<p> The research explores the functional architecture of the brain using fMRI in combination with behavioral and cognitive paradigms. Studying large-scale dynamic interactions of the brain's intrinsic connectivity networks (ICNs) forms the basis of the presented work. ICNs are networks of brain structures that display synchronous activity. Since the discovery of the default mode network in the resting brain, researchers have documented a handful of cortical, cerebellar and subcortical networks with a high level of similarity across subjects. There is striking convergence between ICNs observed in the resting brain and those elicited in activation tasks. ICNs can form when engaging in complex naturalistic tasks such as engaging in a simulated driving experience. ICNs can be identified using “blind source separation methods” such as Independent Components Analysis—a method well-suited for naturalistic and model-free activation-task designs. Most functional connectivity studies have examined the relationship between brain structures over extended periods of time. More recent work suggests that functional connectivity strength exhibits non-stationary fluctuations across longer time scales. Currently, little is known about how brain networks or ICNs interact during complex cognition or when externally engaged in a task. </p><p> Two experiments are presented along with the methods used to study large-scale network interactions while subjects are engaged in complex social cognition as well as basic oculo-motor function. Although the tasks differ in terms of the cognitive and perceptual processes involved, both experiments utilize a similar visually guided paradigm. This similarity enables us to study the effect of the task on the observed large-scale ICN functional interactions and to better our understanding of the functional significance of these functional dynamic organizations. Moreover, visually-guided paradigms can induce synchronous and unified experience across subjects, which allows us to study the common event-related and stimulus-driven interactions. Finally, large-scale network organization at various time scales is also discussed</p>
| Identifer | oai:union.ndltd.org:PROQUEST/oai:pqdtoai.proquest.com:3712047 |
| Date | 26 August 2015 |
| Creators | Ashourvan, Arian |
| Publisher | Indiana University |
| Source Sets | ProQuest.com |
| Language | English |
| Detected Language | English |
| Type | thesis |
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