FIT

Version 2.0.5.0 (18.9 MB) by Cyrus Eierud

Fusion ICA Toolbox (MATLAB)

https://trendscenter.org/software/fit/

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Updated 3 Jun 2022

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FIT

Fusion ICA Toolbox v2.0.5.0 (MATLAB)

Introduction

Fusion ICA (FIT) Toolbox is a Matlab toolbox, implementing joint ICA, parallel ICA, CCA-Joint ICA methods and many other methods. It is supported by the NIH and NSF grants to Dr.Vince Calhoun and Dr. Tulay Adali.

FIT toolbox is used to examine the shared information between features (SPM contrast image, EEG signal or SNP data), having 3239 downloads (as of 7/6/24) by researchers world wide. For any question or comments please contact Vince Calhoun (vcalhoun@gsu.edu) or Cyrus Eierud (ceierud@gsu.edu).

Downloads

Fusion ICA Toolbox (FIT) - 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 FIT requiers MATLAB version 6.5 and higher (releases after 2002).

Stand Alone Versions

Windows 64 - Compiled on Windows 64 bit OS with FITv2.0c. Please see read me text file for installation details.
Linux-x86-64 - Compiled on Linux-x86-64 bit OS with FITv2.0c. Please see read me text file for installation details.
Example Subjects - Example data are: fmri-fmri, eeg-fmri and fmri-gene data-sets.

Screen Shots


Figure 1. FIT Sceenshots

Cite As

Calhoun, V. D., et al. “Neuronal Chronometry of Target Detection: Fusion of Hemodynamic and Event-Related Potential Data.” NeuroImage, vol. 30, no. 2, Elsevier BV, Apr. 2006, pp. 544–53, doi:10.1016/j.neuroimage.2005.08.060.

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Calhoun, Vince D., et al. “A Review of Group ICA for FMRI Data and ICA for Joint Inference of Imaging, Genetic, and ERP Data.” NeuroImage, vol. 45, no. 1, Elsevier BV, Mar. 2009, pp. S163–S172, doi:10.1016/j.neuroimage.2008.10.057.

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Sui, Jing, et al. “A Review of Multivariate Methods for Multimodal Fusion of Brain Imaging Data.” Journal of Neuroscience Methods, vol. 204, no. 1, Elsevier BV, Feb. 2012, pp. 68–81, doi:10.1016/j.jneumeth.2011.10.031.

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MATLAB Release Compatibility

Created with R2016b

Compatible with any release

Platform Compatibility

Windows macOS Linux

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Version	Published	Release Notes
2.0.5.0	3 Jun 2022		Download

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

MLA	Calhoun, V. D., et al. “Neuronal Chronometry of Target Detection: Fusion of Hemodynamic and Event-Related Potential Data.” NeuroImage, vol. 30, no. 2, Elsevier BV, Apr. 2006, pp. 544–53, doi:10.1016/j.neuroimage.2005.08.060.
APA	Calhoun, V. D., Adali, T., Pearlson, G. D., & Kiehl, K. A. (2006). Neuronal chronometry of target detection: Fusion of hemodynamic and event-related potential data. NeuroImage, 30(2), 544–553. Elsevier BV. Retrieved from https://doi.org/10.1016%2Fj.neuroimage.2005.08.060
BibTeX	@article{Calhoun_2006, doi = {10.1016/j.neuroimage.2005.08.060}, url = {https://doi.org/10.1016%2Fj.neuroimage.2005.08.060}, year = 2006, month = {apr}, publisher = {Elsevier {BV}}, volume = {30}, number = {2}, pages = {544--553}, author = {V.D. Calhoun and T. Adali and G.D. Pearlson and K.A. Kiehl}, title = {Neuronal chronometry of target detection: Fusion of hemodynamic and event-related potential data}, journal = {{NeuroImage}} }

MLA	Calhoun, Vince D., et al. “A Review of Group ICA for FMRI Data and ICA for Joint Inference of Imaging, Genetic, and ERP Data.” NeuroImage, vol. 45, no. 1, Elsevier BV, Mar. 2009, pp. S163–S172, doi:10.1016/j.neuroimage.2008.10.057.
APA	Calhoun, V. D., Liu, J., & Adalı, T. (2009). A review of group ICA for fMRI data and ICA for joint inference of imaging, genetic, and ERP data. NeuroImage, 45(1), S163–S172. Elsevier BV. Retrieved from https://doi.org/10.1016%2Fj.neuroimage.2008.10.057
BibTeX	@article{Calhoun_2009, doi = {10.1016/j.neuroimage.2008.10.057}, url = {https://doi.org/10.1016%2Fj.neuroimage.2008.10.057}, year = 2009, month = {mar}, publisher = {Elsevier {BV}}, volume = {45}, number = {1}, pages = {S163--S172}, author = {Vince D. Calhoun and Jingyu Liu and Tülay Adal{\i}}, title = {A review of group {ICA} for {fMRI} data and {ICA} for joint inference of imaging, genetic, and {ERP} data}, journal = {{NeuroImage}} }

MLA	Sui, Jing, et al. “A Review of Multivariate Methods for Multimodal Fusion of Brain Imaging Data.” Journal of Neuroscience Methods, vol. 204, no. 1, Elsevier BV, Feb. 2012, pp. 68–81, doi:10.1016/j.jneumeth.2011.10.031.
APA	Sui, J., Adali, T., Yu, Q., Chen, J., & Calhoun, V. D. (2012). A review of multivariate methods for multimodal fusion of brain imaging data. Journal of Neuroscience Methods, 204(1), 68–81. Elsevier BV. Retrieved from https://doi.org/10.1016%2Fj.jneumeth.2011.10.031
BibTeX	@article{Sui_2012, doi = {10.1016/j.jneumeth.2011.10.031}, url = {https://doi.org/10.1016%2Fj.jneumeth.2011.10.031}, year = 2012, month = {feb}, publisher = {Elsevier {BV}}, volume = {204}, number = {1}, pages = {68--81}, author = {Jing Sui and Tülay Adali and Qingbao Yu and Jiayu Chen and Vince D. Calhoun}, title = {A review of multivariate methods for multimodal fusion of brain imaging data}, journal = {Journal of Neuroscience Methods} }

FIT

FIT

Fusion ICA Toolbox v2.0.5.0 (MATLAB)

Table of Contents

Introduction

Downloads

Stand Alone Versions

Screen Shots

Documentation/Manual

Version History

Publications

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MATLAB Release Compatibility

Platform Compatibility

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