Task-relevant Feature Processing

Task-Relevant Feature Processing is a cognitive mechanism within the domain of feature-based attention that selectively enhances the neural representation of stimulus features pertinent to the current behavioral goal, thereby distinguishing it from task-irrelevant or distracting feature processing.

433

Publications

43.2K

Citations

1.3K

Authors

511

Institutions

Publications per year

2017–2026

160

Authors

1.3K

  1. SJ
    Steven J. Luck

    University of California, Davis, United States

    6 publications · 614 citations

    6

    h-index

  2. MA
    Mircea Ariel Schoenfeld

    Otto-von-Guericke-Universität Magdeburg, Germany

    6 publications · 466 citations

    6

    h-index

  3. JH
    Jens‐Max Hopf

    Otto-von-Guericke-Universität Magdeburg, Germany

    6 publications · 466 citations

    6

    h-index

  4. ZG
    Zaifeng Gao

    Zhejiang University, China

    5 publications · 200 citations

    5

    h-index

  5. HH
    Hans‐Jochen Heinze

    Otto-von-Guericke-Universität Magdeburg, Germany

    5 publications · 451 citations

    5

    h-index

1–5 of 1.3K

Venues

  1. Journal of Neuroscience

    32 publications · 3.8K citations

    27

    h-index

  2. 19

    h-index

  3. Journal of Cognitive Neuroscience

    20 publications · 672 citations

    16

    h-index

  4. Journal of Vision

    17 publications · 749 citations

    15

    h-index

  5. NeuroImage

    14 publications · 1K citations

    13

    h-index

1–5