This program show individual-difference reflection (IDR) of predictted-response decoding for measured-response decoding.
.
├── data
│ ├── TVAdMovieSet
│ │ └── {subject}
│ │ ├── SceneDescription
│ │ ├── ImpressionRatings
│ │ └── AdEffectivenessIndices
│ ├── WebAdMovieSet
│ │ └── {subject}
│ │ ├── SceneDescription
│ │ ├── ImpressionRatings
│ │ ├── AdPreferenceVotes
│ │ └── PreferenceRatings
│ └── subject_data.scv
├── (result)
│ ├── TVAdMovieSet
│ └── WebAdMovieSet
├── config.py
├── labels.py
├── pair_dist.py
├── plot.ipynb
├── plot.py
├── subject_selector.py
└── util.py
There are two different sets of movies, with multiple categories.
We provide predicted decodings by measured and predicted voxel response.
- Web ad movie set
- Scene descriptions (data/WebAdMovieSet/{subject}/SceneDescription/, 40 subjects)
- Impression ratings (data/WebAdMovieSet/{subject}/ImpressionRatings/, 40 subjects)
- Ad effectiveness indices (data/WebAdMovieSet/{subject}/AdEffectivenessIndices/, 40 subjects)
- TV ad movie set
- Scene descriptions (data/TVAdMovieSet/{subject}/SceneDescription/, 28 subjects)
- Impression ratings (data/TVAdMovieSet/{subject}/ImpressionRatings/, 28 subjects)
- Ad preference votes (data/TVAdMovieSet/{subject}/AdPreferenceVotes/, 28 subjects)
- Subjective preference ratings (data/TVAdMovieSet/{subject}/PreferenceRatings/, 14 subjects)
※In subjective preference ratings, IDR is also calculated for manual ratings, which were annotated from fMRI subjects.
Execute plot.py. The result pictures will be stored in result/
directory.
Option | Choices | Description |
---|---|---|
-m | web tv | Movie set as stimlus |
-t | sd ir ae ap pr | Task decoded by predicted- and measured-response decoding |
python pair_dist.py -m web tv -t sd ir ae ap pr
You can execute the same program as above with plot.ipynb.
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