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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.

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