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Fractal Scaling in Motor Sequence Learning: Examining Acceleratory Movement Variability in a Step-based Discrete Sequence Production Test Among Fast and Slow Performers

Hildebrandt, M. (2024) Fractal Scaling in Motor Sequence Learning: Examining Acceleratory Movement Variability in a Step-based Discrete Sequence Production Test Among Fast and Slow Performers.

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Abstract:This study explores the use of fractal analysis, particularly through Hurst exponents, to understand motor sequence learning dynamics in a modified Discrete Sequence Production task using a dance mat interface. We aimed to assess if Hurst exponents predict individual performance, adaptation to novel sequences, and proficiency levels among 22 participants. Movements, particularly the Center of Mass acceleration, were recorded via motion capture sensors. Hurst exponents calculated for movement preparation and sequence execution phases indicated distinct fractal properties of motor outputs. In the preparation phase, better performers showed an increasing trend of Hurst exponents, suggesting more effective anticipation and motor planning. However, in the sequence execution phase, Hurst exponents were not associated with performance or adaptability, as consistently high Hurst exponents indicative of fractal scaling were observed among both proficient and less proficient performers. Notably, some fast participants exhibited reduced, varied Hurst exponents during execution. In response to changing task constraints, their fractal complexity in the motor output increased again. The findings suggest that less fractal motor output may signify an optimized mode for rapid, automatic movements with minimal cognitive control, while high exponents during execution could reflect a strategy focusing on accuracy and exploration, requiring continuous cognitive engagement.
Item Type:Essay (Bachelor)
Faculty:BMS: Behavioural, Management and Social Sciences
Subject:77 psychology
Programme:Psychology BSc (56604)
Link to this item:https://purl.utwente.nl/essays/100732
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