This README provides a brief documentation for the code and data provided in this repository that is linked with the following publication:
A. von Lühmann, A. Ortega-Martinez, D.A. Boas and M.A. Yücel, 2020, Using the General Linear Model to Improve Performance in fNIRS Single Trial Analysis and Classification: A Perspective, Frontiers in Human Neuroscience, vol. 14, no. 30, doi: https://doi.org/10.3389/fnhum.2020.00030
Please cite this work when using any of the presented methods or code.
.../aux functions
- auxilliary functions
.../Homer functions
- processing functions from the homer2 toolbox that our scripts are dependent on. The full toolbox can be downloaded here
.../lit rev data
- the data and function for generating the pie-charts in the paper
.../main
- contains the analysis scripts and functions to generate the main results and corresponding figures from the manuscript.
.../sim HRF
- contains synthetic HRF templates and function to augment fNIRS resting data to generate the ground truth data used for the evaluation.
The following list points to the analysis scripts that generate the results and figures of the publication:
- Figure 1: .../lit rev data/create_piecharts.m
- Figure 2: .../aux functions/generate_Fig2_signals.m
- Figure 3: .../lit rev data/create_piecharts.m
- Figure 7a: .../main/plot_Features_SSvsNo.m
- Figure 7b: .../aux functions/generate_Fig7_right_panel.m
- Figure 8: .../lit rev data/create_piecharts.m
- Figure 9: .../main/plot_Features_SSvsNo.m
- Figure 10: .../lit rev data/create_piecharts.m
- Figure 11: .../main/plot_Features_SSvsNo.m
- Figure 12: .../main/classify_SSvsNo.m - please note that this code depends on the BBCI toolbox that you can find here