ArticleeLife2023
Dynamic organization of cerebellar climbing fiber response and synchrony in multiple functional components reduces dimensions for reinforcement learning.
Article in eLife, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
11 citing papers in PubMed, 14 citations in OpenAlex.
- Motor priming is associated with widespread recruitment into neural ensembles and more rapid ensemble transitions.iScience · 2026Article
- Article
- Consensus Paper: Models of Cerebellar Functions.Cerebellum (London, England) · 2026Review
- A theory of cerebellar learning as spike-based reinforcement learning in continuous time and space.PNAS nexus · 2025Article
- Homeostatic bidirectional plasticity in upbound and downbound micromodules in a model of the olivocerebellar loop.PLoS computational biology · 2025Article
- Cerebellar circuit computations for predictive motor control.Nature reviews. Neuroscience · 2025Review
- A cerebello-thalamo-cortical pathway transmits reward-based post-error signals for motor timing correction during learning in male mice.Nature communications · 2025Article
- Synergistic Reinforcement Learning by Cooperation of the Cerebellum and Basal Ganglia.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2025Article
- Predictive reward-prediction errors of climbing fiber inputs integrate modular reinforcement learning with supervised learning.PLoS computational biology · 2025Article
- Cerebellar control of targeted tongue movements.The Journal of physiology · 2025Article
- Cerebellar climbing fibers multiplex movement and reward signals during a voluntary movement task in mice.Communications biology · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors at 4 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
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.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.