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Exploring differences in functional connectivity between senior fallers and non-fallers

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Title: Exploring differences in functional connectivity between senior fallers and non-fallers
Author: Hsu, Chun Liang
Degree Master of Science - MSc
Program Rehabilitation Sciences
Copyright Date: 2012
Publicly Available in cIRcle 2012-10-31
Abstract: Background: Falls among seniors are a major health issue. About 30% of community-dwelling adults aged 65 years and older experience one or more falls per year. Although not all falls lead to injury, 20% require medical attention and 5% result in fracture. Fall-related injuries are the leading cause of mortality due to unintentional injuries among those 65 and older. Key falls risk factors are categorized into physical factors (e.g. gait speed, balance, muscle strength, etc.) and neurocognitive factors (e.g. cognitive performance, brain volume, etc.). To date, few studies have examined the brain function on falls risk. My thesis explores this question through functional connectivity MRI analysis. Method: A cross-sectional functional magnetic resonance imaging study consisted of 44 (23 non-fallers and 21 fallers) community dwelling older adults. Participants performed the finger tapping motor task and I examined for differences in functional connectivity of four age-related neural networks: default mode network (DMN), fronto-executive network (FE), fronto-parietal network (FP), and motor network (Mot). Results: Significant between-group differences were identified in between-network functional connectivity. Fallers showed decreased connectivity between the FP network and Mot network (p<0.05) and increased connectivity between the FP network and DMN (p=0.04). No significant within-network differences were observed between the two groups. Conclusion: Results from this study extend our current knowledge on the neural basis of falls in community-dwelling older adults, and suggest a history of falls is associated with disruptions in neural network patterns that are undetectable by traditional clinical testing. Thus, a history of falls may be an early clinical biomarker for dementia risk. Future research is required to examine the directionality of this relationship as well as explore innovative falls-prevention strategies.
URI: http://hdl.handle.net/2429/43555
Scholarly Level: Graduate

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