|32 bit||64 bit||(32/64 bit only for shared object/DLL)|
|cocogui.jar||(282 kb)||executable Java archive, full GUI|
|CoCoGUI.sh||(1 kb)||CoCoGUI.bat||(1 kb)||start scripts for Linux and Windows|
|libJNICoCo.so||(387 kb)||libJNICoCo.so||(395 kb)||GNU/Linux shared object, JNI|
|JNICoCo.dll||(72 kb)||JNICoCo.dll||(94 kb)||Windows dynamic link library, JNI|
|cocogui.zip||(1951 kb)||cocogui.tar.gz||(1765 kb)||Java sources, version 1.17 (2016.10.05)|
|jnicoco.zip||(303 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 program on Microsoft Windows, check whether you have the Microsoft Visual C++ Redistributable Packages for Visual Studio 2015 installed, as the library was compiled with Microsoft Visual Studio 2015.
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: