Literature DB >> 30790636

The super-learning hypothesis: Integrating learning processes across cortex, cerebellum and basal ganglia.

Daniele Caligiore1, Michael A Arbib2, R Chris Miall3, Gianluca Baldassarre4.   

Abstract

Despite wide evidence suggesting anatomical and functional interactions between cortex, cerebellum and basal ganglia, the learning processes operating within them --often viewed as respectively unsupervised, supervised and reinforcement learning-- are studied in isolation, neglecting their strong interdependence. We discuss how those brain areas form a highly integrated system combining different learning mechanisms into an effective super-learning process supporting the acquisition of flexible motor behaviour. The term "super-learning" does not indicate a new learning paradigm. Rather, it refers to the fact that different learning mechanisms act in synergy as they: (a) affect neural structures often relying on the widespread action of neuromodulators; (b) act within various stages of cortical/subcortical pathways that are organised in pipeline to support multiple sensation-to-action mappings operating at different levels of abstraction; (c) interact through the reciprocal influence of the output compartments of different brain structures, most notably in the cerebello-cortical and basal ganglia-cortical loops. Here we articulate this new hypothesis and discuss empirical evidence supporting it by specifically referring to motor adaptation and sequence learning.
Copyright © 2019 The Authors. Published by Elsevier Ltd.. All rights reserved.

Keywords:  Acetylcholine; Basal ganglia; Cerebellum; Cortex; Cortical-subcortical hierarchies; Dopamine; Interplay between learning mechanisms; Neuromodulation; Noradrenaline; Reinforcement learning; Serotonin; Super-learning; Supervised learning; System-level neuroscience; Unsupervised learning

Mesh:

Year:  2019        PMID: 30790636     DOI: 10.1016/j.neubiorev.2019.02.008

Source DB:  PubMed          Journal:  Neurosci Biobehav Rev        ISSN: 0149-7634            Impact factor:   8.989


  19 in total

1.  Consensus Paper: Cerebellum and Social Cognition.

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Journal:  Cerebellum       Date:  2020-12       Impact factor: 3.847

2.  The posterior cerebellum supports implicit learning of social belief sequences.

Authors:  Qianying Ma; Min Pu; Elien Heleven; Naem P Haihambo; Kris Baetens; Chris Baeken; Natacha Deroost; Frank Van Overwalle
Journal:  Cogn Affect Behav Neurosci       Date:  2021-06-07       Impact factor: 3.282

3.  Reward-Based Learning and Emotional Habit Formation in the Cerebellum.

Authors:  Jordan E Pierce; Julie A Péron
Journal:  Adv Exp Med Biol       Date:  2022       Impact factor: 3.650

4.  Reorganization of the Neurobiology of Language After Sentence Overlearning.

Authors:  Jeremy I Skipper; Sarah Aliko; Stephen Brown; Yoon Ju Jo; Serena Lo; Emilia Molimpakis; Daniel R Lametti
Journal:  Cereb Cortex       Date:  2022-05-31       Impact factor: 4.861

5.  Cerebellum-cingulo-opercular network connectivity strengthens in adolescence and supports attention efficiency only in childhood.

Authors:  Sarah V Clark; Theodore D Satterthwaite; Tricia Z King; Robin D Morris; Elaheh Zendehrouh; Jessica A Turner
Journal:  Dev Cogn Neurosci       Date:  2022-06-25       Impact factor: 5.811

6.  Task-induced brain functional connectivity as a representation of schema for mediating unsupervised and supervised learning dynamics in language acquisition.

Authors:  Hiroyuki Akama; Yixin Yuan; Shunji Awazu
Journal:  Brain Behav       Date:  2021-05-05       Impact factor: 2.708

7.  Computational Modeling for Neuropsychological Assessment of Bradyphrenia in Parkinson's Disease.

Authors:  Alexander Steinke; Florian Lange; Caroline Seer; Merle K Hendel; Bruno Kopp
Journal:  J Clin Med       Date:  2020-04-18       Impact factor: 4.241

Review 8.  The basal ganglia and the cerebellum in human emotion.

Authors:  Jordan E Pierce; Julie Péron
Journal:  Soc Cogn Affect Neurosci       Date:  2020-07-01       Impact factor: 3.436

9.  Internal Clocks, mGluR7 and Microtubules: A Primer for the Molecular Encoding of Target Durations in Cerebellar Purkinje Cells and Striatal Medium Spiny Neurons.

Authors:  S Aryana Yousefzadeh; Germund Hesslow; Gleb P Shumyatsky; Warren H Meck
Journal:  Front Mol Neurosci       Date:  2020-01-10       Impact factor: 5.639

10.  Parallel model-based and model-free reinforcement learning for card sorting performance.

Authors:  Alexander Steinke; Florian Lange; Bruno Kopp
Journal:  Sci Rep       Date:  2020-09-22       Impact factor: 4.379

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