Ring Attractor Models

Ring Attractor Models is a type of continuous attractor neural network architecture characterized by a circular arrangement of recurrently connected neuronal populations that maintain stable, persistent activity patterns representing continuously varying angular or directional variables through localized firing, enabling biologically plausible modeling of head-direction or spatial orientation coding.

32

Publications

2.3K

Citations

90

Authors

55

Institutions

Publications per year

2017–2026

18

Variants

Ring Attractor NetworkRing Attractor Networks

Authors

90

  1. VJ
    Vivek Jayaraman

    Janelia Research Campus, United States

    4 publications · 676 citations

    4

    h-index

  2. RP
    Robert P. Ray

    University of Sussex, United Kingdom

    3 publications · 217 citations

    3

    h-index

  3. KT
    Kristopher T. Jensen

    University of Cambridge, United Kingdom

    3 publications · 217 citations

    3

    h-index

  4. TP
    Tyler Paterson

    Janelia Research Campus, United States

    3 publications · 217 citations

    3

    h-index

  5. DB
    Daniel B. Turner‐Evans

    California Institute of Technology, United States

    3 publications · 217 citations

    3

    h-index

1–5 of 90

Venues

  1. bioRxiv (Cold Spring Harbor Laboratory)

    Repository · 3 publications · 131 citations

    3

    h-index

  2. Neuron

    2 publications · 183 citations

    2

    h-index

  3. eLife

    2 publications · 114 citations

    2

    h-index

  4. Journal of High Energy Physics

    JHEP · 2 publications · 81 citations

    2

    h-index

  5. PLoS Computational Biology

    1 publications · 22 citations

    1

    h-index

1–5