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BRAIN NETWORKS: MULTIVARIATE TOOLS TO ANALYZE STRUCTURE, FUNCTION, AND DYNAMICS

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abstract
The rapid advancement of neuroimaging techniques and powerful computers has provided an unprecedented opportunity to explore the structure, function, and dynamics of the brain as what it truly is – a complex system. This has led to thousands of publications about brain function and its abnormalities in neural disorders over the past two decades. However, despite promising findings, the inherent limitations of the predominantly used averaging and massively univariate tools prevent clinicians and scientists from fully benefiting from the wealth of information contained in neuroimaging data. This project presents novel multivariate tools to overcome critical limitations of current methods in analyzing the function and dynamics of brain networks.
subject
contributor
Bahrami, Mohsen (author)
Simpson, Sean L (committee chair)
Simpson, Sean L (committee member)
Laurienti, Paul J (committee member)
LaConte, Stephen M (committee member)
Ip, Edward H (committee member)
Berenhaut, Kenneth S (committee member)
date
2020-01-08T09:35:20Z (accessioned)
2020-01-08T09:35:20Z (available)
2019 (issued)
degree
Biomedical Engineering (discipline)
identifier
http://hdl.handle.net/10339/95946 (uri)
language
en (iso)
publisher
Wake Forest University
title
BRAIN NETWORKS: MULTIVARIATE TOOLS TO ANALYZE STRUCTURE, FUNCTION, AND DYNAMICS
type
Dissertation

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