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Motor imagery involves predicting the sensory consequences of the imagined movement

Author

Listed:
  • Konstantina Kilteni

    (Karolinska Institutet)

  • Benjamin Jan Andersson

    (Karolinska Institutet)

  • Christian Houborg

    (Karolinska Institutet)

  • H. Henrik Ehrsson

    (Karolinska Institutet)

Abstract

Research on motor imagery has identified many similarities between imagined and executed actions at the behavioral, physiological and neural levels, thus supporting their “functional equivalence”. In contrast, little is known about their possible “computational equivalence”—specifically, whether the brain’s internal forward models predict the sensory consequences of imagined movements as they do for overt movements. Here, we address this question by assessing whether imagined self-generated touch produces an attenuation of real tactile sensations. Previous studies have shown that self-touch feels less intense compared with touch of external origin because the forward models predict the tactile feedback based on a copy of the motor command. Our results demonstrate that imagined self-touch is attenuated just as real self-touch is and that the imagery-induced attenuation follows the same spatiotemporal principles as does the attenuation elicited by overt movements. We conclude that motor imagery recruits the forward models to predict the sensory consequences of imagined movements.

Suggested Citation

  • Konstantina Kilteni & Benjamin Jan Andersson & Christian Houborg & H. Henrik Ehrsson, 2018. "Motor imagery involves predicting the sensory consequences of the imagined movement," Nature Communications, Nature, vol. 9(1), pages 1-9, December.
  • Handle: RePEc:nat:natcom:v:9:y:2018:i:1:d:10.1038_s41467-018-03989-0
    DOI: 10.1038/s41467-018-03989-0
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    Cited by:

    1. Pauline M. Hilt & Mathilde F. Bertrand & Léonard Féasson & Florent Lebon & France Mourey & Célia Ruffino & Vianney Rozand, 2023. "Motor Imagery Training Is Beneficial for Motor Memory of Upper and Lower Limb Tasks in Very Old Adults," IJERPH, MDPI, vol. 20(4), pages 1-13, February.
    2. Eduardo Quiles & Ferran Suay & Gemma Candela & Nayibe Chio & Manuel Jiménez & Leandro Álvarez-Kurogi, 2020. "Low-Cost Robotic Guide Based on a Motor Imagery Brain–Computer Interface for Arm Assisted Rehabilitation," IJERPH, MDPI, vol. 17(3), pages 1-16, January.

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