neurosparse

Folders map

• Two main folders, one for each dataset
  • IMAGES_BLOCK_MASK: Block-design experiment, with voxels filtering according to probability of belonging to gray matter. This is the dataset used in the paper.
  • IMAGES_EVENT_MASK: Event-design experiment, with voxels filtering according to probability of belonging to gray matter.
  • SOLVERS: contains the optimization solvers.
  • UTILITIES: containes auxiliary functions, such as for thresholding solutions and the NIFTI toolbox for Matlab.
• Each dataset folder contains subfolders for data and for each of the models, e.g., LASSO, ENET, SLAP.
• Each of the models' folders contain the Matlab functions to run the numerical experiment:
  • MODEL_val.m runs the folds of the internal LOSO loop.
  • MODEL_train.m runs the folds of the external LOSO loop, using the results obtained via MODEL_val.m.
  • Both functions require as input argument the number of the fold to execute, as a string, to allow naïve parallel processing.
  • compute_results_MODEL.m computes all the performance metrics and saves them into RESULTS_TRAIN\MODEL_esults.mat.