Impact of physiological noise in characterizing the functional MRI default-mode network in Alzheimer’s disease

Research output: Contribution to journalArticleScientificpeer-review

Researchers

  • Yi Tien Li
  • Chun Yuan Chang
  • Yi Cheng Hsu
  • Jong Ling Fuh
  • Wen Jui Kuo
  • Jhy Neng Tasso Yeh
  • Fa Hsuan Lin

Research units

  • National Taiwan University
  • Taipei Medical University
  • Min-Sheng General Hospital
  • Veterans General Hospital-Taipei
  • National Yang-Ming University
  • Sunnybrook Research Institute
  • University of Toronto

Abstract

The functional connectivity of the default-mode network (DMN) monitored by functional magnetic resonance imaging (fMRI) in Alzheimer's disease (AD) patients has been found weaker than that in healthy participants. Since breathing and heart beating can cause fluctuations in the fMRI signal, these physiological activities may affect the fMRI data differently between AD patients and healthy participants. We collected resting-state fMRI data from AD patients and age-matched healthy participants. With concurrent cardiac and respiratory recordings, we estimated both physiological responses phase-locked and non-phase-locked to heart beating and breathing. We found that the cardiac and respiratory physiological responses in AD patients were 3.00 ± 0.51 s and 3.96 ± 0.52 s later (both p < 0.0001) than those in healthy participants, respectively. After correcting the physiological noise in the resting-state fMRI data by population-specific physiological response functions, the DMN estimated by seed-correlation was more localized to the seed region. The DMN difference between AD patients and healthy controls became insignificant after suppressing physiological noise. Our results indicate the importance of controlling physiological noise in the resting-state fMRI analysis to obtain clinically related characterizations in AD.

Details

Original languageEnglish
JournalJOURNAL OF CEREBRAL BLOOD FLOW AND METABOLISM
Publication statusE-pub ahead of print - 1 Jan 2020
MoE publication typeA1 Journal article-refereed

    Research areas

  • cardiac response function, classification, fMRI, network, physiological noise, Respiratory response function, resting-state

ID: 41761993