Reconstructing Temporal Dynamics of fMRI Time Series via Encoded Contextual Information

Wenjun Bai, Tomoki Tokuda, Okito Yamashita, Junichiro Yoshimoto

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

Abstract

To uncover the rich temporal dynamics from the noisy fMRI time series, we propose a data-driven time series model: temporal reconstruction model, targets on reconstructing subsequences of fMRI time series via encoded contextual representations. This novel reconstruction model is further perfected by learning the commonality among multiple reconstructed temporal resolutions. Through an empirical validation on a synthetic noisy time series, we demonstrate the superior denoising capacity of our reconstruction model. Implementing this reconstruction model on a real fMRI dataset, it reveals the rich temporal dynamics of reconstructed fMRI time series are revealed, assisting the subsequent neuroscientific analysis on discovering more consistent subject-level temporal independent functional modes.

Original languageEnglish
Title of host publicationProceedings - 2020 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2020
EditorsTaesung Park, Young-Rae Cho, Xiaohua Tony Hu, Illhoi Yoo, Hyun Goo Woo, Jianxin Wang, Julio Facelli, Seungyoon Nam, Mingon Kang
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages968-971
Number of pages4
ISBN (Electronic)9781728162157
DOIs
Publication statusPublished - 16-12-2020
Externally publishedYes
Event2020 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2020 - Virtual, Seoul, Korea, Republic of
Duration: 16-12-202019-12-2020

Publication series

NameProceedings - 2020 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2020

Conference

Conference2020 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2020
Country/TerritoryKorea, Republic of
CityVirtual, Seoul
Period16-12-2019-12-20

All Science Journal Classification (ASJC) codes

  • Computer Science Applications
  • Information Systems and Management
  • Medicine (miscellaneous)
  • Health Informatics

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