Fig. 7.

Working model of how FSI–SPN circuit contributes to continuous pursuit. a Schematic diagram of the FSI–SPN feedforward inhibition circuit. Note that in the equation for velocity, distance refers to distance to target. This equation only applies to self-velocity during continuous pursuit. As shown here, excitatory cortical inputs reach both the FSI and SPN. In this case, some excitatory input represents distance to target, a key error signal used to guide pursuit behavior, and the FSI relays a slightly delayed version of the same signal to the SPN. Thus the delayed distance signal (Distance_t−1) is subtracted from the distance signal (Distance_t), and the SPN output reflects the difference between these two signals, i.e. the change in distance in this time step. As the feedforward inhibition circuit can function as a differentiator, the velocity command is proportional to the change in distance in a direction-specific manner. b Actual traces from our experiments illustrating the variables used in the model. c The model is compared with actual data using simultaneously recorded left distance FSI and left velocity SPN from the same mouse (same hemisphere). Using actual distance measure as an estimate of the Distance_t signal (shifted by 100 ms to account for the delay in the perceptual system) sent to the striatum, and FSI activity as the measure of the Distance_t−1 signal sent to the SPN, a subtraction generates a difference signal (model) that is compared to the activity of an actual left velocity SPN. d Model output is highly similar to right velocity SPN output (Pearson’s r, p < 0.0001. e Same as c, except that the model is generated using a right distance FSI. The model is compared with actual data using simultaneously recorded right distance FSI and right velocity SPN. f High correlation between model output and right velocity SPN output (p < 0.0001). Source data are provided as a Source Data file