Comparative study of resolution improvement of optical intrinsic signal imaging by extracting outlier images during data analysis

Optical intrinsic signal imaging (OISI) is a functional neuroimaging technique that measures changes in cortical light reflectance induced in vivo by the change in both cortical absorption and scattering. These changes are spatially correlated with neuronal activity and are due to changes in hemoglobin concentration and cell swelling. Typically, a light source at 630nm illuminates the exposed cortex to emphasize changes in deoxyhemoglobin and CCD camera acquired the reflected light during trial (stimulation). One trial consisted of recording multiple consecutive frames to minimize noise during image acquisition. Unfortunately, during trials processing both good and poor quality images are combined together resulting in an overall degradation of resolution performance. The present study describes the performance evaluation of an algorithm developed to detect and screen out these poor images (outliers) during OISI analysis. Algorithm's performance was tested on rodent's model and the experimental results highlight the potential of the algorithm for enhancing the resolution of the active area in the final OISI images.