Community structure analysis reveals the properties of social networks. The application of this analysis to evolving communities in dynamic networks can help understand how social interactions between individuals dynamically change and how the brain networks grow. Visualizing these communities becomes challenging since the time dimension is an important component in dynamic networks. The problem is still more complex as the biological neural networks have physical structures, and communities are used to explore functional groupings. Our interactive visualization technique is used for exploring the community structure of dynamic mouse brain correlation networks and behaviors of individual nodes in the networks through time.

Keywords: Neural networks, dynamic communities, information visualization.

Index Terms: H.5.2 [Information Interfaces & Presentation]: User Interfaces – Graphical User Interfaces (GUI).

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Ma, C., Kenyon, R.V., Berger-Wolf, T., Llano, D.A., Visualizing Communities in Dynamic Mouse Brain Networks, In Proceedings of the IEEE Visualization (VIS'14) Poster, Paris, France, November 9th, 2014.