Purpose: We describe a model of MT cell responses that explains a variety of neurophysiological findings. Methods: The model (first presented in Simoncelli & Heeger, ARVO '93) consists of two stages, corresponding to cortical areas V1 and MT. Each stage computes a weighted linear sum of inputs, followed by halfwave rectification, squaring, and normalization (in which the output is divided by the pooled activity of a large number of cells). Model V1 cells are tuned for spatio-temporal frequency, and model MT cells are tuned for image velocity. The linear weighting function of a model V1 cell determines its orientation and direction selectivity. The weighting function for a particular V1 cell is only mildly constrained by the model, but the relationship between the cell weighting functions is heavily constrained. The linear weighting function of a model MT cell determines its velocity (both speed and direction) selectivity. Again, the individual weighting functions are only mildly constrained, but the relationship between cells is precisely specified. The free parameters of the model are the overall frequency response of the V1 stage, the overall velocity response of the MT stage, the semi-saturation constants used in the two normalization operations, and the spontaneous firing rates in the two stages. Results: We demonstrate that the model is consistent with a wide range of experimental data. In particular, we show that the model explains data published by Maunsell & Van Essen (1983), Albright (1984), Movshon et. al. (1985), Allman (1985), Rodman & Albright (1989), Orban (1993), Britten et al (1993), and Snowden et al (1993). Conclusions: Our simulation results provide compelling evidence that this model accounts for much of the published data recorded from MT cells. This theoretical work also leads to several testable predictions that will be discussed. Warning: Undefined array key 2 in /System/Volumes/Data/e/1.3/p1/lcv/html_public/pubs/makeAbs.php on line 304