RemBrain: Exploring Dynamic Biospatial Networks with MosaicMatrices and Mirror Glyphs

Integration of temporal community characteristics into the brain slice of an aged mouse, across 64 time steps.

Authors: Ma, C., Pellolio, F., Llano, D., Stebbings, K.A., Kenyon, R.V., Marai, G.E.

Publication: Journal of Imaging Science and Technology

We introduce a web-based visual comparison approach for the systematic exploration of dynamic activation networks across biological datasets. Understanding the dynamics of such networks in he context of demographic factors like age is a fundamental problem in computational systems biology and neuroscience. We design visual encodings for the dynamic and community characteristics of these temporal networks. Our multi-scale approach blends nested mosaic matrices that capture temporal characteristics of the data, spatial views of the network data, Kiviat diagrams and mirror glyphs that detail the temporal behavior and community assignment of specific nodes. A top design specifically targeted at pairwise visual comparison further supports the comparative analysis of multiple dataset activations. We demonstrate the effectiveness of this approach through a case study on mouse brain network data. Domain expert feedback indicates this approach can help identify trends and anomalies in the data. © 2017 Society for Imaging Science and Technology.
[DOI: 10.2352/J.ImagingSci.Technol.2017.61.6.000000]

Date: November 1, 2017 - December 1, 2017

Document: View PDF

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