NIRS-SPM is a SPM5(http://www.fil.ion.ucl.ac.uk/spm/) and MATLAB-based software package for statistical analysis of near-infrared spectroscopy (NIRS) signals, developed at the Bio Imaging Signal Processing (BISP) lab. at KAIST in Korea.
Based on the general linear model (GLM) and Sun's tube formula, NIRS-SPM not only provides activation maps of oxy-, deoxy-, and total- hemoglobin, but also allows for super-resolution activation localization. More details are described in Ye et al., 2009.
To remove the unknown global trends due to breathing, cardiac, vaso-motion, or other experimental errors, NIRS-SPM provides a wavelet-minimum description length (MDL) detrending algorithm (Jang et al., 2009).
Recently, we have developed a method to estimate cerebral metabolic rate of oxygen (CMRO2) without hypercapnia by using simultaneous measurements of NIRS and fMRI (Tak et al., 2010). Using the optimization framework, many assumed parameters such as baseline hemoglobin concentration and hypercapnia can be readily estimated, which promise more accurate estimation of cerebral blood flow (CBF) and CMRO2.