Independent component-cross correlation-sequential epoch (ICS) analysis of high field fMRI time series: direct visualization of dual representation of the primary motor cortex in human.

Abstract

A new technique for functional magnetic resonance imaging (fMRI) time series analysis is presented. The technique referred to here as independent component-cross correlation-sequential epoch (ICS) analysis is a hybrid technique of two standard methodologies of biological signal analysis, namely, data driven methods, represented by independent component analysis, and hypothesis driven methods, represented by a general linear model. The technique successfully identified four functionally discrete areas within the primary sensorimotor cortex (SMI) in normal human subjects based on blood oxygenation level dependent (BOLD) contrast functional magnetic resonance imaging (fMRI) time series performed on a high field (3.0 T) system. Each of the four areas identified corresponded to the four physiological subdivisions of SMI, recognized in primates to be essential for voluntary hand motion, namely, 4 anterior (MI-4a) and 4 posterior (MI-4p) of the primary motor cortex, and 3a and the 'classical' (Brodmann areas 1, 2, and 3b) primary sensory cortex, respectively. ICS analysis appears to be a highly reliable and versatile technique for fMRI time series analysis.