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Co-activation Pattern Analysis of Brain fMRI Signal at Avalanches

dc.contributor.advisorWilkes, Mitchell
dc.creatorGuo, Junlin
dc.date.accessioned2020-07-01T00:08:32Z
dc.date.available2020-07-01T00:08:32Z
dc.date.created2020-06
dc.date.issued2020-06-15
dc.date.submittedJune 2020
dc.identifier.urihttp://hdl.handle.net/1803/10102
dc.description.abstractAvalanches of brain activity, which are viewed as cascades of large spatiotemporal co-activation, have been investigated to be the key to brain functions and some information propagation in the brain. The functional magnetic resonance imaging (fMRI) has significantly contributed to studies concerning avalanches. This work attempts to explore the avalanches of resting-state fMRI via the co-activation pattern (CAP) analysis. The detection of avalanches is done by calculating the instantaneous whole-brain correlation (IWBC). Avalanches correspond to the periods in which the IWBC signal expresses high magnitudes. We showed that, overall, the activation of CAPs is consistent with IWBC magnitudes, and the synchronization of spatial activation exists throughout the brain cortex. The second interesting observation we found is that avalanches might induce changes in local activation (e.g., in several pairs of Brodmann areas). Additionally, the spatial CAPs might be significantly different after approaching avalanche peaks, which suggests the occurrence of spatial propagation during avalanches. Third, we further investigated the CAPs using only a subset of temporal points in the full BOLD signal. We found that the brief IWBC avalanche peaks may preserve more information regarding varying brain activation. Lastly, we measured the dynamics of the CAPs using the Markov model, which suggests that the few gigantic avalanche peaks likely remain significantly consistent and organized CAPs.
dc.format.mimetypeapplication/pdf
dc.language.isoen
dc.subjectAvalanches, CAP
dc.titleCo-activation Pattern Analysis of Brain fMRI Signal at Avalanches
dc.typeThesis
dc.date.updated2020-07-01T00:08:32Z
dc.type.materialtext
thesis.degree.nameMS
thesis.degree.levelMasters
thesis.degree.disciplineElectrical Engineering
thesis.degree.grantorVanderbilt University
dc.creator.orcid0000-0001-9300-0314


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