Analytic Signal-Based Causal Network Estimator for Hemodynamic Signal Analysis in the Brain

Jang Woo Park, Gihyoun Lee, Beop-Min Kim, Yongmin Chang, Young Jin Jung

Research output: Contribution to journalArticle

Abstract

The connectivity and the causality were estimated using functional magnetic resonance imaging (fMRI) and functional near-infrared spectroscopy (f-NIRS) signals to introduce an optimal networks analysis technique for hemodynamic signals. Instantaneous phase information was utilized to analyze the fMRI time series and the f-NIRS signals in order to estimate connectivity and causal networks in the brain. To identify an optimal estimator, the conducted computer-based Monte Carlo simulation using fMRI mimicking signals under various realistic conditions. The simulation results showed that the phase-information-based approach can be an optimal causal estimator for hemodynamic signals.

Original languageEnglish
Pages (from-to)847-854
Number of pages8
JournalJournal of the Korean Physical Society
Volume74
Issue number9
DOIs
Publication statusPublished - 2019 May 1

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hemodynamics
signal analysis
estimators
brain
magnetic resonance
infrared spectroscopy
network analysis
simulation
estimates

Keywords

  • Causality
  • Connectivity
  • f-NIRS
  • fMRI
  • Phase-locking value

ASJC Scopus subject areas

  • Physics and Astronomy(all)

Cite this

Analytic Signal-Based Causal Network Estimator for Hemodynamic Signal Analysis in the Brain. / Park, Jang Woo; Lee, Gihyoun; Kim, Beop-Min; Chang, Yongmin; Jung, Young Jin.

In: Journal of the Korean Physical Society, Vol. 74, No. 9, 01.05.2019, p. 847-854.

Research output: Contribution to journalArticle

Park, Jang Woo ; Lee, Gihyoun ; Kim, Beop-Min ; Chang, Yongmin ; Jung, Young Jin. / Analytic Signal-Based Causal Network Estimator for Hemodynamic Signal Analysis in the Brain. In: Journal of the Korean Physical Society. 2019 ; Vol. 74, No. 9. pp. 847-854.
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