Dynamic random-dot stimuli have been widely used to explore central mechanisms of motion processing. We have measured the responses of neurons in area MT of the alert monkey while we varied the strength and direction of the motion signal in such displays. The strength of motion is controlled by the proportion of spatiotemporally correlated dots, which we term the correlation of the stimulus. For many MT cells, responses varied approximately linearly with stimulus correlation. When they occurred, nonlinearities were equally likely to be either positively or negatively accelerated. We also explored the relationship between response magnitude and response variance for these cells and found, in general agreement with other investigators, that this relationship conforms to a power law with an exponent slightly greater than 1. The variance of the cells' discharge is little influenced by the trial-to-trial fluctuations inherent in our stochastic display, and is therefore likely to be of neural origin. Linear responses to these stochastic motion stimuli are predicted by simple, low-level motion models incorporating sensors having relatively broad spatial and temporal frequency tuning.

We investigated the dynamics of neurons in the striate cortex (V1) and the lateral geniculate nucleus (LGN) to study the transformation in temporal-frequency tuning between the LGN and V1. Furthermore, we compared the temporal-frequency tuning of simple with that of complex cells and direction-selective cells with nondirection-selective cells, in order to determine whether there are significant differences in temporal-frequency tuning among distinct functional classes of cells within V1. In addition, we compared the cells in the primary input layers of V1 (4a, 4cα, and 4cβ) with cells in the layers that are predominantly second and higher order (2, 3, 4b, 5, and 6). We measured temporal-frequency responses to drifting sinusoidal gratings. For LGN neurons and simple cells, we used the amplitude and phase of the fundamental response. For complex cells, the elevation of impulse rate (F0) to a drifting grating was the response measure. There is significant low-pass filtering between the LGN and the input layers of V1 accompanied by a small, 3-ms increase in visual delay. There is further low-pass filtering between V1 input layers and the second- and higher-order neurons in V1. This results in an average decrease in high cutoff temporal-frequency between the LGN and V1 output layers of about 20 Hz and an increase in average visual latency of about 12–14 ms. One of the most salient results is the increased diversity of the dynamic properties seen in V1 when compared to the cells of the lateral geniculate, possibly reflecting specialization of function among cells in V1. Simple and complex cells had distributions of temporal-frequency tuning properties that were similar to each other. Direction-selective and nondirection-selective cells had similar preferred and high cutoff temporal frequencies, but direction-selective cells were almost exclusively band-pass while nondirection-selective cells distributed equally between band-pass and low-pass categories. Integration time, a measure of visual delay, was about 10 ms longer for V1 than LGN. In V1 there was a relatively broad distribution of integration times from 40–80 ms for simple cells and 60–100 ms for complex cells while in the LGN the distribution was narrower.