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Computing Temporal ICA from HCP resting state data using Functional Modes DiFuMo atlas.

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tica's Introduction

Temporal ICA (tICA) HCP resting-state fMRI data

Computing tICA from HCP resting state fMRI data using Functional Modes DiFuMo atlas.

This repository includes the interpretation of the masking block of HCP resting state data in our recent paper:

Independent Component (IC) 1 (Static view)

Figure 1 - IC 1 (Static view)

Independent Component (IC) 1 (Interactive view)

Figure 2 - IC 1 (Interactive view) - Link to the Interactive view

Website

For more informations, please visit the websites below:

Full version with post-processing (788 subjects) :

Link
Full version without post-processing (200 subjects) :

Link

Link

Paper in arXiv version: [PDF]
Paper in HAL version: [PDF]

Citation

If you find this repository useful in your research, please cite:

@inproceedings{tajini2021functional,
  address={Cham},
  author={Tajini, Badr and Richard, Hugo and Thirion, Bertrand},
  booktitle={"Medical Image Computing and Computer Assisted Intervention -- MICCAI 2021"},
  editor={de Bruijne, Marleen and Cattin, Philippe C. and Cotin, St{\'e}phane and Padoy, Nicolas and Speidel, Stefanie and Zheng, Yefeng and Essert, Caroline},
  isbn={978-3-030-87196-3},
  pages={491--500},
  publisher={Springer International Publishing},
  title={Functional Magnetic Resonance Imaging data augmentation through conditional ICA},
  year={2021}
}

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