Development of statistical parametric mapping toolbox for near infrared spectroscopy

Abstract

Even though there exists a powerful statistical parametric mapping (SPM) tool for functional magnetic resonance imaging (fMRI), similar public domain tools are not available for near infrared spectroscopy (NIRS). In this paper, we describe a new public domain statistical toolbox called NIRS-SPM for quantitative analysis of NIRS signals. Mainly, NIRS-SPM statistically analyzes the NIRS data using general linear model (GLM) and makes inferences as the excursion probability which comes from inhomogeneous Gaussian random field that are interpolated from the spare measurement. In order to obtain the correct inference, NIRS-SPM offers the pre-coloring and pre-whitening method for temporal correlation estimation. For simultaneous recording NIRS with fMRI, the spatial mapping between fMRI images and real coordinates in 3-D digitizer is estimated using Horn`s algorithm. These powerful tools allow us the super-resolution localization of the brain activation which is not possible using the conventional NIRS analysis tools.