The code used in the master thesis project "Resting State EEG in Computational Psychiatry".

main_runOnce: runs the following scripts:

• utils_runOnce_sourceLocalization: Uses preprocessed data (channels x time) and source localize it (brain areas x time).
• utils_runOnce_connectivity: Uses the source localized data (brain areas x time) and calculates a connectivity matrix. Saves the upper half of the connectivty matrix for each subject ((brain areas x (brain areas-1)) / 2). Also saves the average connectivity matrix and the variance for group 0 and 1 and the 't-statistics' between the groups.
• utils_runOnce_classification: Uses the connectivity measures ((brain areas x (brain areas-1)) / 2) and try to classify wether subject are group 0 or 1.

main_resultsConnectivity: plots results regarding the connectivity measures.

• utils_resultsConnectivity: the functions used to plot.

main_resultsClassification: plots and prints results regarding the classification.

• utils_resultsClassificationy: the functions used to plot and print.

utils_joint: functions jointly used across several different scripts.

univariate_ttest: code that makes a univariate t-test between the connectivity matrices of group 0 and 1.

parameter_optimization: code to run to visualze effect of parameter intervals for the classification parameter and thereby optimize it.

QualityCheck: Code that plots preprocessed data to visually check the quality.

understandConnectivityMeasures: Code to visualize and understand different connectivity measures.

runPreprocess: preprocess the raw EEG data