CoCoGUI - CoCoNAD GUI + PSF + PSR

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Description

CoCoGUI is a graphical user interface for the CoCoNAD algorithm, as it is (also) implemented as a command line program, which is a tool for the analysis of parallel spike trains with the objective of identifying synchronous spiking activity / neural assemblies. CoCoGUI also implements the methods of pattern spectrum filtering and pattern set reduction as described in Picado-Muiño et al. 2013 and Torre et al. 2013. Furthermore, it is equipped with viewers for parallel spike trains (as a simple dot display) and for the pattern spectrum (as a bar chart or a 3-dimensional scatter plot).

Full description of this program.

If instead of the graphical user interface that the CoCoGUI program provides, a command line interface is desired, the Python scripts in the psf+psr archives on the PyCoCo page are worth looking at.

If you have trouble executing the programs on Microsoft Windows, check whether you have the Microsoft Visual C++ Redistributable for Visual Studio 2022 (see under "Other Tools and Frameworks") installed, as the program was compiled with Microsoft Visual Studio 2022.

References

More information about the CoCoNAD algorithm can be found in the following papers:

• Frequent Item Set Mining for Sequential Data: Synchrony in Neuronal Spike Trains
  David Picado-Muiño and Christian Borgelt
  Intelligent Data Analysis 18(6):997-1012.
  IOS Press, Amsterdam, Netherlands 2014
  doi:10.3233/IDA-140681 iospress.com
  (16 pages)
• Finding Frequent Patterns in Parallel Point Processes
  Christian Borgelt and David Picado-Muiño
  Proc. 12th Int. Symposium on Intelligent Data Analysis, 116-126.
  Springer-Verlag, Berlin/Heidelberg, Germany 2013
  ida_13.pdf (443 kb) ida_13.ps.gz (491 kb) (11 pages)

A description of the methods of pattern spectrum filtering and pattern set reduction can be found in the following papers:

• Finding Neural Assemblies with Frequent Item Set Mining
  David Picado-Muiño, Christian Borgelt, Denise Berger, George Gerstein, and Sonja Grün
  Frontiers in Neuroinformatics 7:article 9
  Frontiers Media, Lausanne, Switzerland 2013
  doi:10.3389/fninf.2013.00009 frontiersin.org
  accfim.pdf (1797 kb) accfim.ps.gz (772 kb) (14 pages)
• Statistical Evaluation of Synchronous Spike Patterns Extracted by Frequent Itemset Mining
  Emiliano Torre, David Picado-Muiño, Michael Denker, Christian Borgelt, and Sonja Grün
  Frontiers in Computational Neuroscience, 7:article 132
  Frontiers Media, Lausanne, Switzerland 2013
  doi:10.3389/fncom.2013.00132 frontiersin.org
  (13 pages)

Pattern spectrum estimation is described in the following paper:

• Simple Pattern Spectrum Estimation for Fast Pattern Filtering with CoCoNAD
  Christian Borgelt and David Picado-Muiño
  Proc. 13th Int. Symposium on Intelligent Data Analysis, 37-48.
  Springer-Verlag, Berlin/Heidelberg, Germany 2014
  ida_14.pdf (1224 kb) ida_14.ps.gz (1190 kb) (11 pages)