GIFT

Versione 4.0.5.0 (105 MB) da Cyrus Eierud

Group ICA/IVA software (MATLAB)

https://trendscenter.org/trends/software/gift/

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Aggiornato 21 feb 2024

Visualizza la licenza su GitHub

Cita come

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.

Visualizza più stili

Iraji, Armin, et al. “Tools of the Trade: Estimating Time-Varying Connectivity Patterns from FMRI Data.” Social Cognitive and Affective Neuroscience, vol. 16, no. 8, Aug. 2020, pp. 849–74, https://doi.org/10.1093/scan/nsaa114.

Visualizza più stili

Compatibilità della release di MATLAB

Creato con R2016b

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Categorie

Sciences > Neuroscience > Human Brain Mapping > Neuroimaging >

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GroupICAT/icatb

GroupICAT/icatb/@gifti

GroupICAT/icatb/@gifti/private

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

contents.m

GroupICAT/icatb/toolbox/Graphical_Lasso

GroupICAT/icatb/toolbox/dynamic_coherence

GroupICAT/icatb/toolbox/eegiftv1.0c

icatb_plotImage

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

fslica_id

GroupICAT/icatb/toolbox/noisecloud/scripts

Versione	Pubblicato	Note della release
4.0.5.0	21 feb 2024	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	Scarica
4.0.4.0	22 feb 2023	See release notes for this release on GitHub: https://github.com/trendscenter/gift/releases/tag/v4.0.4.0	Scarica
4.0.3.5	23 set 2022	See release notes for this release on GitHub: https://github.com/trendscenter/gift/releases/tag/v4.0.3.5	Scarica
4.0.3.0	3 giu 2022		Scarica

Per visualizzare o segnalare problemi su questo componente aggiuntivo di GitHub, visita GitHub Repository.

MLA	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.
APA	Du, Y., Fu, Z., Sui, J., Gao, S., Xing, Y., Lin, D., Salman, M., et al. (2020). NeuroMark: An automated and adaptive ICA based pipeline to identify reproducible fMRI markers of brain disorders. NeuroImage: Clinical, 28, 102375. Elsevier BV. Retrieved from https://doi.org/10.1016%2Fj.nicl.2020.102375
BibTeX	@article{Du_2020, doi = {10.1016/j.nicl.2020.102375}, url = {https://doi.org/10.1016%2Fj.nicl.2020.102375}, year = 2020, publisher = {Elsevier {BV}}, volume = {28}, pages = {102375}, author = {Yuhui Du and Zening Fu and Jing Sui and Shuang Gao and Ying Xing and Dongdong Lin and Mustafa Salman and Anees Abrol and Md Abdur Rahaman and Jiayu Chen and L. Elliot Hong and Peter Kochunov and Elizabeth A. Osuch and Vince D. Calhoun}, title = {{NeuroMark}: An automated and adaptive {ICA} based pipeline to identify reproducible {fMRI} markers of brain disorders}, journal = {{NeuroImage}: Clinical} }

MLA	Iraji, Armin, et al. “Tools of the Trade: Estimating Time-Varying Connectivity Patterns from FMRI Data.” Social Cognitive and Affective Neuroscience, vol. 16, no. 8, Aug. 2020, pp. 849–74, https://doi.org/10.1093/scan/nsaa114.
APA	Iraji, A., Faghiri, A., Lewis, N., Fu, Z., Rachakonda, S., & Calhoun, V. D. (2020). Tools of the trade: estimating time-varying connectivity patterns from fMRI data. Social Cognitive and Affective Neuroscience, 16(8), 849–874. Oxford University Press (OUP). Retrieved from http://dx.doi.org/10.1093/scan/nsaa114
BibTeX	@article{Iraji_2020, title={Tools of the trade: estimating time-varying connectivity patterns from fMRI data}, volume={16}, ISSN={1749-5024}, url={http://dx.doi.org/10.1093/scan/nsaa114}, DOI={10.1093/scan/nsaa114}, number={8}, journal={Social Cognitive and Affective Neuroscience}, publisher={Oxford University Press (OUP)}, author={Iraji, Armin and Faghiri, Ashkan and Lewis, Noah and Fu, Zening and Rachakonda, Srinivas and Calhoun, Vince D}, year={2020}, month=aug, pages={849–874} }