Methods for Analyzing Multi-Subject Resting-State Neuroimaging Time Series Data
2019-05
Loading...
View/Download File
Persistent link to this item
Statistics
View StatisticsJournal Title
Journal ISSN
Volume Title
Title
Methods for Analyzing Multi-Subject Resting-State Neuroimaging Time Series Data
Authors
Published Date
2019-05
Publisher
Type
Thesis or Dissertation
Abstract
Resting-state neuroimaging modalities such as electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) collect data in the form of time series which represent the activity in the brain at rest. This resting-state behavior can be analyzed in different ways to address different research questions and is thought to represent the intrinsic activity of the brain. We discuss three potential avenues of analysis. First, we propose a permutation-based method which tests the longitudinal functional connectivity of fMRI data collected from cognitively normal participants and Alzheimer’s patients. Next, we propose a Bayesian nonparametric model to jointly perform spectral time series analysis on EEG data from 1,116 twins from the Minnesota Twin Family Study (MTFS) and discuss a novel heritability estimator for features of the estimated spectral density curves. Finally, we propose another Bayesian nonparametric model to perform EEG microstate analysis of the MTFS data at the twin pair level. Each method discussed views the resting-state time series data from a different angle. Additionally, in each of these scenarios, we jointly analyze data collected from many different participants while accounting for the design of the study in which the data was collected. Regardless of the analysis method chosen, accounting for the within and between-participant dependence structure yields improved results.
Description
University of Minnesota Ph.D. dissertation. May 2019. Major: Biostatistics. Advisors: Mark Fiecas, Lynn Eberly. 1 computer file (PDF); xv, 107 pages.
Related to
Replaces
License
Collections
Series/Report Number
Funding information
Isbn identifier
Doi identifier
Previously Published Citation
Suggested citation
Hart, Brian. (2019). Methods for Analyzing Multi-Subject Resting-State Neuroimaging Time Series Data. Retrieved from the University Digital Conservancy, https://hdl.handle.net/11299/206265.
Content distributed via the University Digital Conservancy may be subject to additional license and use restrictions applied by the depositor. By using these files, users agree to the Terms of Use. Materials in the UDC may contain content that is disturbing and/or harmful. For more information, please see our statement on harmful content in digital repositories.