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Cerebellar-driven cortical dynamics can enable task acquisition, switching and consolidation

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  • Joseph Pemberton

    (University of Bristol
    University of Oxford
    University of Washington)

  • Paul Chadderton

    (University of Bristol)

  • Rui Ponte Costa

    (University of Bristol
    University of Oxford)

Abstract

The brain must maintain a stable world model while rapidly adapting to the environment, but the underlying mechanisms are not known. Here, we posit that cortico-cerebellar loops play a key role in this process. We introduce a computational model of cerebellar networks that learn to drive cortical networks with task-outcome predictions. First, using sensorimotor tasks, we show that cerebellar feedback in the presence of stable cortical networks is sufficient for rapid task acquisition and switching. Next, we demonstrate that, when trained in working memory tasks, the cerebellum can also underlie the maintenance of cognitive-specific dynamics in the cortex, explaining a range of optogenetic and behavioural observations. Finally, using our model, we introduce a systems consolidation theory in which task information is gradually transferred from the cerebellum to the cortex. In summary, our findings suggest that cortico-cerebellar loops are an important component of task acquisition, switching, and consolidation in the brain.

Suggested Citation

  • Joseph Pemberton & Paul Chadderton & Rui Ponte Costa, 2024. "Cerebellar-driven cortical dynamics can enable task acquisition, switching and consolidation," Nature Communications, Nature, vol. 15(1), pages 1-19, December.
  • Handle: RePEc:nat:natcom:v:15:y:2024:i:1:d:10.1038_s41467-024-55315-6
    DOI: 10.1038/s41467-024-55315-6
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    References listed on IDEAS

    as
    1. Zengcai V. Guo & Hidehiko K. Inagaki & Kayvon Daie & Shaul Druckmann & Charles R. Gerfen & Karel Svoboda, 2017. "Maintenance of persistent activity in a frontal thalamocortical loop," Nature, Nature, vol. 545(7653), pages 181-186, May.
    2. Zhenyu Gao & Courtney Davis & Alyse M. Thomas & Michael N. Economo & Amada M. Abrego & Karel Svoboda & Chris I. Zeeuw & Nuo Li, 2018. "A cortico-cerebellar loop for motor planning," Nature, Nature, vol. 563(7729), pages 113-116, November.
    3. Barbara Feulner & Matthew G. Perich & Raeed H. Chowdhury & Lee E. Miller & Juan A. Gallego & Claudia Clopath, 2022. "Small, correlated changes in synaptic connectivity may facilitate rapid motor learning," Nature Communications, Nature, vol. 13(1), pages 1-14, December.
    4. Abhishek Banerjee & Giuseppe Parente & Jasper Teutsch & Christopher Lewis & Fabian F. Voigt & Fritjof Helmchen, 2020. "Value-guided remapping of sensory cortex by lateral orbitofrontal cortex," Nature, Nature, vol. 585(7824), pages 245-250, September.
    5. Ellen Boven & Joseph Pemberton & Paul Chadderton & Richard Apps & Rui Ponte Costa, 2023. "Cerebro-cerebellar networks facilitate learning through feedback decoupling," Nature Communications, Nature, vol. 14(1), pages 1-18, December.
    6. Ben Deverett & Mikhail Kislin & David W. Tank & Samuel S.-H. Wang, 2019. "Cerebellar disruption impairs working memory during evidence accumulation," Nature Communications, Nature, vol. 10(1), pages 1-7, December.
    7. N. Alex Cayco-Gajic & Claudia Clopath & R. Angus Silver, 2017. "Sparse synaptic connectivity is required for decorrelation and pattern separation in feedforward networks," Nature Communications, Nature, vol. 8(1), pages 1-11, December.
    8. James B. Heald & Máté Lengyel & Daniel M. Wolpert, 2021. "Contextual inference underlies the learning of sensorimotor repertoires," Nature, Nature, vol. 600(7889), pages 489-493, December.
    9. Guillaume Bellec & Franz Scherr & Anand Subramoney & Elias Hajek & Darjan Salaj & Robert Legenstein & Wolfgang Maass, 2020. "A solution to the learning dilemma for recurrent networks of spiking neurons," Nature Communications, Nature, vol. 11(1), pages 1-15, December.
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