Functional near-infrared spectroscopy (fNIRS) is a non-invasive method for studying functional activation via monitoring changes of the hemodynamic properties in brain and event-related experimental in examining cognitive processes is very useful but much more flexible in data analysis. To validate the usefulness of independent component analysis (ICA) of event-related fNRIS data, a "high-motivation" GKT (guilty knowledge test) task was applied. A very efficient method of maximization suited called FastICA was applied to maximize the contrast function in practice. Compared with the fMRI studies of ICA, the oxy-HB (oxygenated hemoglobin) signals can be decomposed and the active areas can be found in emotional behavior. The time courses and active regions of the event-related ICA components were consistent across trials. ICA approach delivers valid fNIRS amplitude estimations and enables the analysis of event-related fNIRS data series which are highly relevant in particular for cognitive fNIRS studies.