Complexity analysis of resting state fMRI signals in depressive patients

Pei Shan Ho, Chemin Lin, Guan Yen Chen, Ho Ling Liu, Chih-Mao Huang, Tatia Mei Chun Lee, Shwu Hua Lee, Shun Chi Wu

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Scopus citations

Abstract

Analysis of brain signal complexity reveals the intrinsic network dynamics and is widely utilized in the investigation of mechanisms in mental disorders. In this study, the complexity of resting-state functional magnetic resonance imaging (fMRI) signals was explored in patients with depression using multiscale entropy (MSE). Thirty-five patients diagnosed with depression and 22 age-and gender-matched healthy controls were considered. The MSE profiles in five brain networks of the two participant groups were evaluated and analyzed. The results showed that depressive patients exhibited higher complexity in the left frontoparietal network than that seen in healthy controls, which is known to be critical for executive control functions. Through this study, the efficacy of MSE in identifying and understanding the mental disorders was also demonstrated.

Original languageEnglish
Title of host publication2017 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society
Subtitle of host publicationSmarter Technology for a Healthier World, EMBC 2017 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages3190-3193
Number of pages4
ISBN (Electronic)9781509028092
DOIs
StatePublished - 13 Sep 2017
Event39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2017 - Jeju Island, Korea, Republic of
Duration: 11 Jul 201715 Jul 2017

Publication series

NameProceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
ISSN (Print)1557-170X

Conference

Conference39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2017
CountryKorea, Republic of
CityJeju Island
Period11/07/1715/07/17

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  • Cite this

    Ho, P. S., Lin, C., Chen, G. Y., Liu, H. L., Huang, C-M., Lee, T. M. C., Lee, S. H., & Wu, S. C. (2017). Complexity analysis of resting state fMRI signals in depressive patients. In 2017 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society: Smarter Technology for a Healthier World, EMBC 2017 - Proceedings (pp. 3190-3193). [8037535] (Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/EMBC.2017.8037535