Dynamic organization of cerebellar climbing fiber response and synchrony in multiple functional components reduces dimensions for reinforcement learning

Author:

Hoang Huu1ORCID,Tsutsumi Shinichiro2,Matsuzaki Masanori3ORCID,Kano Masanobu45ORCID,Kawato Mitsuo6,Kitamura Kazuo7ORCID,Toyama Keisuke1

Affiliation:

1. ATR Neural Information Analysis Laboratories

2. RIKEN Center for Brain Science

3. Department of Physiology, The University of Tokyo

4. Department of Neurophysiology, The University of Tokyo

5. International Research Center for Neurointelligence (WPI-IRCN), The University of Tokyo

6. ATR Brain Information Communication Research Laboratory Group

7. Department of Neurophysiology, University of Yamanashi

Abstract

Cerebellar climbing fibers convey diverse signals, but how they are organized in the compartmental structure of the cerebellar cortex during learning remains largely unclear. We analyzed a large amount of coordinate-localized two-photon imaging data from cerebellar Crus II in mice undergoing ‘Go/No-go’ reinforcement learning. Tensor component analysis revealed that a majority of climbing fiber inputs to Purkinje cells were reduced to only four functional components, corresponding to accurate timing control of motor initiation related to a Go cue, cognitive error-based learning, reward processing, and inhibition of erroneous behaviors after a No-go cue. Changes in neural activities during learning of the first two components were correlated with corresponding changes in timing control and error learning across animals, indirectly suggesting causal relationships. Spatial distribution of these components coincided well with boundaries of Aldolase-C/zebrin II expression in Purkinje cells, whereas several components are mixed in single neurons. Synchronization within individual components was bidirectionally regulated according to specific task contexts and learning stages. These findings suggest that, in close collaborations with other brain regions including the inferior olive nucleus, the cerebellum, based on anatomical compartments, reduces dimensions of the learning space by dynamically organizing multiple functional components, a feature that may inspire new-generation AI designs.

Funder

Japan Society for the Promotion of Science

Japan Agency for Medical Research and Development

Japan Science and Technology Agency

Acquisition, Technology & Logistics Agency

Publisher

eLife Sciences Publications, Ltd

Subject

General Immunology and Microbiology,General Biochemistry, Genetics and Molecular Biology,General Medicine,General Neuroscience

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