This repo contains code for evaluating forward encoding models of animals, actions, and scenes using fMRI data collected while participants viewed the Life nature documentary

• google docs "life encoding project"
• Cara's frontier's paper (2018)
• Cara's "data": /idata/DBIC/cara/life/
• Cara's "code": /ihome/cara/frontiers_18w/life/forward_encoding/
• New Discovery path: /dartfs/rc/lab/D/DBIC/DBIC/f0042x1/life-encoding

idata/DBIC/cara/life
├──  data
│     ├── annotations 
│     │    └── 4 files: annotations_1.csv
│     └── audio 
│          └── 4 files: annotations_1.csv
│     
├──  pymvpa
│     ├── search_hyper_mappers_life_mask_nofsel_lh_leftout_1.hdf5
│     ├── ...
│     └── search_hyper_mappers_life_mask_nofsel_rh_leftout_4.hdf5
│
├──  ridge
│     ├── avg_corrs (e.g. annotations_1.csv)
│     ├── models (e.g. life_part1.wav)
│     ├── incomplete
│     ├── niml
│     └── only actions.npy     only_animals.npy               only_bg.npy            
│     
└──  semantic_cat
      ├── actions_bg.npy       bg_animals.npy                 faces.npy
      ├── actions.npy          bg.npy                         objects.npy
      ├── all.npy              body_parts.npy                 places.npy
      ├── animals_actions.npy  body_parts_strict_animals.npy  strict_animals_faces.npy
      └── animals.npy          faces_body_parts.npy           strict_animals.npy

• Anatomical
• Hyperalignment

/idata/DBIC/snastase/life

• Data in this directory is later used by the code ridge_regression.py
• This code runs both aa, ws, ha (common/participant specific)g
• For the ha, the hyperaligned mappers are saved in /idata/DBIC/cara/life/pymvpa/

Cara has, of course, run the models and the results can be found in the following directories:

• Anatomical data: /idata/DBIC/cara/models/aa/visual/all/leftout_run_1/sub-rid000001/lh
• Hyperalignment data: /idata/DBIC/cara/models/ha_testsubj/visual/all/leftout_run_1/sub-rid00000*
• Within Subject data: /idata/DBIC/cara/models/ws/visual/all/leftout_run_1/sub-rid000001/lh

• word2vector

• Behavior
• Taxonomy
• Scene

• Behavior
• Taxonomy
• Scene
• Behavior & Taxonomy
• Behavior & Scene
• Taxonomy & Scene
• Behavior & Taxonomy & Scene

• Behavior
• Taxonomy
• Scene
• Behavior & Taxonomy
• Behavior & Scene
• Taxonomy & Scene
• Behavior & Taxonomy & Scene

• Behavior
• Taxonomy
• Scene
• Behavior & Taxonomy
• Behavior & Scene
• Taxonomy & Scene
• Behavior & Taxonomy & Scene

• Behavior
• Taxonomy
• Scene
• Behavior & Taxonomy
• Behavior & Scene
• Taxonomy & Scene
• Behavior & Taxonomy & Scene