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Mid-lateral cerebellar complex spikes encode multiple independent reward-related signals during reinforcement learning

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  • Naveen Sendhilnathan

    (Columbia University
    Columbia University
    Mahoney Center for Brain and Behavior Research, Columbia University
    Zuckerman Mind, Brain, and Behavior Institute, Columbia University)

  • Anna Ipata

    (Columbia University
    Mahoney Center for Brain and Behavior Research, Columbia University
    Zuckerman Mind, Brain, and Behavior Institute, Columbia University
    New York State Psychiatric Institute)

  • Michael E. Goldberg

    (Columbia University
    Mahoney Center for Brain and Behavior Research, Columbia University
    Zuckerman Mind, Brain, and Behavior Institute, Columbia University
    New York State Psychiatric Institute)

Abstract

Although the cerebellum has been implicated in simple reward-based learning recently, the role of complex spikes (CS) and simple spikes (SS), their interaction and their relationship to complex reinforcement learning and decision making is still unclear. Here we show that in a context where a non-human primate learned to make novel visuomotor associations, classifying CS responses based on their SS properties revealed distinct cell-type specific encoding of the probability of failure after the stimulus onset and the non-human primate’s decision. In a different context, CS from the same cerebellar area also responded in a cell-type and learning independent manner to the stimulus that signaled the beginning of the trial. Both types of CS signals were independent of changes in any motor kinematics and were unlikely to instruct the concurrent SS activity through an error based mechanism, suggesting the presence of context dependent, flexible, multiple independent channels of neural encoding by CS and SS. This diversity in neural information encoding in the mid-lateral cerebellum, depending on the context and learning state, is well suited to promote exploration and acquisition of wide range of cognitive behaviors that entail flexible stimulus-action-reward relationships but not necessarily motor learning.

Suggested Citation

  • Naveen Sendhilnathan & Anna Ipata & Michael E. Goldberg, 2021. "Mid-lateral cerebellar complex spikes encode multiple independent reward-related signals during reinforcement learning," Nature Communications, Nature, vol. 12(1), pages 1-10, December.
  • Handle: RePEc:nat:natcom:v:12:y:2021:i:1:d:10.1038_s41467-021-26338-0
    DOI: 10.1038/s41467-021-26338-0
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    References listed on IDEAS

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    1. Mark J. Wagner & Tony Hyun Kim & Joan Savall & Mark J. Schnitzer & Liqun Luo, 2017. "Cerebellar granule cells encode the expectation of reward," Nature, Nature, vol. 544(7648), pages 96-100, April.
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    4. Ming Ma & Gregory L. Futia & Fabio M. Simoes de Souza & Baris N. Ozbay & Isabel Llano & Emily A. Gibson & Diego Restrepo, 2020. "Molecular layer interneurons in the cerebellum encode for valence in associative learning," Nature Communications, Nature, vol. 11(1), pages 1-16, December.
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    1. Naveen Sendhilnathan & Andreea C. Bostan & Peter L. Strick & Michael E. Goldberg, 2024. "A cerebro-cerebellar network for learning visuomotor associations," Nature Communications, Nature, vol. 15(1), pages 1-14, December.

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