Wide-field optical imaging techniques constitute powerful tools to sample and study mesoscale neuronal activity. The sampled data constitutes a sequence of image frames in which one can perceive the flow of brain activity starting and terminating at source and sink locations respectively. The most common data analyses include qualitative assessment to identify sources and sinks of activity as well as their trajectories. The quantitative analyses is mostly based on computing the temporal variation of the intensity of pixels while a few studies have also reported estimates of wave motion using optical-flow techniques from computer vision. A comprehensive toolbox for the quantitative analyses of mesoscale brain activity data however is still missing. We present a graphical-user-interface based Matlab ® toolbox for investigating the spatiotemporal dynamics of mesoscale brain activity using optical-flow analyses. The toolbox includes the implementation of three optical-flow methods namely Horn-Schunck, Combined Local-Global, and Temporospatial algorithms for estimating velocity vector fields of perceived flow in mesoscale brain activity. From the velocity vector fields we determine the locations of sources and sinks as well as the trajectories and temporal velocities of activity flow. Using our toolbox, we compare the efficacy of the three optical-flow methods for determining spatiotemporal dynamics by using simulated data. We also demonstrate the application of optical-flow methods onto sensory-evoked calcium and voltage imaging data. Our results indicate that the combined local-global method we employ, yields results that correlate with the manual assessment. The automated approach permits rapid and effective quantification of mesoscale brain dynamics and may facilitate the study of brain function in response to new experiences or pathology.