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# GLMdenoise

GLMdenoise is a MATLAB toolbox for analyzing and denoising task-based fMRI data.
It is developed by Kendrick Kay ([email protected]).

To use the toolbox, add it to your MATLAB path:
  addpath(genpath('GLMdenoise'));

To try the toolbox on an example dataset, change to the GLMdenoise directory 
and then type:
  example1;
This script will download the example dataset (if it has not already been
downloaded) and will run the toolbox on the dataset.

For additional information, please visit:
  http://kendrickkay.net/GLMdenoise/

Terms of use: This content is licensed under a Creative Commons Attribution 3.0 
Unported License (http://creativecommons.org/licenses/by/3.0/us/). You are free 
to share and adapt the content as you please, under the condition that you cite 
the appropriate manuscript (see below).

If you use GLMdenoise in your research, please cite the following paper:
  Kay KN, Rokem A, Winawer J, Dougherty RF and Wandell BA (2013) 
    GLMdenoise: a fast, automated technique for denoising task-based fMRI data.
    Front. Neurosci. 7:247. doi: 10.3389/fnins.2013.00247

History of major code changes:
- 2014/08/01:
    Version 1.4.
    - Add option for obtaining parametric GLM fits and error estimates.
    - Add new DVARS sanity-check figures.
    - Change the polynomial functions such that they are all mutually orthogonal
      and unit-length.  This may cause slight changes to behavior due to numerical
      precision issues.
- 2014/07/14:
    Version 1.31.
    - Minor fixes to improve platform compatibility.
    - Add additional input flexibility.
- 2013/12/13:
    Version 1.3.
    - Added new example scripts.
- 2013/11/18:
    Version 1.2.
    - The default canonical HRF has changed.  (It is now smoother/nicer than before.)
    - Add additional input flexibility.
    - If pcvoxels is determined to be empty (e.g. no voxels were above 0% for any number
      of PCs), we now issue a warning (instead of crashing) and fallback to simply using 
      the top 100 voxels to select the number of PCs.
    - Change the colormap scaling for the PCcrossvalidationscaled*.png figures.
    - Use fullfile to ensure compatibility with different platforms.
    - In GLMestimatemodel.m, we now use the same default for opt.maxpolydeg that is
      used in GLMdenoisedata.m (instead of defaulting to 2).
    - Various small tweaks.
- 2013/05/12:
    Version 1.1.
    - The experimental design can now be specified in terms of onset times.
      This means that conditions do not have to exactly coincide with the TRs.
    - Fixed a bug concerning extraregressors.
    - Additional optional inputs, additional outputs, and additional figures.
    - All-zero regressors (e.g. encountered via bootstrapping) are now assigned zero weight.
- 2012/12/03 - Version 1.02. Various speed-ups and minor bug fixes.
- 2012/11/24 - Version 1.0.

## CONTENTS

Contents:
- example*.m - Example scripts
- exampledataset.mat - Example dataset
- GLMdenoisedata.m - The main top-level function that you probably want to call
- GLMestimatemodel.m - Another top-level function that you may call
- GLMpredictresponses.m - Another top-level function that you may call
- README - The file you are reading
- setup.m - A simple script that downloads the example dataset
            and adds GLMdenoise to the MATLAB path
- utilities - A directory containing various utility functions

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

Copyright (c) 2012, Kendrick Kay
All rights reserved.

Redistribution and use in source and binary forms, with or without
modification, are permitted provided that the following conditions are met:

Redistributions of source code must retain the above copyright notice, this
list of conditions and the following disclaimer.

Redistributions in binary form must reproduce the above copyright notice, this
list of conditions and the following disclaimer in the documentation and/or
other materials provided with the distribution.

Neither the name of Stanford University nor the names of its contributors may be
used to endorse or promote products derived from this software without specific
prior written permission.

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