Automated signal drift and global fluctuation removal from 4D fMRI data based on principal component analysis as a major preprocessing step for fMRI data analysis

Harshit S. Parmar, Brian Nutter, Rodney Long, Sameer Antani, Sunanda Mitra

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

1 Scopus citations

Abstract

Temporal signal drift is one of the significant artifacts in functional Magnetic Resonance Imaging (fMRI) data that is not given as much attention as motion or physiological artifacts. However, signal drift if not accounted for, can introduce spurious correlation between different regions in resting state fMRI data. Hence detection and removal of signal drift is an important preprocessing step in fMRI data analysis. Here we propose an automated data driven approach that makes use of Principal Component Analysis (PCA) to eliminate not only low frequency signal drift but also spontaneous high frequency global signal fluctuations. This approach is also able to identify the most dominant component for each voxel separately. For task fMRI, this can help us identify regions that respond in a time locked manner to the experiment paradigm. Such regions can be thought of as activation regions. The dominant principal components corresponding to such regions can also be used to investigate intra-region Hemodynamic Response (HR) variability within subjects and across subjects.

Original languageEnglish
Title of host publicationMedical Imaging 2019
Subtitle of host publicationBiomedical Applications in Molecular, Structural, and Functional Imaging
EditorsBarjor Gimi, Andrzej Krol
PublisherSPIE
ISBN (Electronic)9781510625532
DOIs
StatePublished - 2019
EventMedical Imaging 2019: Biomedical Applications in Molecular, Structural, and Functional Imaging - San Diego, United States
Duration: Feb 19 2019Feb 21 2019

Publication series

NameProgress in Biomedical Optics and Imaging - Proceedings of SPIE
Volume10953
ISSN (Print)1605-7422

Conference

ConferenceMedical Imaging 2019: Biomedical Applications in Molecular, Structural, and Functional Imaging
CountryUnited States
CitySan Diego
Period02/19/1902/21/19

Keywords

  • PCA
  • fMRI
  • global signal fluctuations
  • preprocessing
  • signal drift

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