Neural Data Analysis

Neural Data Analysis is a methodological subfield of computational neuroscience and neural engineering that develops and applies quantitative, statistical, and computational techniques to extract, model, and interpret information from experimentally or clinically acquired neural signals.

5K

Publications

475.8K

Citations

17.9K

Authors

3.6K

Institutions

Publications per year

2017–2026

2.4K

Authors

17.9K

  1. VD
    Vince D. Calhoun

    Mind Research Network, United States

    135 publications · 11.7K citations

    51

    h-index

  2. SM
    Stephen M. Smith

    University of Oxford, United Kingdom

    34 publications · 18.3K citations

    30

    h-index

  3. RA
    Russell A. Poldrack

    Stanford University, United States

    39 publications · 13.6K citations

    28

    h-index

  4. AG
    Alexandre Gramfort

    Commissariat à l'Énergie Atomique et aux Énergies Alternatives, France

    28 publications · 11K citations

    24

    h-index

  5. KF
    Karl Friston

    University College London, United Kingdom

    31 publications · 15.8K citations

    24

    h-index

1–5 of 17.9K

Venues

  1. NeuroImage

    471 publications · 74.5K citations

    121

    h-index

  2. Human Brain Mapping

    164 publications · 31.6K citations

    66

    h-index

  3. Journal of Neuroscience Methods

    161 publications · 45.4K citations

    50

    h-index

  4. Frontiers in Neuroinformatics

    113 publications · 16.9K citations

    47

    h-index

  5. Frontiers in Neuroscience

    123 publications · 13.5K citations

    45

    h-index

1–5