Functional near-infrared spectroscopy (fNIRS) allows the ability to monitor brain activation by measuring changes in the concentration of oxy- and deoxy-hemoglobin. Until now no standardized approach for fNIRS data analysis has been established, although this has to be regarded as a precondition for future application. Hence, we applied the well-established general linear model to optical imaging data. Further, fNIRS data were analyzed in the frequency domain. Two visual tasks were investigated with optical imaging: a checkerboard paradigm supposed to activate the primary and secondary visual cortex, and a paradigm consisting of moving colored stimuli (rotating 'L's) additionally involving the motion area V5. Analysis with the general linear model detected the activation focus in the primary and secondary visual cortex during the first paradigm. For the second paradigm, a second laterally localized activated brain region was found, most likely representing V5. Spatially resolved spectral analysis confirmed the results by showing maxima of power spectral density and coherence in the same respective brain regions. Moreover, it demonstrated a delay of the hemodynamic response in the motion area. In summary, the present study suggests that the general linear model and spatially resolved spectral analysis can be used as standard statistical approaches for optical imaging data, particularly because they are almost independent of the assumed differential path length factors.