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University of Ontario Institute of Technology

Exploring lateralized sensorimotor processing using somatosensory evoked potentials

Abstract

dc:description.abstract

Differences exist between the two upper limbs in the chosen motor control strategy when moving in dynamic environments. To date, a large body of literature has explored these differences but few studies have incorporated neurophysiological data to support their findings. By utilizing somatosensory evoked potentials (SEPs) we can gain insight into the underlying neurological processes at the levels of the spinal cord and the cortex in response to movement and motor learning. The research conducted showed greater accuracy in the non-dominant limb following a novel tracing task. This was complimented by differential SEP peak amplitudes in the pathways that reflect cerebellar activation and sensorimotor integration. Additionally, the research also showed that when motor task acquisition occurs in the presence of sensory perturbations, the non-dominant limb is more accurate than a control group and there are differential changes in peaks reflecting the primary somatosensory cortex and the cerebellum

Degree

thesis:*
Name thesis:degree_name
Master of Health Sciences (MHSc)
Discipline thesis:degree_discipline
Kinesiology
Grantor
University of Ontario Institute of Technology
Year dc:date.issued
2017

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Gilley, Ryan
Advisors dc:contributor.advisor
  • Yielder, Paul
  • Murphy, Bernadette

Subjects

dc:subject × 5

Rights

Language dc:language.iso
en

Identifiers

dc:identifier.*
Handle dc:identifier.uri
https://hdl.handle.net/10155/831
OAI identifier oai:identifier
oai:ontariotechu.scholaris.ca:10155/831

Chain of custody

source
Harvested from
Ontario Institute of Technology
Base URL
ontariotechu.scholaris.ca/server/oai/request
Last updated
2026-07-24
Source record
OAI-PMH GetRecord
citation

Gilley, Ryan. Exploring lateralized sensorimotor processing using somatosensory evoked potentials. University of Ontario Institute of Technology, 2017. https://hdl.handle.net/10155/831