Concurrent spatiotemporal analysis of functional near-infrared spectroscopy data using independent component analysis

Abstract

Functional near infrared spectroscopy (fNIRS) recordings are the hemodynamic signals that come from the latent neural sources and physiological noise that are spatially and temporally mixed across the brain. The purpose of this work was to extract the temporal characteristics and the spatial activation patterns of human brains captured by independent component analysis (ICA). Both of the raw and filtered fNIRS datasets are processed with ICA. In particular the temporal components and spatial activity maps identified by ICA for a right finger tapping task were investigated in detail.