Dynamic Neural Correlates of Mental Attention Capacity
dc.contributor.advisor | Stevens, Dale | |
dc.contributor.author | Zarie, Amir Abbas | |
dc.date.accessioned | 2021-03-08T17:17:59Z | |
dc.date.available | 2021-03-08T17:17:59Z | |
dc.date.copyright | 2020-10 | |
dc.date.issued | 2021-03-08 | |
dc.date.updated | 2021-03-08T17:17:58Z | |
dc.degree.discipline | Psychology (Functional Area: Brain, Behaviour & Cognitive Sciences | |
dc.degree.level | Master's | |
dc.degree.name | MA - Master of Arts | |
dc.description.abstract | Mental attention capacity (M-capacity) the maximum amount of information one can process simultaneously is a predictor of academic and professional success. However, its neural underpinnings are not well understood. Here, a novel implementation of dynamic functional connectivity (dFC) analysis of resting-state functional MRI data with parcellation of individual brains into a common set of functional areas (Group Prior Individual Parcellation, GPIP) was used to determine whether dFC is 1) related to individual differences in M-capacity and 2) modulated by prior performance of a demanding M-capacity task. Additionally, the novel dFC approach using GPIP was validated against a well-established dFC method (Group ICA of fMRI Toolbox, GIFT). While one measure of dFC accounted for individual differences in Mcapacity, dFC was not modulated by prior task performance. The novel dFC analysis using GPIP produced similar results to GIFT dFC, demonstrating the validity and potential advantages of this novel approach to dFC analysis | |
dc.identifier.uri | http://hdl.handle.net/10315/38156 | |
dc.language | en | |
dc.rights | Author owns copyright, except where explicitly noted. Please contact the author directly with licensing requests. | |
dc.subject | Neurosciences | |
dc.subject.keywords | dynamic functional connectivity | |
dc.subject.keywords | fMRI | |
dc.subject.keywords | M-capacity | |
dc.subject.keywords | GPIP | |
dc.title | Dynamic Neural Correlates of Mental Attention Capacity | |
dc.type | Electronic Thesis or Dissertation |
Files
Original bundle
1 - 1 of 1
Loading...
- Name:
- Zarie_Amir_A_2020_Masters.pdf
- Size:
- 2.23 MB
- Format:
- Adobe Portable Document Format
- Description: