Research output: Contribution to book/anthology/report/proceeding › Article in proceedings › Research › peer-review

- Valeri Tsatsishvili, Department of Mathematical Information Technology, Denmark
- Fengyu Cong, Department of Mathematical Information Technology ,
- Tuomas Puoliväli, Department of Mathematical Information Technology, Denmark
- Vinoo Alluri, Department of Mathematical Information Technology ,
- Petri Toiviainen, Department of Mathematical Information Technology ,
- Asoke K. Nandi, Helsingin yliopisto, Denmark
- Elvira Brattico
- Tapani Ristaniemi, Department of Mathematical Information Technology

Group independent component analysis (ICA) with special assumptions is often used for analyzing functional magnetic resonance imaging (fMRI) data. Before ICA, dimension reduction is applied to separate signal and noise subspaces. For analyzing noisy fMRI data of individual participants in free-listening to naturalistic and long music, we applied individual ICA and therefore avoided the assumptions of Group ICA. We also compared principal component analysis (PCA) and canonical correlation analysis (CCA) for dimension reduction of such fMRI data. We found interesting brain activity associated with music across majority of participants, and found that PCA and CCA were comparable for dimension reduction.

Original language | English |
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Title of host publication | ESANN 2013 proceedings, 21st European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning |

Number of pages | 6 |

Publication year | 2013 |

Pages | 137-142 |

ISBN (print) | 9782874190810 |

Publication status | Published - 2013 |

Event | 21st European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning, ESANN 2013 - Bruges, Belgium Duration: 24 Apr 2013 → 26 Apr 2013 |

Conference | 21st European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning, ESANN 2013 |
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Land | Belgium |

By | Bruges |

Periode | 24/04/2013 → 26/04/2013 |

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ID: 90549268