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A Stratification Matrix Viewer for Analysis of Neural Network Data

  • The analysis of brain networks is central to neurobiological research. In this context the following tasks often arise: (1) understand the cellular composition of a reconstructed neural tissue volume to determine the nodes of the brain network; (2) quantify connectivity features statistically; and (3) compare these to predictions of mathematical models. We present a framework for interactive, visually supported accomplishment of these tasks. Its central component, the stratification matrix viewer, allows users to visualize the distribution of cellular and/or connectional properties of neurons at different levels of aggregation. We demonstrate its use in four case studies analyzing neural network data from the rat barrel cortex and human temporal cortex.

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Author:Philipp HarthORCiD, Sumit VohraORCiD, Daniel UdvaryORCiD, Marcel OberlaenderORCiD, Hans-Christian HegeORCiDGND, Daniel BaumORCiD
Document Type:In Proceedings
Parent Title (English):Eurographics Workshop on Visual Computing for Biology and Medicine (VCBM)
Place of publication:Vienna, Austria
Publishing Institution:Zuse Institute Berlin (ZIB)
Year of first publication:2022
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