The Spatial Standard Observer (SSO) was developed to predict the detectability of spatial contrast targets such as those used in the ModelFest project (Watson, 2000). The SSO is a lumped parameter model basing its predictions on the visible contrast generalized energy. Visible contrast means that the contrast has been reduced by a contrast sensitivity function (CSF). Generalized energy means that the visible contrast is raised to a power higher than 2 before spatial and temporal integration. To adapt the SSO to predict the effects of variations of optical image quality on tasks, the optical component of the SSO CSF needs to be removed, leaving the neural CSF. Also, since target detection is not the typical criterion task for assessing optical image quality, the SSO concept needs to be extended to other tasks, such as Sloan character recognition.