From consideration of a number of types of apparently linear and nonlinear behavior of direction selectivity of visual cortex neurons, it will be argued that there are at least two fundamentally different types of motion computation. The first, designated quasi-linear, entails a summation of afferent signals which are in approximate quadrature phase, both spatially and temporally (e.g., lagged and nonlagged LGN afferents, in the cat); the summation may be of a linear or a partially nonlinear nature, but is carried out on specific signals falling within a relatively restricted spatial frequency passband and confined receptive field. The second, referred to as nonlinear, involves a highly nonlinear integration of additional, nonspecific afferent signals, generally outside the conventional spatiotemporal frequency passband of a neuron, and also outside of the `classical' receptive field. Some novel aspects of this formulation are: the same neuron may exhibit both quasi-linear and nonlinear behavior; quasi- linear mechanisms may display substantial nonlinearities, possibly accounting for detection of some non-Fourier stimuli. Data are presented to illustrate the idea that white noise analysis methods are well-suited to characterize the spatiotemporal nonlinearities of quasi-linear mechanisms, but fail to provide insight into the processing of nonlinear mechanisms.