Neural correlates of high visuomotor performance using a sporting model

Winstanley, Mike (2024). Neural correlates of high visuomotor performance using a sporting model. University of Birmingham. Ph.D.

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Abstract

The present study seeks to identify neural correlates of high performance in ecological valid, sporting tasks and quantify the differences between high skilled and low skilled players. To do this, Esports is chosen to be the sporting model to facilitate clean brain activity recordings whilst playing sport, something that is considerably more challenging with traditional sports. Participants are first separated into a skilled or unskilled group based on their Esports performance using objective classification measures to identify the presence of a higher and lower performing groups. Their brain activity is then recorded as they complete a series of visuomotor psychophysics and Esports aim-training tasks. Results indicate that there are several key differences in the brain activity of skilled players that facilitate a higher level of performance. Firstly, skilled players modulate visual attention, gated by alpha oscillations, to release the visual system before target onset. As a result, visual information is consciously accessed more readily to be utilized for a motor response. Secondly, skilled players utilize cueing information, received from multi-sensory cues, and propagate it in working memory to narrow visual search and improve performance. Finally, skilled players show an increase in frontal-midline theta during Esports performance facilitating management of cognitive load and repeated execution of precise movements. Due to the nature of the model, applied implications are suggested for both coaches and athletes of all sports to utilize this research. Specifically, performance improvement of players could be facilitated by identifying deficits in their brain activity and talent identification, by observing the neural correlates reported in developing players.

Type of Work:

Thesis (Doctorates > Ph.D.)

Award Type:

Doctorates > Ph.D.

Supervisor(s):