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Group Study of Simulated Driving fMRI Data by Multiset Canonical Correlation Analysis

In this work, we apply a novel statistical method, multiset canonical correlation analysis (M-CCA), to study a group of functional magnetic resonance imaging (fMRI) datasets acquired during simulated driving task. The M-CCA method jointly decomposes fMRI datasets from different subjects/sessions int...

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Detalles Bibliográficos
Autores principales: Li, Yi-Ou, Eichele, Tom, Calhoun, Vince D., Adali, Tulay
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer US 2011
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3673747/
https://www.ncbi.nlm.nih.gov/pubmed/23750290
http://dx.doi.org/10.1007/s11265-010-0572-8
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author Li, Yi-Ou
Eichele, Tom
Calhoun, Vince D.
Adali, Tulay
author_facet Li, Yi-Ou
Eichele, Tom
Calhoun, Vince D.
Adali, Tulay
author_sort Li, Yi-Ou
collection PubMed
description In this work, we apply a novel statistical method, multiset canonical correlation analysis (M-CCA), to study a group of functional magnetic resonance imaging (fMRI) datasets acquired during simulated driving task. The M-CCA method jointly decomposes fMRI datasets from different subjects/sessions into brain activation maps and their associated time courses, such that the correlation in each group of estimated activation maps across datasets is maximized. Therefore, the functional activations across all datasets are extracted in the order of consistency across different dataset. On the other hand, M-CCA preserves the uniqueness of the functional maps estimated from each dataset by avoiding concatenation of different datasets in the analysis. Hence, the cross-dataset variation of the functional activations can be used to test the hypothesis of functional-behavioral association. In this work, we study 120 simulated driving fMRI datasets and identify parietal-occipital regions and frontal lobe as the most consistently engaged areas across all the subjects and sessions during simulated driving. The functional-behavioral association study indicates that all the estimated brain activations are significantly correlated with the steering operation during the driving task. M-CCA thus provides a new approach to investigate the complex relationship between the brain functions and multiple behavioral variables, especially in naturalistic tasks as demonstrated by the simulated driving study.
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spelling pubmed-36737472013-06-05 Group Study of Simulated Driving fMRI Data by Multiset Canonical Correlation Analysis Li, Yi-Ou Eichele, Tom Calhoun, Vince D. Adali, Tulay J Signal Process Syst Article In this work, we apply a novel statistical method, multiset canonical correlation analysis (M-CCA), to study a group of functional magnetic resonance imaging (fMRI) datasets acquired during simulated driving task. The M-CCA method jointly decomposes fMRI datasets from different subjects/sessions into brain activation maps and their associated time courses, such that the correlation in each group of estimated activation maps across datasets is maximized. Therefore, the functional activations across all datasets are extracted in the order of consistency across different dataset. On the other hand, M-CCA preserves the uniqueness of the functional maps estimated from each dataset by avoiding concatenation of different datasets in the analysis. Hence, the cross-dataset variation of the functional activations can be used to test the hypothesis of functional-behavioral association. In this work, we study 120 simulated driving fMRI datasets and identify parietal-occipital regions and frontal lobe as the most consistently engaged areas across all the subjects and sessions during simulated driving. The functional-behavioral association study indicates that all the estimated brain activations are significantly correlated with the steering operation during the driving task. M-CCA thus provides a new approach to investigate the complex relationship between the brain functions and multiple behavioral variables, especially in naturalistic tasks as demonstrated by the simulated driving study. Springer US 2011-01-13 2012 /pmc/articles/PMC3673747/ /pubmed/23750290 http://dx.doi.org/10.1007/s11265-010-0572-8 Text en © The Author(s) 2011 https://creativecommons.org/licenses/by-nc/4.0/ This article is distributed under the terms of the Creative Commons Attribution Noncommercial License which permits any noncommercial use, distribution, and reproduction in any medium, provided the original author(s) and source are credited.
spellingShingle Article
Li, Yi-Ou
Eichele, Tom
Calhoun, Vince D.
Adali, Tulay
Group Study of Simulated Driving fMRI Data by Multiset Canonical Correlation Analysis
title Group Study of Simulated Driving fMRI Data by Multiset Canonical Correlation Analysis
title_full Group Study of Simulated Driving fMRI Data by Multiset Canonical Correlation Analysis
title_fullStr Group Study of Simulated Driving fMRI Data by Multiset Canonical Correlation Analysis
title_full_unstemmed Group Study of Simulated Driving fMRI Data by Multiset Canonical Correlation Analysis
title_short Group Study of Simulated Driving fMRI Data by Multiset Canonical Correlation Analysis
title_sort group study of simulated driving fmri data by multiset canonical correlation analysis
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3673747/
https://www.ncbi.nlm.nih.gov/pubmed/23750290
http://dx.doi.org/10.1007/s11265-010-0572-8
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