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Author Correction: A hippocampo-cerebellar centred network for the learning and execution of sequence-based navigation

Authors :
Laure Rondi-Reig
Anne-Lise Paradis
Benedicte M. Babayan
Aurélie Watilliaux
Benoît Girard
Guillaume Viejo
Sorbonne Université (SU)
Neurosciences Paris Seine (NPS)
Sorbonne Université (SU)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut de Biologie Paris Seine (IBPS)
Institut National de la Santé et de la Recherche Médicale (INSERM)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS)
Institut de Biologie Paris Seine (IBPS)
Institut National de la Santé et de la Recherche Médicale (INSERM)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)
Institut des Systèmes Intelligents et de Robotique (ISIR)
Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)
Architectures et modèles d'Adptation et de la cognition (AMAC)
Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)
Neuroscience Paris Seine (NPS)
Institut National de la Santé et de la Recherche Médicale (INSERM)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut de Biologie Paris Seine (IBPS)
Institut National de la Santé et de la Recherche Médicale (INSERM)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)
Source :
Scientific Reports, Scientific Reports, Nature Publishing Group, 2019, 9 (1), pp.19904. ⟨10.1038/s41598-019-56345-7⟩, Scientific Reports, Vol 9, Iss 1, Pp 1-2 (2019)
Publication Year :
2019
Publisher :
HAL CCSD, 2019.

Abstract

How do we translate self-motion into goal-directed actions? Here we investigate the cognitive architecture underlying self-motion processing during exploration and goal-directed behaviour. The task, performed in an environment with limited and ambiguous external landmarks, constrained mice to use self-motion based information for sequence-based navigation. The post-behavioural analysis combined brain network characterization based on c-Fos imaging and graph theory analysis as well as computational modelling of the learning process. The study revealed a widespread network centred around the cerebral cortex and basal ganglia during the exploration phase, while a network dominated by hippocampal and cerebellar activity appeared to sustain sequence-based navigation. The learning process could be modelled by an algorithm combining memory of past actions and model-free reinforcement learning, which parameters pointed toward a central role of hippocampal and cerebellar structures for learning to translate self-motion into a sequence of goal-directed actions.

Details

Language :
English
ISSN :
20452322
Database :
OpenAIRE
Journal :
Scientific Reports, Scientific Reports, Nature Publishing Group, 2019, 9 (1), pp.19904. ⟨10.1038/s41598-019-56345-7⟩, Scientific Reports, Vol 9, Iss 1, Pp 1-2 (2019)
Accession number :
edsair.doi.dedup.....3fb9528ed5a432e264d76ce3c9698c0a
Full Text :
https://doi.org/10.1038/s41598-019-56345-7⟩