Predicting domain-specific actions in expert table tennis players activates the semantic brain network
Wang, Y., Lu, Y., Deng, Y., Gu, N., Parviainen, T., & Zhou, C. (2019). Predicting domain-specific actions in expert table tennis players activates the semantic brain network. NeuroImage, 200, 482-489. https://doi.org/10.1016/j.neuroimage.2019.06.035
Julkaistu sarjassa
NeuroImagePäivämäärä
2019Oppiaine
Monitieteinen aivotutkimuskeskusHyvinvoinnin tutkimuksen yhteisöCentre for Interdisciplinary Brain ResearchSchool of WellbeingTekijänoikeudet
© 2019 Elsevier Inc.
Motor expertise acquired during long-term training in sports enables top athletes to predict the outcomes of domain-specific actions better than nonexperts do. However, whether expert players encode actions, in addition to the concrete sensorimotor level, also at a more abstract, conceptual level, remains unclear. The present study manipulated the congruence between body kinematics and the subsequent ball trajectory in videos of an expert player performing table tennis serves. By using functional magnetic resonance imaging, the brain activity was evaluated in expert and nonexpert table tennis players during their predictions on the fate of the ball trajectory in congruent versus incongruent videos. Compared with novices, expert players showed greater activation in the sensorimotor areas (right precentral and postcentral gyri) in the comparison between incongruent vs. congruent videos. They also showed greater activation in areas related to semantic processing: the posterior inferior parietal lobe (angular gyrus), middle temporal gyrus, and ventromedial prefrontal cortex. These findings indicate that action anticipation in expert table tennis players engages both semantic and sensorimotor regions and suggests that skilled action observation in sports utilizes predictions both at motor-kinematic and conceptual levels.
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ElsevierISSN Hae Julkaisufoorumista
1053-8119Asiasanat
Julkaisu tutkimustietojärjestelmässä
https://converis.jyu.fi/converis/portal/detail/Publication/32097257
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This work was supported by the grants from National Natural Science Foundation of China (No.31571151), and YW was supported by a grant from the Chinese Scholarship Council.Lisenssi
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