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.
| 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 |
| DOI: | https://doi.org/10.2312/vcbm.20221194 |
