When neural circuits develop abnormally due to different genetic deficits and/or environmental insults, neural computations and the behaviors that rely on them are altered. Computational theories that relate neural circuits with specific quantifiable behavioral and physiological phenomena, therefore, serve as extremely useful tools for elucidating the neuropathological mechanisms that underlie different disorders. The visual system is particularly well suited for characterizing differences in neural computations; computational theories of vision are well established, and empirical protocols for measuring the parameters of those theories are well developed. In this article, we examine how psychophysical and neuroimaging measurements from human subjects are being used to test hypotheses about abnormal neural computations in autism, with an emphasis on hypotheses regarding potential excitation/inhibition imbalances. We discuss the complexity of relating specific computational abnormalities to particular underlying mechanisms given the diversity of neural circuits that can generate the same computation, and we discuss areas of research in which computational theories need to be further developed to provide useful frameworks for interpreting existing results. A final emphasis is placed on the need to extend existing ideas into developmental frameworks that take into account the dramatic developmental changes in neurophysiology (e.g., changes in excitation/inhibition balance) that take place during the first years of life, when autism initially emerges.