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Faculty of Graduate Studies

Isaac Barss

  • B.Sc. (University of Victoria, 2018)
Notice of the Final Oral Examination for the Degree of Master of Science

Topic

Mobile EEG for the Detection of Mild Cognitive Impairment

School of Medical Sciences

Date & location

  • Thursday, September 10, 2026
  • 9:00 A.M.
  • Virtual Defence

Examining Committee

Supervisory Committee

  • Dr. Olav Krigolson, School of Medical Sciences, University of Victoria (Supervisor)
  • Dr. Alexandre Henri-Bhargava, School of Medical Sciences, UVic (Member)

External Examiner

  • Dr. Gordon Binsted, Provost and Vice-President Academic, Thompson Rivers University

Chair of Oral Examination

  • Dr. Lisa Surridge, Department of English, UVic

Abstract

This thesis investigates the utility of mobile electroencephalography (EEG) as a screening tool for mild cognitive impairment (MCI), a clinical syndrome that describes a level of cognitive function between normal aging and dementia. Current diagnostic approaches rely primarily on cognitive screening tests, such as the Montreal Cognitive Assessment (MoCA), and clinical interviews. These methods face well-documented limitations that restrict their feasibility and accessibility in primary care and population-level screening settings. Given the high prevalence of MCI, its frequent progression to dementia, and the etiological heterogeneity underlying the syndrome, there are clear benefits to efficient first-pass screening, but no tool currently meets this need. Event-related potentials (ERPs) and power spectral density (PSD) are promising electrophysiological markers of cognitive decline in MCI, with both cross-sectional and longitudinal evidence linking changes in these features to cognitive status. Traditional EEG acquisition, however, has historically been subject to the same limitations as other neuroimaging methods: time, cost, and testing space requirements that restrict scalability. Recent advances in mobile EEG systems have effectively eliminated these barriers, positioning mobile EEG as a low-cost and rapid potential complement to existing screening and diagnostic approaches. The present thesis examines whether mobile EEG measures can reliably distinguish individuals with MCI from cognitively healthy older adults. Two studies are applied to this problem. Cognitive performance was assessed in all participants using standardized cognitive assessments. EEG data were then recorded using a low-density, mobile EEG device. First, the N200 and P300 ERPs were derived from a visual oddball task. Second, posterior alpha power was examined during resting-state eyes-open and eyes-closed conditions. Group differences in ERP amplitude and latency, and in resting-state alpha power and reactivity were assessed to evaluate the feasibility of mobile EEG for the screening of MCI. Study 1 Results: Group differences in N200 ERP amplitude were identified between MCI and healthy controls, but not N200 latency, or P300 amplitude or latency. Study 2 Results: Group differences in alpha power were identified between MCI and healthy controls during eyes-closed resting state, but not eyes-open resting state. Together, these two studies provide converging evidence that mobile EEG is sensitive to electrophysiological markers of MCI in both ERPs and PSDs.

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