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Ensemble representations reveal distinct neural coding of visual working memory

Author

Listed:
  • Byung-Il Oh

    (Sungkyunkwan University)

  • Yee-Joon Kim

    (Institute for Basic Science (IBS))

  • Min-Suk Kang

    (Sungkyunkwan University
    Institute for Basic Science (IBS))

Abstract

We characterized the population-level neural coding of ensemble representations in visual working memory from human electroencephalography. Ensemble representations provide a unique opportunity to investigate structured representations of working memory because the visual system encodes high-order summary statistics as well as noisy sensory inputs in a hierarchical manner. Here, we consistently observe stable coding of simple features as well as the ensemble mean in frontocentral electrodes, which even correlated with behavioral indices of the ensemble across individuals. In occipitoparietal electrodes, however, we find that remembered features are dynamically coded over time, whereas neural coding of the ensemble mean is absent in the old/new judgment task. In contrast, both dynamic and stable coding are found in the continuous estimation task. Our findings suggest that the prefrontal cortex holds behaviorally relevant abstract representations while visual representations in posterior and visual areas are modulated by the task demands.

Suggested Citation

  • Byung-Il Oh & Yee-Joon Kim & Min-Suk Kang, 2019. "Ensemble representations reveal distinct neural coding of visual working memory," Nature Communications, Nature, vol. 10(1), pages 1-12, December.
  • Handle: RePEc:nat:natcom:v:10:y:2019:i:1:d:10.1038_s41467-019-13592-6
    DOI: 10.1038/s41467-019-13592-6
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    Cited by:

    1. Francesco Ceccarelli & Lorenzo Ferrucci & Fabrizio Londei & Surabhi Ramawat & Emiliano Brunamonti & Aldo Genovesio, 2023. "Static and dynamic coding in distinct cell types during associative learning in the prefrontal cortex," Nature Communications, Nature, vol. 14(1), pages 1-17, December.

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