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Latin American Workshop on Computational Neuroscience

LAWCN 2019: Computational Neuroscience pp 91–103Cite as

Association Between Fast and Slow Learning and Molecular Processes in Repetitive Practice: A Post Hoc Analysis

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Part of the Communications in Computer and Information Science book series (CCIS,volume 1068)

Abstract

The explanations for the positive effects of less repetitive practice in learning, compared to more repetitive practice, converge towards an idea of a greater memory strengthening in less repetitive practice. These benefits are associated with the AMPA glutamate receptor. However, there are no studies in the literature that explain, in molecular terms, how memory processes during practice (or acquisition) are associated with these benefits. Overall, the process of memory strengthening in the acquisition of a motor skill has two distinct stages: a fast initial performance improvement followed by a gradual change associated with the memory state termed slow learning. Computational models, like the multi-rate learning model, help to identify these two distinct stages (fast and slow learning). This study aimed to investigate if the AMPA receptors are associated with the memory’s fast state (fast learning) and slow state (slow learning). Mice (n = 30) practiced the rotarod in two days of constant (one rotation frequency) or varied (three different rotation frequencies) practice. Animals were tested both 24 h and 10 days after acquisition. Two analyses were conducted, stepwise discriminant analysis and analysis of the difference between the predicted and observed values. Varied practice was more associated with the slow state. The findings of the present study advance in the explanations of the molecular mechanisms underpinning the greater memory strengthening proposed by behavioral hypotheses. Furthermore, we propose an alternative explanation for the explanations formulated at behavioral level, highlighting the role of the reference of the error that is produced trial-to-trial.

Keywords

  • Motor learning
  • Practice schedule
  • AMPA receptor
  • Fast learning
  • Slow learning

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Acknowledgments

This study was supported by Fundação de Amparo à Pesquisa do Estado de Minas Gerais (FAPEMIG) (grant APQ-03305-15) and Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - Brasil (CAPES), finance Code 001.

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Authors and Affiliations

  1. School of Physical Education, Physiotherapy and Occupational Therapy, NNeuroM, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil

    Tércio Apolinário-Souza, Natália Lelis Torres, Juliana Otoni Parma, Lidiane Aparecida Fernandes & Guilherme Menezes Lage

  2. Department of Human Movement Sciences, GEPECOM, Universidade do Estado de Minas Gerais, Ibirité, Brazil

    Tércio Apolinário-Souza

  3. Institute of Biological Sciences, NNC, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil

    Ana Flavia Santos-Almeida & Grace Schenatto Pereira

  4. Rua Desembargador Paula Mota, 30, ap.201. Ouro Preto, Belo Horizonte, CEP 31310-340, Brazil

    Tércio Apolinário-Souza

Authors
  1. Tércio Apolinário-Souza
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  2. Ana Flavia Santos-Almeida
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  3. Natália Lelis Torres
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  4. Juliana Otoni Parma
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  5. Lidiane Aparecida Fernandes
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  6. Grace Schenatto Pereira
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  7. Guilherme Menezes Lage
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Corresponding author

Correspondence to Tércio Apolinário-Souza .

Editor information

Editors and Affiliations

  1. Federal University of São João Del-Rei, São João Del-Rei, Brazil

    Vinícius Rosa Cota

  2. Federal University of Rio Grande do Sul, Porto Alegre, Brazil

    Dante Augusto Couto Barone

  3. Federal University of São João Del-Rei, São João Del-Rei, Brazil

    Diego Roberto Colombo Dias

  4. Federal University of São João Del-Rei, São João Del-Rei, Brazil

    Laila Cristina Moreira Damázio

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Apolinário-Souza, T. et al. (2019). Association Between Fast and Slow Learning and Molecular Processes in Repetitive Practice: A Post Hoc Analysis. In: Cota, V., Barone, D., Dias, D., Damázio, L. (eds) Computational Neuroscience. LAWCN 2019. Communications in Computer and Information Science, vol 1068. Springer, Cham. https://doi.org/10.1007/978-3-030-36636-0_7

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  • DOI: https://doi.org/10.1007/978-3-030-36636-0_7

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