Purdue University Graduate School
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posted on 2019-08-12, 19:00 authored by Sumra BariSumra Bari

Head injuries in collision sports have been linked to long-term neurological disorders. High school collision sport athletes, a population vulnerable to head injuries, are at a greater risk of chronic damage. Various studies have indicated significant deviations in brain function due to the accumulation of repetitive low-level subconcussive impacts to the head without externally observable cognitive symptoms. The aim of this study was to investigate metabolic changes in asymptomatic collision sport athletes across time within their competition season and as a function of mechanical force to their head. For this purpose, Proton Magnetic Resonance Spectroscopy (MRS) was used as a tool to detect altered brain metabolism in high school collision sport athletes (football and soccer) without diagnosed concussion. Also, sensors were attached to each athletes head to collect the count and magnitude of head impacts during their games and practices. Transient neurometabolic alterations along with prolonged recovery were observed in collision sport athletes.

Multi-site studies are becoming important to increase statistical power, enhance generalizability, and to improve the likelihood of pooling relevant subgroups together activities which are otherwise limited by the availability of patients or funds at a single site. Even with harmonized imaging sequences, site-dependent variability can mask the advantages of these multi-site studies. The aim of this study was to assess multi-site reproducibility in resting-state functional connectivity fingerprints, and to improve identifiability of obtained functional connectomes. We evaluated individual fingerprints in test- retest visit pairs within and across two sites and present a generalized framework based on principal component analysis (PCA) to improve identifiability. The optimally reconstructed functional connectomes using PCA showed a substantial improvement in individual fingerprinting of the subjects within and across the two sites and test-retest visit pairs relative to the original data. Results demonstrate that the data-driven method presented in the study can improve identifiability in resting-state functional connectomes in multi-site studies.


Degree Type

  • Doctor of Philosophy


  • Electrical and Computer Engineering

Campus location

  • West Lafayette

Advisor/Supervisor/Committee Chair

Thomas M. Talavage

Additional Committee Member 2

Eric A. Nauman

Additional Committee Member 3

Joaquin Goni

Additional Committee Member 4

David J. Love

Additional Committee Member 5

Edward J. Delp