Node Identification Using Inter-Regional Correlation Analysis for Mapping Detailed Connections in Resting State Networks

Brain function is often characterized by the connections and interactions between highly interconnected brain regions. Pathological disruptions in these networks often result in brain dysfunction, which manifests as brain disease. Typical analysis investigates disruptions in network connectivity bas...

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Bibliographic Details
Published in:Frontiers in neuroscience 2017-05, Vol.11, p.238-238
Main Authors: Sohn, William S, Lee, Tae Young, Yoo, Kwangsun, Kim, Minah, Yun, Je-Yeon, Hur, Ji-Won, Yoon, Youngwoo Bryan, Seo, Sang Won, Na, Duk L, Jeong, Yong, Kwon, Jun Soo
Format: Article
Language:English
Subjects:
Alzheimer's disease
Brain diseases
Brain mapping
Brain research
Caregivers
connectomics
Correlation analysis
Functional magnetic resonance imaging
Methods
Neural networks
Neurodegeneration
Neuroscience
node identification
Patients
resting fMRI
Studies
subject-specific ROIs
Citations: Items that this one cites
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Summary:Brain function is often characterized by the connections and interactions between highly interconnected brain regions. Pathological disruptions in these networks often result in brain dysfunction, which manifests as brain disease. Typical analysis investigates disruptions in network connectivity based correlations between large brain regions. To obtain a more detailed description of disruptions in network connectivity, we propose a new method where functional nodes are identified in each region based on their maximum connectivity to another brain region in a given network. Since this method provides a unique approach to identifying functionally relevant nodes in a given network, we can provide a more detailed map of brain connectivity and determine new measures of network connectivity. We applied this method to resting state fMRI of Alzheimer's disease patients to validate our method and found decreased connectivity within the default mode network. In addition, new measure of network connectivity revealed a more detailed description of how the network connections deteriorate with disease progression. This suggests that analysis using key relative network hub regions based on regional correlation can be used to detect detailed changes in resting state network connectivity.
ISSN:1662-4548
1662-453X
1662-453X
DOI:10.3389/fnins.2017.00238