Off-campus UMass Amherst users: To download campus access dissertations, please use the following link to log into our proxy server with your UMass Amherst user name and password.

Non-UMass Amherst users: Please talk to your librarian about requesting this dissertation through interlibrary loan.

Dissertations that have an embargo placed on them will not be available to anyone until the embargo expires.

Author ORCID Identifier


Open Access Dissertation

Document Type


Degree Name

Doctor of Philosophy (PhD)

Degree Program


Year Degree Awarded


Month Degree Awarded


First Advisor

Jennifer Martin McDermott

Subject Categories

Cognitive Neuroscience | Cognitive Psychology


Mental fatigue causes an increase in task-based EEG theta and alpha power and a decrease in performance (for a review, see Tran et al., 2020). However, little is known about the emergence of mental fatigue in resting state EEG recordings and whether the progression of mental fatigue over time is influenced by individual differences. The current dissertation examined the utility of resting state EEG as a measure of mental fatigue by testing whether EEG power changed in young adults over the course of a cognitively demanding battery of tasks. The current dissertation also tested how this measure of mental fatigue interacted with individual differences in ADHD symptomology to predict performance on one of the cognitive tasks as well as performance in a driving simulator. Resting state EEG was recorded at four intervals, before and after the three cognitively demanding tasks. Driving outcomes were collected at a separate visit to a driving simulator lab. Results indicated that resting state EEG theta and alpha power significantly decreased over time, but this association was not influenced by levels of ADHD symptomology. There was no evidence that resting state EEG power changes over time predicted cognitive or driving performance, even when ADHD symptomology was included. The current findings present preliminary evidence that resting state EEG power can be used as a marker of mental fatigue and provide unique insight into how mental fatigue develops by including an initial measurement of neural readiness before individuals engage in a cognitively demanding task.