New Features
GroupICAT v2.0d (March 31, 2010):
- Added data pre-processing options like intensity normalization, variance normalization and removing mean
time-series. Intensity normalization is recommended for maximizing the reliability and replicability of the
components. Please see abstract for more detalis.
- Added expectation maximization option to PCA computation (S.Roweis, "EM
algorithms for PCA and sensible PCA", Advances in Neural Information Processing
Systems. 1998). EM PCA has fewer memory constraints
compared to covariance based PCA and is the preferred method for very large data-set analysis.
- All the subsequent analysis MAT files after PCA with the exception of ICASSO will be converted to single
precision if you have selected single precision in the PCA options. This is recommended for maximizing the
number of data sets given a fixed amount of RAM.
- GICA3 back reconstruction method was released as an update to GroupICAT
v2.0c. GICA3 is the recommended method for reconstructing individual subject
components with the most accurate spatial maps and timecourses. GICA3 has two
desirable properties that the sum of the subject spatial maps is the aggregate
spatial map and the product of the time courses and spatial maps estimate the
data to the accuracy of the PCA's. We have performed extensive comparison with 3
different PCA/data-reduction approaches and 4 back-reconstruction approaches
including spatio-temporal regression/dual regression. These approaches are
included as options in GIFT. Please see abstract for more details.
- Component images sign in ICA is flipped based on the skewness measure of the distribution (previously it was
flipped based upon the maximum voxel).
- Subject component image distributions are centered to zero by default when scaling component images. Centering is done based on the peak of the distribution.
- "icatb_mem_ica.m" script is updated to include all the data reduction strategies and will give a close estimate
of how much RAM is required for all the analysis types.
- ICASSO can now be acessed from Setup ICA GUI.
- Dimensionality estimation source code ("icatb_estimate_dimension.m") developed by Leo Li is now available.
- Batch script doesn't read "numOfPC3" variable if only two data reduction steps are used.
- Bug was fixed in the back reconstruction code (GroupICAT v2.0c Updates, March 11, 2010) to handle "Constrained ICA (Spatial)" algorithm.
- Covariance options is replaced with PCA options and will be available when you select the PCA type in Setup
ICA GUI.
GroupICAT v2.0c (August 17, 2009):
- Enabled two data reduction steps in Setup ICA when the number of subjects is greater than 10.
- Two data reduction steps method is handled better in terms of memory usage for analyzing very large datasets.
- Added C-MEX files for computing eigen values of a symmetric matrix using packed storage scheme (this approach is slightly slower, but less memory intensive).
- Added spatial-temporal back reconstruction approach (this is an alternative approach to back-reconstruction and computes a spatial regression of the aggregate component images onto each timepoint of the single subject data and then computes a temporal regression of the single subject component timecourses onto each voxels timecourse).
Overall results are quite similar to back-reconstruction using the
PCA de-whitening matrix, however for the most accurate estimates of spatial
maps we recommend GICA3.
GroupICAT v2.0b (April 02, 2009):
- Single trial amplitudes utility based on Dr. Tom Eichele's work is now added to the GIFT toolbox.
- Added an option in the batch script to select the input data using regular expression pattern match. This can be used to get
the directories that are highly nested.
- We remove the limitation to use MATLAB Statistics toolbox in order to compute statistics on the time courses.
- Added Multiple Regression design criteria in the Stats on time courses GUI.
- Percent variance calculation is added in the Utilities Section.
GroupICAT v2.0a (April 11, 2008):
- We now provide EEGIFT toolbox for analyzing group ICA on EEG data (By Tom
Eichele). EEGIFT contains options for importing data in .SET format from EEGLAB and
visualization methods for viewing group ICA components. Both GIFT and EEGIFT are
subsumed within GroupICAT v2.0a.
- Temporal sorting in GIFT is optimized. We load .MAT files for individual subject components instead of using time course images.
- Event average using deconvolution method (By Tom Eichele) is implemented.
- Event average utility in main figure window now has the options for selecting multiple regressors and components. Event average results will be
written as .MAT files.
- Slider callback is optimized when very large number of time courses are plotted using "Split-timecourses" utility.
GIFT v1.3d (Dec 18, 2007):
- GUI for doing statistical testing of time courses (beta weights) is included.
- Right-left text plotted during display is changed in this version to make it consistent with SPM convention (Neurological convention).
- Flip parameter for analyze images is stored in ICA parameter file and will give a warning message whenever flip parameter is changed during display.
- Statistics are done on component images and time courses even if the time points are different.
- Latest SPM updates for volume functions are installed.
- File selection window contains an option to enter a subset of Nifti files and an edit button to change the file selection.
GIFT v1.3c (Jan 8, 2007):
- Constrained ICA (Spatial) algorithm developed by Qiu-Hua Lin is added to the GIFT toolbox.
- Default mask calculation is changed such that Boolean AND operation is performed on each data-set.
- PCA, ICA, Calibration MAT files contain only the voxels that are in the mask. Atleast 30% - 40% disk space will be saved.
- Both batch script and setup ICA GUI share the same code.
- Dimensionality estimation step is now batched.
- Display methods can now be accessed through a batch file.
- Error messages are reported with the line numbers on Matlab 7.
GIFT v1.3b (April 21, 2006):
- Now writes 3D analyze images compatible with SPM2.
- Component images are detrended while converting to Z-scores.
GIFT v1.3a (March 17, 2006) :
- Now
reads functional data in Nifti or 4D Analyze format.
- New MDL
Algorithm for estimating the number of components.
-
Pre-compiled ICA algorithms: Erica, Simbec, Jade Opac, EVD and Amuse can
now be run on Matlab 7.
- Option
is provided to compress image files to zip format (to reduce the number
of files and disk space).
-
v1.3a reads
the images from the previous version but older versions cannot read the
images written using the new version.
- Correlation,
regression, kurtosis and maximum voxel results are saved to a text file.
The text file location will be printed to the command prompt.
-
Manual is
updated to include additional examples of temporal sorting and using
output regression parameters, as well as statistical analysis of images
using SPM2.
-
Display GUI
and setup ICA GUI are changed to minimize the selection process.
-
Option is provide to
calculate stats and event average under Utilities drop down box.
GIFT v1.2d (December 5, 2005):
- Dimensionality estimation code is fixed to handle negative voxel dimensions
and PCA is run on voxels that surpass the threshold.
GIFTv1.2c with updates (November 7, 2005):
- Slices in mm are shown in Component Explorer and Composite viewer visualization
methods.
- Option is provided in temporal sorting to automatically sort components
or enter the regressor names through a text file.
GIFTv1.2c with updates (October 3, 2005):
- Fixed bug for the component time courses that look flipped after calibration.
- Removing artifacts from
the data is included.
- Temporal sorting with session specific regressors using one SPM2 design
matrix is provided.
- Detrending of ICA time courses during scaling of components is included.
GIFT v1.2c with the release date 5 July 2005:
- Data-sets can be analyzed with different number of images or scans but voxel
dimensions should be the same.
- Error checking is done when SPM2 design matrix is loaded. Number of images
of data-set is checked with the nscans field in SPM structure.
- Regressors specific to session can be selected during temporal sorting.
- Higher order detrending is provided when the components are sorted temporally.
- Multiple Regression step is optimized in sorting components.
GIFT v1.2b with the release date 18 March 2005:
- Semi-blind ICA algorithm created by Vince Calhoun is added to the toolbox.
- Data reduction step is optimized in the ICA analysis step. Estimating components
and the group ICA run faster than the previous version.
- New user interface is provided to select the reference functions while sorting
the components.
- After the components are temporally sorted using Multiple Regression as
sorting criteria, ICA Time courses can be adjusted by right clicking on the
axis. ICA time courses are adjusted by removing the nuisance parameters and
the regression coefficients other than the selected reference function.
- In the event related average option is provided to select the reference
function.
- In batch scripts option is provided to specify one design matrix for all
subjects. Components can be visualized using the Display GUI.
- Fixed bug in batch scripts when subject folder names with variable length
are specified.
GIFT v1.2a with the release date 26 November 2004:
- New user interface for Setup ICA is provided. ICA parameters and algorithms
can be easily switched. Help button is included adjacent to each parameter.
- Event related average for the ICA time course is calculated based on the
onsets of the given SPM model or design matrix.
- Time course window for multiple subjects and sessions is shown in a new
figure window with a scroll bar.
- New color maps for the composite viewer are provided. A maximum of five
different color bars are plotted.
- Batch script with two sample text files is provided. The explanation of
the parameters is given in the help manual.
- Interactive file selection window is updated to show the number of selected
files and directory history.
- Regression parameters or the coefficients are written to .mat and .txt files
when the components are sorted with Multiple Regression sorting criteria.
GIFT v1.1d with the release date 14 October 2004 (Released for the ICA
Class at the Olin Neuropsychiatry Research Center):
- Estimating number of independent components from the fMRI data is included.
The number of components estimated is shown to the user before selecting the
number of principal components.
- HTML Help Manual is provided. When the help button is pressed HTML Help
is opened in the default browser.
- Maximum Voxel sorting criteria is added to sort components spatially based
on the spatial template selected.
- Optimal ICA algorithm created by Baoming Hong and Vince Calhoun is added.
- Interactive file selection window is added instead of using the spm_get
function.
GIFT v1.01d with the release date 13 September 2004:
- Components can be spatially sorted by using a template image which contains
regions of interest. Sample templates are provided in the folder 'icatb_templates'
with names 'LeftTemplate.img' and 'RightTemplate.img'.
- All the analysis information is stored in a log file which ends with '_results.log'.
This file gets appended every time when you run the analysis with the same prefix
for the output files.
- The parameters involved in the ICA and PCA step are shown to the user when
the subject files are already selected.
- Scroll bar is provided for the edit and pop up controls in the input dialog
box for selecting the ICA options.
- Any error occurring during setting up the analysis, running the analysis
or displaying the results is shown to the user.
- Fixed bug with correlation sorting criteria - When 'temporal' is selected
in 'Select Sorting Type' option and 'Select All Subjects and Sessions' is selected
in 'What do you want to sort?' option.
- Horizontal scroll bar in all the dialog boxes is turned off.
GIFT v1.01c with the release date 20 August 2004:
- Number of partitions option in Setup ICA Analysis is turned off.
- Normalize model time course checkbox option removed for the components that
are not sorted in the figure window which will be displayed when clicked on
the time course window.
- Defaults in the 'icatb_defaults.m' file are applied to display GUI window.
Option is provided to the user to change the defaults. Time courses can be smoothed
by replacing the parameter 'SMOOTHPARA' from 'no' to 'yes' and the value can
be changed by giving different values to 'SMOOTHINGVALUE' parameter in 'icatb_defaults.m'
file.Four options for detrending time courses are provided in case of sorting
with the Multiple Regression sorting criteria.
- The 'DETRENDNUMBER' parameter in 'icatb_defaults.m' file can be changed
from '0' to '3' depending on the type of detrending you want to do. Comments
are included in the 'icatb_defaults.m' file which explains what 'DETRENDNUMBER'
means.
GIFT v1.01b with the release date 28 July 2004:
- Fixed bug for the components to be sorted when you use combination of "No
design matrix" in the Setup ICA Analysis and "select model for every subject"
in Sort Components GUI. New dialog boxes for showing the directions about the
toolbox.
- New input dialog box for ICA algorithms which can incorporate any number
of inputs from the user.
- Detrend is done prior to concatenation of the time courses in sorting components.
- Line fit is shown along with the model and ICA time courses for Multiple
Regression sorting criteria. Help button which explains how to use Group ICA
Toolbox.
- Status bar in the run analysis button which shows how much percentage of
the analysis is done.ICA algorithms like Simbec, Evd, Jade Opac and Amuse are
included in compiled version.
- Option for selecting one regressor or multiple regressors is removed in
sorting components GUI.