Neural State Estimation

Neural State Estimation is a computational framework within neural control systems that infers the latent dynamical state of a neural population from observed neurophysiological signals by combining biophysical modeling with statistical inference techniques.

363

Publications

59K

Citations

940

Authors

448

Institutions

Publications per year

2017–2026

139

Authors

940

  1. ZW
    Zidong Wang

    Brunel University of London, United Kingdom

    24 publications · 2.1K citations

    22

    h-index

  2. JC
    Jinde Cao

    Southeast University, China

    13 publications · 688 citations

    13

    h-index

  3. JH
    Ju H. Park

    Yeungnam University, South Korea

    12 publications · 747 citations

    12

    h-index

  4. FE
    Fuad E. Alsaadi

    King Abdulaziz University, Saudi Arabia

    11 publications · 569 citations

    11

    h-index

  5. HL
    Hongjian Liu

    Anhui Polytechnic University, China

    10 publications · 583 citations

    10

    h-index

1–5 of 940

Venues

  1. Neurocomputing

    58 publications · 24.3K citations

    27

    h-index

  2. Neural Networks

    15 publications · 885 citations

    14

    h-index

  3. NeuroImage

    15 publications · 2K citations

    13

    h-index

  4. 12

    h-index

  5. Neural Computation

    9 publications · 837 citations

    9

    h-index

1–5