Evaluation of performance to detect default mode network among some algorithms applied to resting-state fMRI data

Kenta Tachikawa; Shun Izawa; Yumie Ono; Shinya Kuriki; Atsushi Ishiyama

doi:10.1109/EMBC.2015.7318730

Evaluation of performance to detect default mode network among some algorithms applied to resting-state fMRI data

Kenta Tachikawa^*, Shun Izawa, Yumie Ono, Shinya Kuriki, Atsushi Ishiyama

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

1 Citation (Scopus)

Abstract

Significant correlation exists in the blood-oxygen-level-dependent (BOLD) signals of resting-state fMRI across different regions in the brain. These regions form the default mode network (DMN), salience network (SN), sensory networks, and others. Among these, the DMN is widely investigated in relation to various mental diseases. Several analytic methods are available for obtaining the DMN activity from individuals' fMRI time-series signals, but a fully effective method has not yet been established. In the present study, we examined a functional connectivity analysis and three algorithms of blind source separation including independent component analysis, second-order blind identification, and non-negative matrix factorization using a set of resting-state fMRI data measured for twelve young participants. Results showed that the second-order blind identification yielded superior performance for the DMN detection, indicating significant activation in all DMN regions based on statistical parametric maps.

Original language	English
Title of host publication	Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	1805-1808
Number of pages	4
Volume	2015-November
ISBN (Print)	9781424492718
DOIs	https://doi.org/10.1109/EMBC.2015.7318730
Publication status	Published - 2015 Nov 4
Event	37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2015 - Milan, Italy Duration: 2015 Aug 25 → 2015 Aug 29

Other

Other	37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2015
Country/Territory	Italy
City	Milan
Period	15/8/25 → 15/8/29

ASJC Scopus subject areas

Computer Vision and Pattern Recognition
Signal Processing
Biomedical Engineering
Health Informatics

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10.1109/EMBC.2015.7318730

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Tachikawa, K., Izawa, S., Ono, Y., Kuriki, S., & Ishiyama, A. (2015). Evaluation of performance to detect default mode network among some algorithms applied to resting-state fMRI data. In Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS (Vol. 2015-November, pp. 1805-1808). [7318730] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/EMBC.2015.7318730

Evaluation of performance to detect default mode network among some algorithms applied to resting-state fMRI data. / Tachikawa, Kenta; Izawa, Shun; Ono, Yumie et al.

Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS. Vol. 2015-November Institute of Electrical and Electronics Engineers Inc., 2015. p. 1805-1808 7318730.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Tachikawa, K, Izawa, S, Ono, Y, Kuriki, S & Ishiyama, A 2015, Evaluation of performance to detect default mode network among some algorithms applied to resting-state fMRI data. in Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS. vol. 2015-November, 7318730, Institute of Electrical and Electronics Engineers Inc., pp. 1805-1808, 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2015, Milan, Italy, 15/8/25. https://doi.org/10.1109/EMBC.2015.7318730

Tachikawa K, Izawa S, Ono Y, Kuriki S, Ishiyama A. Evaluation of performance to detect default mode network among some algorithms applied to resting-state fMRI data. In Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS. Vol. 2015-November. Institute of Electrical and Electronics Engineers Inc. 2015. p. 1805-1808. 7318730 doi: 10.1109/EMBC.2015.7318730

Tachikawa, Kenta ; Izawa, Shun ; Ono, Yumie et al. / Evaluation of performance to detect default mode network among some algorithms applied to resting-state fMRI data. Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS. Vol. 2015-November Institute of Electrical and Electronics Engineers Inc., 2015. pp. 1805-1808

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abstract = "Significant correlation exists in the blood-oxygen-level-dependent (BOLD) signals of resting-state fMRI across different regions in the brain. These regions form the default mode network (DMN), salience network (SN), sensory networks, and others. Among these, the DMN is widely investigated in relation to various mental diseases. Several analytic methods are available for obtaining the DMN activity from individuals' fMRI time-series signals, but a fully effective method has not yet been established. In the present study, we examined a functional connectivity analysis and three algorithms of blind source separation including independent component analysis, second-order blind identification, and non-negative matrix factorization using a set of resting-state fMRI data measured for twelve young participants. Results showed that the second-order blind identification yielded superior performance for the DMN detection, indicating significant activation in all DMN regions based on statistical parametric maps.",

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Evaluation of performance to detect default mode network among some algorithms applied to resting-state fMRI data

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