Electrophysiological Data Analysis

Electrophysiological Data Analysis is a methodological framework within neural data analysis that specifically involves the processing, interpretation, and modeling of electrical activity recorded directly from neurons or neural populations to infer functional dynamics, connectivity, and coding properties of the nervous system.

981

Publications

76.5K

Citations

4.3K

Authors

1.2K

Institutions

Publications per year

2017–2026

220

Authors

4.3K

  1. TA
    Tadashi Akaike

    Nagoya University, Japan

    7 publications · 490 citations

    7

    h-index

  2. RT
    Robert T. Knight

    University of California, Berkeley, United States

    7 publications · 1.5K citations

    7

    h-index

  3. MR
    Max R. Bennett

    The University of Sydney, Australia

    7 publications · 292 citations

    7

    h-index

  4. MW
    Mark W. Woolrich

    University of Oxford, United Kingdom

    7 publications · 838 citations

    7

    h-index

  5. RO
    Robert Oostenveld

    Radboud University Nijmegen, Netherlands

    6 publications · 13.5K citations

    6

    h-index

1–5 of 4.3K

Venues

  1. Journal of Neuroscience Methods

    32 publications · 2.9K citations

    22

    h-index

  2. NeuroImage

    23 publications · 5.5K citations

    20

    h-index

  3. Brain Research

    22 publications · 728 citations

    18

    h-index

  4. PubMed

    Repository · 29 publications · 3.3K citations

    16

    h-index

  5. The Journal of Physiology

    17 publications · 844 citations

    16

    h-index

1–5