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Updated 21 Feb 2024

GIFT

Group ICA/IVA software (MATLAB) v4.0.5.4

TReNDS

Table of Contents

  1. Introduction
  2. Download
  3. GIFT BIDS-Apps
  4. Screen Shots
  5. Version Compatability
  6. Toolboxes and Features added to GIFT
    1. Mancovan
    2. NBiC
  7. Documentation/Manual
  8. FAQ
  9. Version History
  10. Publications

Introduction

GIFT is an application, originally supported by NIH grant 1RO1 EB000840 to Dr. Vince Calhoun and Dr. Tulay Adali and has been continuous supported by NIH and NSF. The MATLAB application implements multiple algorithms for independent component analysis and blind source separation of group (and single subject) functional magnetic resonance imaging data. GIFT has been downloaded 18581 times (as of 7/6/24) by researchers world wide. For question or comments please contact Vince Calhoun (vcalhoun@gsu.edu) or Cyrus Eierud (ceierud@gsu.edu).

Downloads

GroupICAT - Download latest version by clicking the green code button on the upper right on this page and then clone the software using the link and the git clone command in your terminal. Current version of Group ICA. Requires MATLAB R2008a and higher.

Stand Alone Versions

Windows 64 - Compiled on Windows 64 bit OS and MATLAB R2020a. Please see read me text file for more details.
Linux-x86-64 - Compiled on Linux-x86-64 bit OS and MATLAB R2016b. Please see read me text file for more details.
fMRI Data - Example fMRI datais from a visuomotor paradigm. Mancovan Sample Data - Sample data to use in mancovan analysis or temporal dfnc analysis.

Complex GIFT - ICA is applied on complex fMRI data. Please follow the read me text file instructions for doing complex fMRI ICA analysis.

GIFT BIDS-Apps

If you have your data in BIDS format or you want to run GIFT under a cluster you may want to our GIFT BIDS-Apps gift-bids.

Screen Shots

<markdown-accessiblity-table><table class="readme_table"> <thead> <tr> <th align="center" class="readme_th"><a target="_blank" rel="nofollow noopener noreferrer" rel="nofollow noopener noreferrer" href="https://github.com/trendscenter/gift/blob/master/doc/web/img/20240705Gift4Ims.png"><img src="https://github.com/trendscenter/gift/raw/master/doc/web/img/20240705Gift4Ims.png" alt="GIFT" style="max-width: 100%;"></a></th> </tr> </thead> <tbody> <tr> <td align="center" class="readme_td">Figure 1. GIFT Sceenshots</td> </tr> </tbody> </table></markdown-accessiblity-table>

Version Compatability

All the toolboxes in GIFT require only MATLAB and not dependent on additional MATLAB toolboxes like Image Processing, Signal Processing, etc. Basic GIFT analysis (without GUI) runs on MATLAB R13 and higher. GIFT GUI works on R2008a and higher. Please see below for specific details related to toolboxes in GIFT:

  • MANCOVAN runs on MATLAB R2008a and higher. From R2012b onwards, Optimization toolbox is not required to compute t-threshold based on distribution of voxelwise t-stats. There is an option to use Z-threshold or select mask if Optimization toolbox is not installed on MATLAB versions less than R2012b.
  • Temporal and Spatial dFNC runs on MATLAB R2008a and higher.

Toolboxes and Features added to GIFT

Mancovan

Mancovan toolbox is based on the paper (E. Allen, E. Erhardt, E. Damaraju, W. Gruner, J. Segall, R. Silva, M. Havlicek, S. Rachakonda, J. Fries, R.Kalyanam, A. Michael, J. Turner, T. Eichele, S. Adelsheim, A. Bryan, J. R. Bustillo, V. P. Clark, S. Feldstein,F. M. Filbey, C. Ford, et al, 2011). This toolbox works on MATLAB versions greater than R2008a. Features used are subject component spatial maps, timecourses spectra and FNC correlations. Multivariate tests are done on the features to determine the significant covariates which are later used in the univariate tests on each feature. To invoke the toolbox, select “Mancovan� under “Toolboxes� menu (Figure 3.2). You could also invoke toolbox using mancovan_toolbox at the command prompt. Mancovan toolbox (Figure 3.38) is divided into four parts like create design matrix, setup features, run mancova and display.

N-BiC

NBiC toolbox is based on the 2020 publication "N-BiC: A Method for Multi-Component and Symptom Biclustering of Structural MRI Data: Application to Schizophrenia" (Md Abdur Rahaman , Jessica A. Turner, Cota Navin Gupta, Srinivas Rachakonda, Jiayu Chen , Jingyu Liu , Theo G. M. van Erp, Steven Potkin, Judith Ford, Daniel Mathalon, Hyo Jong Lee, Wenhao Jiang, Bryon A. Mueller, Ole Andreassen, Ingrid Agartz, Scott R. Sponheim , Andrew R. Mayer, Julia Stephen , Rex E. Jung, Jose Canive, Juan Bustillo, and Vince D. Calhoun). This toolbox works on MATLAB versions greater than R2008a. Click here for more info.

Documentation/Manual

Click here for link to manual in PDF format
Click here for link to manual in Word format

FAQ

Click here for FAQ

Version History

More information about about the GIFT version history is found at the following link: GIFT version history

Publications

Click here for a list of GIFT related publications

Cite As

Calhoun, V. D., et al. “A Method for Making Group Inferences Using Independent Component Analysis of Functional MRI Data: Exploring the Visual System.” NeuroImage, 2001, pp. S88.

Du, Yuhui, et al. “NeuroMark: An Automated and Adaptive ICA Based Pipeline to Identify Reproducible FMRI Markers of Brain Disorders.” NeuroImage: Clinical, vol. 28, Elsevier BV, 2020, p. 102375, doi:10.1016/j.nicl.2020.102375.

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MATLAB Release Compatibility
Created with R2016b
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GroupICAT/icatb

GroupICAT/icatb/@gifti

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GroupICAT/icatb/icatb_analysis_functions

GroupICAT/icatb/icatb_analysis_functions/icatb_algorithms

GroupICAT/icatb/icatb_analysis_functions/icatb_algorithms/icatb_semiblindInfomax

GroupICAT/icatb/icatb_batch_files

GroupICAT/icatb/icatb_display_functions

GroupICAT/icatb/icatb_helpManual

GroupICAT/icatb/icatb_helper_functions

GroupICAT/icatb/icatb_io_data_functions

GroupICAT/icatb/icatb_mancovan_files

GroupICAT/icatb/icatb_parallel_files

GroupICAT/icatb/icatb_scripts

GroupICAT/icatb/icatb_spm_files

GroupICAT/icatb/icatb_spm_files/@icatb_file_array

GroupICAT/icatb/icatb_spm_files/@icatb_file_array/private

GroupICAT/icatb/icatb_spm_files/@icatb_nifti

GroupICAT/icatb/icatb_spm_files/@icatb_nifti/private

GroupICAT/icatb/icatb_talairach_scripts

GroupICAT/icatb/icatb_templates

GroupICAT/icatb/toolbox/Graphical_Lasso

GroupICAT/icatb/toolbox/dynamic_coherence

GroupICAT/icatb/toolbox/eegiftv1.0c

GroupICAT/icatb/toolbox/eegiftv1.0c/icatb_eeg_batch_files

GroupICAT/icatb/toolbox/eegiftv1.0c/icatb_eeg_files

GroupICAT/icatb/toolbox/eegiftv1.0c/icatb_eeglabv6.0b_files

GroupICAT/icatb/toolbox/export_fig

GroupICAT/icatb/toolbox/icasso122

GroupICAT/icatb/toolbox/mancovan

GroupICAT/icatb/toolbox/mi

GroupICAT/icatb/toolbox/nbic

GroupICAT/icatb/toolbox/noisecloud

GroupICAT/icatb/toolbox/noisecloud/3rdparty

GroupICAT/icatb/toolbox/noisecloud/3rdparty/glmnet_matlab

GroupICAT/icatb/toolbox/noisecloud/prep

GroupICAT/icatb/toolbox/noisecloud/prep/label-good-bad-gui

GroupICAT/icatb/toolbox/noisecloud/scripts

Version Published Release Notes
4.0.5.0

See release notes for this release on GitHub: https://github.com/trendscenter/gift/releases/tag/v4.0.5.0
See release notes for this release on GitHub: https://github.com/trendscenter/gift/releases/tag/v4.0.5.0

4.0.4.0

See release notes for this release on GitHub: https://github.com/trendscenter/gift/releases/tag/v4.0.4.0

4.0.3.5

See release notes for this release on GitHub: https://github.com/trendscenter/gift/releases/tag/v4.0.3.5

4.0.3.0

To view or report issues in this GitHub add-on, visit the GitHub Repository.
To view or report issues in this GitHub add-on, visit the GitHub Repository.