A popular hypothesis is that the dorsal striatum generates discrete "traffic-light" signals that initiate, maintain and terminate the execution of learned actions. Alternatively, the striatum may continuously monitor the dynamics of movements associated with action execution by processing inputs from somatosensory and motor cortices. Here we recorded the activity of striatal neurons in mice performing a run-and-stop task and characterized the diversity of firing rate modulations relative to run performance (tuning curves) across neurons. We found that the tuning curves could not be statistically clustered in discrete functional groups (start or stop neurons). Rather, their shape varied continuously according to the movement dynamics of the task. Moreover, striatal spiking activity correlated with running speed on a run-by-run basis, and was modulated by task-related non-locomotor movements such as licking. We hypothesize that such moment-to-moment movement monitoring by the dorsal striatum contributes to the learning of adaptive actions and/or updating their kinematics.

The superior colliculus (SC) is a brainstem structure at the crossroad of multiple functional pathways. Several neurophysiological studies suggest that the population of active neurons in the SC encodes the location of a visual target to foveate, pursue or attend to. Although extensive research has been carried out on computational modeling, most of the reported models are often based on complex mechanisms and explain a limited number of experimental results. This suggests that a key aspect may have been overlooked in the design of previous computational models. After a careful study of the literature, we hypothesized that the representation of the whole retinal stimulus (not only its center) might play an important role in the dynamics of SC activity. To test this hypothesis, we designed a model of the SC which is built upon three well-accepted principles: the log-polar representation of the visual field onto the SC, the interplay between a center excitation and a surround inhibition and a simple neuronal dynamics, like the one proposed by the dynamic neural field theory. Results show that the retinotopic organization of the collicular activity conveys an implicit computation that deeply impacts the target selection process.