Visual-motor sequence learning by competitive fighting game experts

Hanako Ikeda, Satoshi Tanaka, Ryo Kato, Kazumi Kasahara, Takashi Hanakawa, Manabu Honda, Katsumi Watanabe

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

Playing action video games has been reported to modify some cognitive functions. However, no study has investigated whether the explicit learning of arbitrary visualmotor sequences would differ between video game expert and non-expert groups. The present study compared the explicit learning of visual-motor sequences in 12 expert players of a competitive fighting video game with 20 non-expert control participants. The participants were required to determine a sequence of button presses by trial and error and elaborate the learned sequence. The results showed that the expert game players were generally faster in visual-motor responses and kept improving at the later stage of learning compared with the control group. These results suggest that competitive fighting game experts have enhanced ability in sequence learning and imply that this can be generalized to the learning of arbitrary spatiotemporal structures of visual-motor behaviors.

Original languageEnglish
Title of host publicationProceedings of the 2013 5th International Conference on Knowledge and Smart Technology, KST 2013
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages178-181
Number of pages4
ISBN (Electronic)9781467348508
DOIs
Publication statusPublished - 2013
Event5th International Conference on Knowledge and Smart Technology, KST 2013 - Chonburi, Thailand
Duration: 2013 Jan 312013 Feb 1

Publication series

NameProceedings of the 2013 5th International Conference on Knowledge and Smart Technology, KST 2013

Conference

Conference5th International Conference on Knowledge and Smart Technology, KST 2013
Country/TerritoryThailand
CityChonburi
Period13/1/3113/2/1

Keywords

  • Component
  • Expert
  • Sequential motor learning

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Science Applications
  • Computer Vision and Pattern Recognition
  • Industrial and Manufacturing Engineering

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