|32 bit||64 bit||(32/64 bit only for shared object/DLL)|
|cocogui.jar||(345 kb)||executable Java archive, full GUI|
|CoCoGUI.sh||(1 kb)||CoCoGUI.bat||(1 kb)||start scripts for Linux and Windows|
|libJNICoCo.so||(383 kb)||libJNICoCo.so||(391 kb)||GNU/Linux shared object, JNI|
|JNICoCo.dll||(72 kb)||JNICoCo.dll||(93 kb)||Windows dynamic link library, JNI|
|cocogui.zip||(2195 kb)||cocogui.tar.gz||(1955 kb)||Java sources, version 1.17 (2016.10.05)|
|jnicoco.zip||(304 kb)||jnicoco.tar.gz||(284 kb)||C sources, version 1.28 (2016.11.18)|
|trains.txt||(67 kb)||Example parallel spike trains file|
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 2017 (see under "Other Tools and Frameworks") installed, as the program was compiled with Microsoft Visual Studio 2017.
More information about the CoCoNAD algorithm can be found in the following papers:
A description of the methods of pattern spectrum filtering and pattern set reduction can be found in the following papers:
Pattern spectrum estimation is described in the following paper: