Accession Number:

ADA460194

Title:

Analysis of fMRI Data by Blind Separation into Independent Spatial Components

Descriptive Note:

Journal article

Corporate Author:

NAVAL HEALTH RESEARCH CENTER SAN DIEGO CA

Report Date:

1997-06-01

Pagination or Media Count:

31.0

Abstract:

Current analytical techniques applied to functional magnetic resonance imaging fMRI data require a priori knowledge or specific assumptions about the time courses of processes contributing to the measured brain electrical signals. Here we describe a new method for analyzing fMRI data based on the independent component analysis ICA algorithm of Bell and Sejnowski. We decomposed eight fMRI data sets from 4 normal subjects performing various cognitive tasks. By utilizing higher-order statistics to enforce successively stricter criteria for spatial independence between component maps, both the ICA algorithm and related fourth-order decomposition technique were superior to principal component analysis PCA in determining the spatial and temporal extent of task-related activation. ICA appears to be a highly promising method for the analysis of fMRI data from normal and clinical populations.

Subject Categories:

  • Medicine and Medical Research
  • Numerical Mathematics

Distribution Statement:

APPROVED FOR PUBLIC RELEASE