Skip to main content
SpringerLink
Log in

Towards an Explorative Visual Analysis of Cortical Neuronal Network Simulations

  • Conference paper
  • First Online:
Brain-Inspired Computing (BrainComp 2013)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 8603))

Included in the following conference series:

Abstract

In neuroscientific analysis, visualization researchers have traditionally concentrated on medical imaging and microscopy data. While the visualization of experimental neuroscientific data is consequently on its way turning out increasingly mature tools, solutions for a visual analysis of neuroscientific simulation data are still in their infancy. For the assessment of large-scale neuronal network simulations, correlations between the brain's structure, function, and connectivity at the different temporal as well as spatial scales will have to be identified. The analysis of such "in silico experiments" requires immediate access to a number of heterogeneous data sources, e.g. connectivity information, spiking behavior of individual neurons, populations of neurons or entire brain regions. To address these requirements, we introduce a prototype of an interactive tool for the visual analysis of neuronal network models simulated via NEST. The tool strictly follows a multi-view approach, combining geometrical as well as abstract views to the data at multiple scales. Furthermore, we will discuss design parameters for adequate high-fidelity analysis workplaces, focusing on high-resolution or even immersive displays.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  • Carnevale, N.T., Hines, M.L.: The NEURON Book. Cambridge University Press, Cambridge (2006)

    Book  Google Scholar 

  • Cruz-Neira, C., Sandin, D.J., DeFanti, T.A., Kenyon, R.V., Hart, J.C.: The CAVE: Audio visual experience automatic virtual environment. Commun. ACM 35(6), 64–72 (1992)

    Article  Google Scholar 

  • Dercksen, V., Oberlaender, M., Sakmann, B., Hege, H.-C.: Interactive visualization – a key prerequisite for reconstruction of anatomically realistic neural networks. In: Linsen, L., Hagen, H., Hamann, B., Hege, H.-C. (eds.) Visualization in Medicine and Life Sciences II, pp. 27–44. Springer, Berlin (2012)

    Google Scholar 

  • Gewaltig, M.-O., Diesmann, M.: NEST (NEural Simulation Tool). Scholarpedia 2(4), 1430 (2007)

    Article  Google Scholar 

  • Gerhard, S., Daducci, A., Lemkaddem, A., Meuli, R., Thiran, J.P., Hagmann, P.: The connectome viewer toolkit: an open source framework to manage, analyze, and visualize connectomes. Front. Neuroinform. 5, 3 (2011)

    Google Scholar 

  • Haber, R.B., McNabb, D.A.: Visualization idioms: A conceptual model for scientific visualization systems. In: Shriver, B., Neilson, G.M., Rosenblum, L.J. (eds.) Visualization in Scientific Computing, pp. 74–93. IEEE Computer Society Press, Los Alamitos (1990)

    Google Scholar 

  • Hadwiger, M., Beyer, J., Jeong, W.-K., Pfister, H.: Interactive volume exploration of petascale microscopy data streams using a visualization-driven virtual memory approach. IEEE Trans. Vis. Comput. Graph. 18(12), 2285–2294 (2012)

    Article  Google Scholar 

  • Hentschel, B., Tedjo, I., Probst, M., Wolter, M., Behr, M., Bischof, C., Kuhlen, T.: interactive blood damage analysis for ventricular assist devices. IEEE Trans. Vis. Comput. Graph. 14(6), 1515–1522 (2008)

    Article  Google Scholar 

  • Hernando, J., Schürmann, F., Pastor, L.: Towards real-time visualization of detailed neural tissue models: view frustum culling for parallel rendering. In: IEEE Symposium on Biological Data Visualization (BioVis), pp. 25–32 (2012)

    Google Scholar 

  • Jeong, W., Beyer, J., Hadwiger, M., Vazquez, A., Pfister, H., Whitaker, R.T.: Scalable and interactive segmentation and visualization of neural processes in EM datasets. IEEE Trans. Vis. Comput. Graph. 15(6), 1505–1514 (2009)

    Article  Google Scholar 

  • Laha, B., Sensharma, K., Schiffbauer, J.D., Bowman, D.A.: Effects of immersion on visual analysis of volume data. IEEE Trans. Vis. Comput. Graph. 18(4), 597–606 (2012)

    Article  Google Scholar 

  • Laha, B., Bowman, D.A., Socha, J.J.: Effects of VR system fidelity on analyzing isosurface visualization of volume datasets. IEEE Trans. Vis. Comput. Graph. 20(4), 513–522 (2014)

    Article  Google Scholar 

  • Lasserre, S., Hernando, J., Hill, S., Schürmann, F., De Miguel Anasagasti, P., Jaoude, G., Markram, H.: A neuron membrane mesh representation for visualization of electrophysiological simulations. IEEE Trans. Vis. Comput. Graph. 18(2), 214–227 (2012)

    Article  Google Scholar 

  • LaTorre, A., Alonso-Nanclares, L., Muelas, S., Peña, J.M., DeFelipe, J.: Segmentation of neuronal nuclei based on clump splitting and a two-step binarization of images. Expert Syst. Appl. 40(16), 6521–6530 (2013)

    Article  Google Scholar 

  • Morales, J., Alonso-Nanclares, L., Rodríguez, J.R., DeFelipe, J., Rodríguez, Á., Merchán-Pérez, Á.: Espina: a tool for the automated segmentation and counting of synapses in large stacks of electron microscopy images. Front. Neuroanat. 5, 18 (2011)

    Article  Google Scholar 

  • Nordlie, E., Plesser, H.E.: Visualizing neuronal network connectivity with connectivity pattern tables. Front. Neuroinformat. 3, 39 (2010)

    Google Scholar 

  • Nowke, C., Schmidt, M., van Albada, S., Eppler, J., Bakker, R., Diesmann, M., Hentschel, B., Kuhlen, T.: VisNEST – Interactive analysis of neural activity data. In: IEEE Symposium on Biological Data Visualization (in Conjunction with IEEE VIS 2013), pp. 65–72 (2013)

    Google Scholar 

  • Rick, T., von Kapri, A., Caspers, S., Amunts, K., Zilles, K., Kuhlen, T.: Visualization of probabilistic fiber tracts in virtual reality. In: J. Westwood et al. (eds.) Studies in Health Technology and Informatics, vol. 163, pp. 486–492. IOS Press, Amsterdam (2011)

    Google Scholar 

  • da Silva, M., Zhang, S., Demiralp, C., Laidlaw, D.: Visualizing diffusion tensor volume differences. In: IEEE Visualization Conference (2001)

    Google Scholar 

  • Roberts, M., Jeong, W., Vazquez-Reina, A., Unger, M., Bischof, H., Lichtman, J., Pfister, H.: Neural process reconstruction from sparse user scribbles. In: IEEE Symposium on Biological Data Visualization (BioVis) (2011)

    Google Scholar 

  • Schmitt, S., Evers, J.F., Duch, C., Scholz, M., Obermayer, K.: New methods for the computer-assisted 3D Reconstruction of Neurons from Confocal Image Stacks. NeuroImage 23(4), 1283–1298 (2004)

    Article  Google Scholar 

  • Weinstein, D.M., Kindlmann, G.L., Lundberg, E.C.: Tensorlines: Advection-diffusion based propagation through diffusion tensor fields. In: IEEE Visualization Conference, pp. 249–253 (1999)

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Forschungszentrum Jülich, Jülich Supercomputing Centre, 52425, Jülich, Germany

    Torsten Wolfgang Kuhlen

  2. Virtual Reality Group, Department of Computer Science, RWTH Aachen University, Seffenter Weg 23, 52074, Aachen, Germany

    Bernd Hentschel

  3. JARA – High-Performance Computing, RWTH Aachen University, Schinkelstraße 2, 52062, Aachen, Germany

    Torsten Wolfgang Kuhlen & Bernd Hentschel

Authors
  1. Torsten Wolfgang Kuhlen
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Bernd Hentschel
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Torsten Wolfgang Kuhlen .

Editor information

Editors and Affiliations

  1. Faculty of Engineering, University of Calabria, Arcavacada di Rende, Italy

    Lucio Grandinetti

  2. Jülich Supercomputing Centre, Jülich, Germany

    Thomas Lippert

  3. Computing Science, University of Groningen Institute for Mathematics &, Groningen, The Netherlands

    Nicolai Petkov

Rights and permissions

Reprints and permissions

Copyright information

© 2014 Springer International Publishing Switzerland

About this paper

Cite this paper

Kuhlen, T.W., Hentschel, B. (2014). Towards an Explorative Visual Analysis of Cortical Neuronal Network Simulations. In: Grandinetti, L., Lippert, T., Petkov, N. (eds) Brain-Inspired Computing. BrainComp 2013. Lecture Notes in Computer Science(), vol 8603. Springer, Cham. https://doi.org/10.1007/978-3-319-12084-3_14

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-12084-3_14

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-12083-6

  • Online ISBN: 978-3-319-12084-3

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation