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Exploring the brain connectivity: questions, challenges and recent findings

Banff International Research Station for Mathematical Innovation and Discovery

In recent years, there has been significant interest in investigating brain connectivity based on functional neuroimaging data to better understand brain organization and networks. A wide range of network modeling tools has been proposed for this goal. The simplest and most commonly used methods, such as full correlation, measure the marginal connection between fMRI time-series from a pair of brain regions. Some other methods, such as partial correlation, aim to measure the direct connectivity between brain regions by adjusting for the effects from other regions. Several important questions relevant to network analysis include: how does the brain network change when we construct the network based on direct connection as against marginal connection; how does the brain network change when we apply different levels of sparse regularization in estimating the network; whether and how functional connections are related to structural connections in the brain network. In this talk, we discuss methods and analyses that we have recently worked on in the effort to search for answers to these questions. We will present some interesting findings in our exploration of brain connectivity based on resting-state fMRI and diffusion MRI.

Mathematics; Statistics; Game theory, economics, social and behavioral sciences

video/mp4

Author affiliation: Emory University

2016-08-02

Attribution-NonCommercial-NoDerivatives 4.0 International

http://hdl.handle.net/2429/58629

Unreviewed

http://creativecommons.org/licenses/by-nc-nd/4.0/