A robust independent component analysis (ICA) model for functional magnetic resonance imaging (fMRI) data

Jingqi Ao, Sunanda Mitra, Zheng Liu, Brian Nutter

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

The coupling of carefully designed experiments with proper analysis of functional magnetic resonance imaging (fMRI) data provides us with a powerful as well as noninvasive tool to help us understand cognitive processes associated with specific brain regions and hence could be used to detect abnormalities induced by a diseased state. The hypothesisdriven General Linear Model (GLM) and the data-driven Independent Component Analysis (ICA) model are the two most commonly used models for fMRI data analysis. A hybrid ICA-GLM model combines the two models to take advantages of benefits from both models to achieve more accurate mapping of the stimulus-induced activated brain regions. We propose a modified hybrid ICA-GLM model with probabilistic ICA that includes a noise model. In this modified hybrid model, a probabilistic principle component analysis (PPCA)-based component number estimation is used in the ICA stage to extract the intrinsic number of original time courses. In addition, frequency matching is introduced into the time course selection stage, along with temporal correlation, F-test based model fitting estimation, and time course combination, to produce a more accurate design matrix for GLM. A standard fMRI dataset is used to compare the results of applying GLM and the proposed hybrid ICA-GLM in generating activation maps.

Original languageEnglish
Title of host publicationMedical Imaging 2011
Subtitle of host publicationComputer-Aided Diagnosis
DOIs
StatePublished - 2011
EventMedical Imaging 2011: Computer-Aided Diagnosis - Lake Buena Vista, FL, United States
Duration: Feb 15 2011Feb 17 2011

Publication series

NameProgress in Biomedical Optics and Imaging - Proceedings of SPIE
Volume7963
ISSN (Print)1605-7422

Conference

ConferenceMedical Imaging 2011: Computer-Aided Diagnosis
CountryUnited States
CityLake Buena Vista, FL
Period02/15/1102/17/11

Keywords

  • GLM
  • ICA
  • component number estimation
  • fMRI data analysis
  • modified hybrid ICA-GLM

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