Keywords

motor control, limb dominance, handedness, electroencephalography, bimanual coordination

Subject Categories

Cognitive Neuroscience | Kinesiology | Neuroscience and Neurobiology

Abstract

Humans interact with our environment in many ways. One of the most outward-facing aspects of this is limb dominance. The neural underpinnings of limb dominance remain in question today. The objective of this research was to use different methods to analyze neural activation while subjects performed upper extremity motor tasks while recording electroencephalography (EEG). The first experiment used decoding methods to examine whether neural signals collected from the contralateral limb could be used to train a classifier to test on the ipsilateral limb during a reach-to-grasp or reach-to-touch task. It was determined above chance level that within-subject action and direction were able to be decoded for planning and execution phases of movement. The second experiment examined the effect of hand preference and hand used on the neural response to a mechanical perturbation. Subjects performed a move to target task while using a robotic device and a mechanical perturbation was randomly applied. Left-handers showed a greater negative frontal event related potential (ERP) during the beginning of the voluntary response than right-handers and showed a greater frontal and parietal positive symmetrical ERP, while right-handers showed a more asymmetrical response. Finally, neural activity of bimanual coordination was examined in response to visual perturbation. Subjects performed a balance task where one, or both sides of a horizontal bar was perturbed on a screen while the subjects controlled both ends or one end of the bar using a robotic manipulandum. Differences were observed in both ERP and ERSP in parietal reach regions, sensorimotor regions and anterior cingulate involved in bimanual coordination, even during unimanual movements. All these results show the importance of considering limb dominance while implementing motor control research and informing brain machine interfaces, as well as filling a gap in the literature.

Completion Date

2026

Semester

Summer

Committee Chair

Fu, Qiushi

Degree

Doctor of Philosophy (Ph.D.)

College

College of Engineering and Computer Science

Department

Mechanical and Aerospace Engineering

Format

PDF

Document Type

Dissertation

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