Studying Network Variants With Electroencephalography

McCarthy, Michael

Studying Network Variants With Electroencephalography

dc.contributor.advisor	Protzner, Andrea
dc.contributor.author	McCarthy, Michael
dc.contributor.committeemember	Bray, Signe
dc.contributor.committeemember	Goodyear, Bradley
dc.contributor.committeemember	Pexman, Penny
dc.date	2024-05
dc.date.accessioned	2024-02-16T19:03:31Z
dc.date.available	2024-02-16T19:03:31Z
dc.date.issued	2024-02-15
dc.description.abstract	Functional MRI (fMRI) studies have shown that the human functional connectome exhibits reliable and substantial variability in organization across individuals, so-called network variants. However, it is unclear whether neuroimaging modalities that measure different aspects of brain function show similar evidence of such individual differences. Here we explored the feasibility of using electroencephalography (EEG) to study network variants using repeated measures eyes-closed and eyes-open resting state data from 14 participants taken across three sessions over the course of three months—estimating how much and in which ways band-limited phase coupling and amplitude coupling functional connectomes differed in similarity within and between individuals across contexts. For each coupling mode and frequency band, we hypothesized that if functional connectome organization was influenced by stable individual- dependent factors in our sample, then functional connectomes would be more similar within than between individuals across all contexts, on average, with smaller variations in similarity related to session or state. Overall, our results were inconclusive. Although we generally found consistently positive differences in functional connectome similarity across coupling modes, frequency bands, and contexts on average—depending on the comparison, these differences were either negligible or at most small, and were inconsistent across participants. We discuss several factors that may explain the differences between our results and the larger, more consistent effects reported in fMRI network variant studies, such as the spatial and temporal resolution of EEG and fMRI, and the methods used to estimate functional connectivity. We then offer suggestions for future EEG research that might address some shortcomings of our study.
dc.identifier.citation	McCarthy, M. (2024). Studying network variants with electroencephalography (Master's thesis, University of Calgary, Calgary, Canada). Retrieved from https://prism.ucalgary.ca.
dc.identifier.uri	https://hdl.handle.net/1880/118186
dc.language.iso	en
dc.publisher.faculty	Graduate Studies
dc.publisher.institution	University of Calgary
dc.rights	University of Calgary graduate students retain copyright ownership and moral rights for their thesis. You may use this material in any way that is permitted by the Copyright Act or through licensing that has been assigned to the document. For uses that are not allowable under copyright legislation or licensing, you are required to seek permission.
dc.subject	Electroencephalography
dc.subject	Functional Connectivity
dc.subject	Network Variants
dc.subject	Individual Differences
dc.subject.classification	Psychology
dc.subject.classification	Neuroscience
dc.title	Studying Network Variants With Electroencephalography
dc.type	master thesis
thesis.degree.discipline	Psychology
thesis.degree.grantor	University of Calgary
thesis.degree.name	Master of Science (MSc)
ucalgary.thesis.accesssetbystudent	I do not require a thesis withhold – my thesis will have open access and can be viewed and downloaded publicly as soon as possible.