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Time-compressed preplay of anticipated events in human primary visual cortex

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  • Matthias Ekman

    (Donders Institute For Brain, Cognition and Behaviour, Radboud University Nijmegen)

  • Peter Kok

    (Donders Institute For Brain, Cognition and Behaviour, Radboud University Nijmegen
    Princeton Neuroscience Institute, Princeton University)

  • Floris P. de Lange

    (Donders Institute For Brain, Cognition and Behaviour, Radboud University Nijmegen)

Abstract

Perception is guided by the anticipation of future events. It has been hypothesized that this process may be implemented by pattern completion in early visual cortex, in which a stimulus sequence is recreated after only a subset of the visual input is provided. Here we test this hypothesis using ultra-fast functional magnetic resonance imaging to measure BOLD activity at precisely defined receptive field locations in visual cortex (V1) of human volunteers. We find that after familiarizing subjects with a spatial sequence, flashing only the starting point of the sequence triggers an activity wave in V1 that resembles the full stimulus sequence. This preplay activity is temporally compressed compared to the actual stimulus sequence and remains present even when attention is diverted from the stimulus sequence. Preplay might therefore constitute an automatic prediction mechanism for temporal sequences in V1.

Suggested Citation

  • Matthias Ekman & Peter Kok & Floris P. de Lange, 2017. "Time-compressed preplay of anticipated events in human primary visual cortex," Nature Communications, Nature, vol. 8(1), pages 1-9, August.
    • Handle: RePEc:nat:natcom:v:8:y:2017:i:1:d:10.1038_ncomms15276
    DOI: 10.1038/ncomms15276
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    Cited by:

    1. Johanna Bergmann & Lucy S. Petro & Clement Abbatecola & Min S. Li & A. Tyler Morgan & Lars Muckli, 2024. "Cortical depth profiles in primary visual cortex for illusory and imaginary experiences," Nature Communications, Nature, vol. 15(1), pages 1-13, December.
    2. Ingmar E. J. Vries & Moritz F. Wurm, 2023. "Predictive neural representations of naturalistic dynamic input," Nature Communications, Nature, vol. 14(1), pages 1-16, December.

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