Harth, PhilippVohra, SumitUdvary, DanielOberlaender, MarcelHege, Hans-ChristianBaum, DanielRenata G. RaidouBjörn SommerTorsten W. KuhlenMichael KroneThomas SchultzHsiang-Yun Wu2022-09-192022-09-192022978-3-03868-177-92070-5786https://doi.org/10.2312/vcbm.20221194https://diglib.eg.org:443/handle/10.2312/vcbm20221194The 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.Attribution 4.0 International LicenseCCS Concepts: Human-centered computing → Visual analytics; Computing methodologies → Model verification and validation; Applied computing → Biological networks"Humancentered computing → Visual analyticsComputing methodologies → Model verification and validationApplied computing → Biological networks"10.2312/vcbm.20221194117-1215 pages