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Spatiotemporal refinement of signal flow through association cortex during learning

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  • Ariel Gilad

    (University of Zurich
    The Hebrew University)

  • Fritjof Helmchen

    (University of Zurich
    Neuroscience Center Zurich)

Abstract

Association areas in neocortex encode novel stimulus-outcome relationships, but the principles of their engagement during task learning remain elusive. Using chronic wide-field calcium imaging, we reveal two phases of spatiotemporal refinement of layer 2/3 cortical activity in mice learning whisker-based texture discrimination in the dark. Even before mice reach learning threshold, association cortex—including rostro-lateral (RL), posteromedial (PM), and retrosplenial dorsal (RD) areas—is generally suppressed early during trials (between auditory start cue and whisker-texture touch). As learning proceeds, a spatiotemporal activation sequence builds up, spreading from auditory areas to RL immediately before texture touch (whereas PM and RD remain suppressed) and continuing into barrel cortex, which eventually efficiently discriminates between textures. Additional correlation analysis substantiates this diverging learning-related refinement within association cortex. Our results indicate that a pre-learning phase of general suppression in association cortex precedes a learning-related phase of task-specific signal flow enhancement.

Suggested Citation

  • Ariel Gilad & Fritjof Helmchen, 2020. "Spatiotemporal refinement of signal flow through association cortex during learning," Nature Communications, Nature, vol. 11(1), pages 1-14, December.
  • Handle: RePEc:nat:natcom:v:11:y:2020:i:1:d:10.1038_s41467-020-15534-z
    DOI: 10.1038/s41467-020-15534-z
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    Cited by:

    1. Dongsheng Xiao & Brandon J. Forys & Matthieu P. Vanni & Timothy H. Murphy, 2021. "MesoNet allows automated scaling and segmentation of mouse mesoscale cortical maps using machine learning," Nature Communications, Nature, vol. 12(1), pages 1-13, December.

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