural activity.

126

Publications

10.1K

Citations

278

Authors

148

Institutions

Publications per year

2017–2026

16

Authors

278

  1. SP
    Stefano Panzeri

    Italian Institute of Technology, Italy

    12 publications · 713 citations

    11

    h-index

  2. WB
    William Bialek

    Princeton University, United States

    7 publications · 1.5K citations

    7

    h-index

  3. ET
    Edmund T. Rolls

    University of Oxford, United Kingdom

    5 publications · 662 citations

    5

    h-index

  4. MP
    Malcolm P. Young

    Newcastle University, United Kingdom

    5 publications · 170 citations

    5

    h-index

  5. JC
    José C. Prı́ncipe

    University of Florida, United States

    5 publications · 226 citations

    5

    h-index

1–5 of 278

Venues

  1. Network Computation in Neural Systems

    17 publications · 701 citations

    15

    h-index

  2. Neural Computation

    10 publications · 835 citations

    10

    h-index

  3. Journal of Neurophysiology

    JN · 6 publications · 936 citations

    6

    h-index

  4. Journal of Neuroscience

    5 publications · 615 citations

    5

    h-index

  5. IEEE Transactions on Information Theory

    4 publications · 90 citations

    4

    h-index

1–5