This code was used for the binocular coordination experiment data analysis.
Run the file "MonoBinoActivityPlot.m". The right side of the GUI shows several parameters which can be used to only run the code on a specific subset of data (spatial location or
correlation with the regressors used during the ROI selection (Kubo et al., 2014; Miri et al., 2011; Method section in the paper)). The code was run with the current initiation 
parameters which ensure that all ROIs were analyzed. One can further change the frames when the monocular left and right eye and binocular stimulation was started (leave as it is
due to data structure).Regressor threshold is the minimal coefficient that must be reached to ensure an ROI is used in further analysis. 
Run the code by clicking "Load to identify neurons". Select all the R-files in the general data folder for the MonoBino experiment and click "open". Now, select all the Exportmat files
and open them (might take some time). Then specify a path where the data should be saved to in the Matlab command window and press "enter". Press "Go" in the GUI and the code will
run the correlation analysis. When this step is completed click "Load to analyze neurons" and select the same R-files from the first step. Then load the "AllAutomatedNeuronsWithoutType54.mat"-
file generated in the first step (This file contains only neurons where the minimal correlation coefficient was reached, might take some time) and specify a save path when prompted. 
Then click the "Go" button to run the firing thresholds analysis (figure 8 position, figure 9 velocity). The resulting file "AutomatedRegressorRevised.mat" contains all the neurons
analyzed in the manuscript. The code was run with the start-up initiation parameters using MATLAB R2015a.