About ERP_CC Toolbox
This toolbox provides an opportunity to process spatio-temporal ERP data utilizing a cluster analysis methodology.
A novel consensus clustering and time-window selection mechanism has been developed for measuring the best possible time-window for measuring ERPs of interest.
Additionally, a repeated ANOVA measurement included enhancing the statistical analysis based on mean latency amplitude for the ERP of interest.
Please add MST1.0 to MATLAB path to use clustering functions provided by Andreas Trier Poulsen and cite the addressed researches in below as well:
Download from:
https://github.com/DTUComputeCognitiveSystems/Microstate-EEGlab-toolbox/tree/master/MST1.0
Please cite this toolbox as:
Poulsen, A. T., Pedroni, A., Langer, N., & Hansen, L. K. (2018). Microstate EEGlab toolbox: An introductionary guide. bioRxiv.
Andreas Trier Poulsen, atpo@dtu.dk Technical University of Denmark, Cognitive systems - February 2017
We are sorry to state that, some functions are encrypted temporary, We will update the current version as we could publish the related works. We hope you kindly understand us and patiently wait for our final version update.
Inputs: Information about the ERP data such as number of groups, Number of Stimuli, number of subjects, number of components, number of time samples, start time (ms), End time (ms), and more important experimental measurement time-window.
Outputs: Time-windows for conditions/groups, Topographical maps and waveform plots, Statistical power analysis results.
Updated in Aug 2019