CITATION.cff

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cff-version: 1.2.0
title: SI-GCCA Toolbox and Experiments
message: >-
  If you use this software, please cite it and the
  corresponding paper: S. Geirnaert, Y. Yao, T. Francart and
  A. Bertrand, "Stimulus-Informed Generalized Canonical
  Correlation Analysis for Group Analysis of Neural
  Responses to Natural Stimuli," arXiv, 2024,
  https://doi.org/10.48550/arXiv.2401.17841.
type: software
authors:
  - given-names: Simon
    family-names: Geirnaert
    email: simon.geirnaert@esat.kuleuven.be
    affiliation: KU Leuven
    orcid: 'https://orcid.org/0000-0002-4120-4232'
  - given-names: Yuanyuan
    family-names: Yao
    email: yuanyuan.yao@esat.kuleuven.be
    affiliation: KU Leuven
  - given-names: Tom
    family-names: Francart
    email: tom.francart@kuleuven.be
    affiliation: KU Leuven
  - given-names: Alexander
    family-names: Bertrand
    email: alexander.bertrand@esat.kuleuven.be
    affiliation: Ku Leuven
identifiers:
  - type: doi
    value: 10.48550/arXiv.2401.17841
repository-code: >-
  https://github.com/AlexanderBertrandLab/si-gcca?tab=readme-ov-file
abstract: >-
  This repository includes the MATLAB-code for the (SI-)GCCA
  algorithms (and corrCA variants) as explained in [1] (in
  the toolbox) as well as all the experiments from the paper
  in [1], conducted on the publicly available dataset of
  [2]. The experimental files for the video dataset [3] are
  not available, due to copyright constraints on the video
  stimuli (see [3]). However, the analysis code is very
  similar to the group size experiment on the speech data
  (which is available), such that it is fairly easy to
  reproduce the results on the video data once the video
  features are generated.


  [1] S. Geirnaert, Y. Yao, T. Francart and A. Bertrand,
  "Stimulus-Informed Generalized Canonical Correlation
  Analysis for Group Analysis of Neural Responses to Natural
  Stimuli," arXiv, 2024,
  https://doi.org/10.48550/arXiv.2401.17841.


  [2] M. P. Broderick, A. J. Anderson, G. M. Di Liberto, M.
  J. Crosse, and E. C. Lalor, “Data from:
  Electrophysiological correlates of semantic dissimilarity
  reflect the comprehension of natural, narrative speech,”
  Feb. 2019. [Online]. Available:
  https://doi.org/10.5061/dryad.070jc


  [3] Y. Yao, A. Stebner, T. Tuytelaars, S. Geirnaert, and
  A. Bertrand, “Video-EEG Encoding-Decoding Dataset KU
  Leuven,” Zenodo, Jan. 15, 2024. doi:
  10.5281/zenodo.10512414.