The physiological effects of non-invasive brain stimulation fundamentally differ across the human cortex

### Data
Twenty-three healthy participants underwent three counterbalanced rTMS-fMRI sessions on different days, where a prefrontal (FRO), an occipital (OCC) and a temporo-parietal control (CTR) region were identically stimulated with low-frequency (1Hz) rTMS. We measured brain activity with resting state-fMRI before (rest-pre) and immediately after stimulation (rest-post). All data is anonymized and the structural T1 images were defaced with [pydeface](https://github.com/poldracklab/pydeface).

### Analysis

The folder **code** contains the scripts and configuration files used for the data analysis, this is the description of each file:

* *pipeline_config_cpac_v0.3.9.2.yml* (YAML): Configuration file pipeline for CPAC v0.3.9.2 which runs the pre-processing, FC, timeseries generation and local signal analysis.
* *cpac_file_processor.sh* (Bash): Extracts and organizes the files from CPAC's output for the statistical analysis (e.g. FC, fALFF).
* *anova_rm_spm_batch.mat* (Matlab): SPM's batch configuration file for the one-way repeated measures ANOVA second level analysis.
* *spm_contrast_vis.py* (Python): Visualizes the statistically significant contrast's images by overlaying them on a glass brain representation.
* *cons_mod_calc.m* (Matlab): Extracts the timeseries generated by CPAC and runs the consensus modularity analysis. The output of this script provides the input for the scripts below
* *cons_mod_stats_vis.py* (Python): Visualizes and runs the statistical analysis on the consensus modularity analysis results.
* *cv_classifier.py* (Python): Extracts the features and run the cross-validated classification on them.
* *sDCM*.m* (Matlab): run the spectral DCM analysis on the extracted timeseries.