Brain Modulyzer: Interactive Visual Analysis of Functional Brain Connectivity

We present Brain Modulyzer, an interactive visual exploration tool for functional magnetic resonance imaging (fMRI) brain scans, aimed at analyzing the correlation between different brain regions when resting or when performing mental tasks. Brain Modulyzer combines multiple coordinated views-such a...

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Bibliographic Details
Published in:IEEE/ACM transactions on computational biology and bioinformatics 2017-07, Vol.14 (4), p.805-818
Main Authors: Murugesan, Sugeerth, Bouchard, Kristopher, Brown, Jesse A., Hamann, Bernd, Seeley, William W., Trujillo, Andrew, Weber, Gunther H.
Format: Article
Language:English
Subjects:
60 APPLIED LIFE SCIENCES
BASIC BIOLOGICAL SCIENCES
Brain
Brain architecture
brain imaging
Brain mapping
Case studies
cluster analysis
Cognitive tasks
Correlation
Correlation analysis
Data visualization
Feedback
Functional magnetic resonance imaging
functional magnetic resonance imaging (fMRI)
Functional morphology
Graph theory
Graph visualization
Layout
linked views
Magnetic resonance imaging
Network topology
Neural networks
Neuroimaging
neuroinformatics
neutroinformatics
Organizations
Paralysis
Progressive supranuclear palsy
Scientific visualization
Statistical analysis
Three-dimensional displays
Visual perception
Visualization
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Summary:We present Brain Modulyzer, an interactive visual exploration tool for functional magnetic resonance imaging (fMRI) brain scans, aimed at analyzing the correlation between different brain regions when resting or when performing mental tasks. Brain Modulyzer combines multiple coordinated views-such as heat maps, node link diagrams, and anatomical views-using brushing and linking to provide an anatomical context for brain connectivity data. Integrating methods from graph theory and analysis, e.g., community detection and derived graph measures, makes it possible to explore the modular and hierarchical organization of functional brain networks. Providing immediate feedback by displaying analysis results instantaneously while changing parameters gives neuroscientists a powerful means to comprehend complex brain structure more effectively and efficiently and supports forming hypotheses that can then be validated via statistical analysis. To demonstrate the utility of our tool, we present two case studies-exploring progressive supranuclear palsy, as well as memory encoding and retrieval.
ISSN:1545-5963
1557-9964
DOI:10.1109/TCBB.2016.2564970