-
Notifications
You must be signed in to change notification settings - Fork 1
/
README
15 lines (8 loc) · 1.38 KB
/
README
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
For the configuration and main entrance, please run `python face_0_main.py`.
`face_1_prep.py` is for preprocessing. Note that we provide a flag `cfg['auto_flag']` to control whether the preprocessing is done automatically or manually. This flag should be set to `cfg['auto_flag']=True`, to avoid bulky manual work.
`face_2_dec.py` is for SVM decoding, including SVM decoding for temporal dynamics, temporal generalization, and SVM decoding in the test-retest section.
`face_3_rsa.py` is for representational similarity analysis.
`face_4_stat.py` is for some statistical tests.
`face_6_bayes.m` is used to run Bayesian model selection. It should be run manually as the main entrance `face_0_main.py` only includes steps `1` to `4`. Before running this Matlab script, ensure you have installed [VBA toolbox](https://github.com/MBB-team/VBA-toolbox) in your search path.
Note that all of the preprocessed data and intermediate results are placed in the `derivatives` folder (of course you could change it to wherever you want simply by referring to the configuration in `face_0_main.py`).
In the `./code/experiment` folder is the script for the experiment. Before running the experiment, ensure you have set up [Psychtoolbox](https://github.com/Psychtoolbox-3/Psychtoolbox-3) correctly in the Matlab searching path. The usage is detailed in `main.m`. The stimuli are placed in the `./stimuli/meg` folder.