Population Decoding

Population Decoding is a neural decoding method that infers external stimuli or behavioral variables from the collective activity patterns of a population of neurons, distinguishing itself from single-unit approaches by leveraging distributed representational codes across multiple simultaneously recorded neural signals.

91

Publications

8.7K

Citations

275

Authors

160

Institutions

Publications per year

2017–2026

29

Authors

275

  1. TJ
    Terrence J. Sejnowski

    Salk Institute for Biological Studies, United States

    4 publications · 228 citations

    4

    h-index

  2. ZC
    Zhe Chen

    New York University, United States

    4 publications · 204 citations

    4

    h-index

  3. MB
    Matthias Bethge

    University of Tübingen, Germany

    4 publications · 384 citations

    4

    h-index

  4. EM
    Ethan M. Meyers

    Massachusetts Institute of Technology, United States

    3 publications · 661 citations

    3

    h-index

  5. SG
    Stephen G. Lisberger

    W. M. Keck Foundation, United States

    3 publications · 91 citations

    3

    h-index

1–5 of 275

Venues

  1. Neural Computation

    12 publications · 830 citations

    12

    h-index

  2. Journal of Neuroscience

    9 publications · 1.2K citations

    9

    h-index

  3. Nature Neuroscience

    8 publications · 2.1K citations

    8

    h-index

  4. Journal of Computational Neuroscience

    6 publications · 163 citations

    6

    h-index

  5. Neuron

    6 publications · 583 citations

    6

    h-index

1–5