Cited by 54Motor Control and AdaptationMemory and Neural MechanismsSport Psychology and Performance

Multifaceted aspects of chunking enable robust algorithms

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Acuna, Daniel E., Wymbs, Nicholas F., Reynolds, Chelsea A., Picard, Nathalie, Turner, Robert S., Strick, Peter L., Grafton, Scott T., Kording, Konrad P.·2014·Journal of Neurophysiology

Abstract

Sequence production tasks are a standard tool to analyze motor learning, consolidation, and habituation. As sequences are learned, movements are typically grouped into subsets or chunks. For example, most Americans memorize telephone numbers in two chunks of three digits, and one chunk of four. Studies generally use response times or error rates to estimate how subjects chunk, and these estimates are often related to physiological data. Here we show that chunking is simultaneously reflected in reaction times, errors, and their correlations. This multimodal structure enables us to propose a Bayesian algorithm that better estimates chunks while avoiding overfitting. Our algorithm reveals previously unknown behavioral structure, such as an increased error correlations with training, and promises a useful tool for the characterization of many forms of sequential motor behavior.

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Crossref · 10.1152/jn.00028.2014

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  • Humans excel at stitching together sub-actions to form larger actions.

    “Humans excel at stitching together sub-actions to form larger actions (Verwey, 1996; Acuna et al., 2014; Sejnowski and Poizner, 2014).”

    From Toward an integration of deep learning and neuroscience (2016) · cites this paper as Acuna et al., 2014

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Research works printed but not linked: 3

  1. Pavlov I. Conditioning Reflexes. New York: Oxford Univ Press, 1927 [Google Scholar]
  2. Thorndike EL. Animal intelligence: an experimental study of the association processes in animals. Psychol Rev Monograph 2: 1–8, 1898 [Google Scholar]
  3. Welch LR. Hidden Markov models and the Baum-Welch algorithm. IEEE Info Theory Soc Newsletter 53: 1–14, 2003 [Google Scholar]

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Authors
Acuna, D. E., Wymbs, N. F., Reynolds, C. A., Picard, N., Turner, R. S., Strick, P. L., Grafton, S. T., & Kording, K. P.
Affiliations
  • Northwestern University (US)
  • University of California, Santa Barbara (US)
  • University of Pittsburgh (US)
Corresponding author
Acuna, Daniel E.
Venue
Journal of Neurophysiology
Published
2014-10-15
Volume
112
Issue
8
Pages
1849-1856
ISSN
  • 0022-3077 (ISSN-L)
  • 1522-1598
OpenAlex
W2141348937
Cited by
54
References
36
Citations by year
2026: 2 · 2025: 3 · 2024: 2 · 2023: 6 · 2022: 6 · 2021: 4 · 2020: 3 · 2019: 3 · 2018: 8 · 2017: 7 · 2016: 5 · 2015: 4 · 2014: 1
FWCI
3.16
Type
journal article
Language
en
Open access
Locations
  • Journal of Neurophysiology (publishedVersion)
  • Europe PMC (PubMed Central) (publishedVersion)
  • PubMed Central (publishedVersion)
  • PubMed (publishedVersion)
Funders
National Institute of Neurological Disorders and Stroke (R01NS074044, NS 44393, P01NS044393, P30NS076405, NS-074044)
Topics
  • Life Sciences › Neuroscience › Cognitive Neuroscience › Motor Control and Adaptation
  • Life Sciences › Neuroscience › Cognitive Neuroscience › Memory and Neural Mechanisms
  • Social Sciences › Psychology › Developmental and Educational Psychology › Sport Psychology and Performance
Keywords
chunking, sequence generation, motor learning, habituation, reaction time, error rate, error correlation, Bayesian estimation, overfitting
MeSH terms
Algorithms, Animals, Bayes Theorem, Humans, Models, Biological, Models, Neurological, Movement, Practice, Psychological, Reaction Time

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