Density visualization pipeline: a tool for cellular and network density visualization and analysis
- Neuron classification is an important component in analyzing network structure and quantifying the effect of neuron topology on signal processing. Current quantification and classification approaches rely on morphology projection onto lower-dimensional spaces. In this paper a 3D visualization and quantification tool is presented. The Density Visualization Pipeline (DVP) computes, visualizes and quantifies the density distribution, i.e., the “mass” of interneurons. We use the DVP to characterize and classify a set of GABAergic interneurons. Classification of GABAergic interneurons is of crucial importance to understand on the one hand their various functions and on the other hand their ubiquitous appearance in the neocortex. 3D density map visualization and projection to the one-dimensional x, y, z subspaces show a clear distinction between the studied cells, based on these metrics. The DVP can be coupled to computational studies of the behavior of neurons and networks, in which network topology information is derived from DVP information. The DVP reads common neuromorphological file formats, e.g., Neurolucida XML files, NeuroMorpho.org SWC files and plain ASCII files. Full 3D visualization and projections of the density to 1D and 2D manifolds are supported by the DVP. All routines are embedded within the visual programming IDE VRL-Studio for Java which allows the definition and rapid modification of analysis workflows.
Author: | Stephan Grein, Guanxiao Qi, Gillian Queisser |
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URN: | urn:nbn:de:hebis:30:3-553287 |
DOI: | https://doi.org/10.3389/fncom.2020.00042 |
ISSN: | 1662-5188 |
Parent Title (English): | Frontiers in computational neuroscience |
Publisher: | Frontiers Research Foundation |
Place of publication: | Lausanne |
Document Type: | Article |
Language: | English |
Date of Publication (online): | 2020/06/26 |
Date of first Publication: | 2020/06/26 |
Publishing Institution: | Universitätsbibliothek Johann Christian Senckenberg |
Release Date: | 2020/08/11 |
Tag: | GABAergic; barrel cortex; density maps; density visualization; interactive data analysis; neuronal morphology; synaptogenesis; visual programming |
Volume: | 14 |
Issue: | art. 42 |
Page Number: | 16 |
First Page: | 1 |
Last Page: | 16 |
Note: | This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. |
HeBIS-PPN: | 470984260 |
Institutes: | Informatik und Mathematik |
Dewey Decimal Classification: | 0 Informatik, Informationswissenschaft, allgemeine Werke / 00 Informatik, Wissen, Systeme / 004 Datenverarbeitung; Informatik |
Sammlungen: | Universitätspublikationen |
Open-Access-Publikationsfonds: | Informatik und Mathematik |
Licence (German): | Creative Commons - Namensnennung 4.0 |