Comparison of Signals from Cerebellar Purkinje Cells and Deep Nuclei during Temporal Prediction in Primates

The cerebellum is crucial for predictive motor control and learning, but growing evidence suggests that it also generates forward models for nonmotor functions. Previous studies have reported periodic neuronal activity in the cerebellar dentate nucleus when animals predicted the timing of regularly presented visual stimuli. Since the dentate nucleus is an output structure, this activity likely reflects computations in the cerebellar cortex. Considering that Purkinje cells (PCs), the sole output of the cerebellar cortex, are more numerous than cerebellar nuclear neurons and that nuclear neurons also receive input from mossy and climbing fibers, information integration likely occurs within the cerebellar nuclei. To explore this, we recorded PC activity in the cerebellar crus lobules of three male monkeys trained to detect the omission of periodically flashing visual stimuli and compared it with dentate nucleus data. PCs showed gradually increasing periodic simple spike activity, with amplitudes proportional to the interstimulus intervals. As a population, PC signals slightly preceded those of dentate nucleus neurons and were more temporally variable. However, the individual dentate neuron activity was 84% explained by a linear sum of signals from a small subset of PCs. These results suggest that the main components of cerebellar output signals for temporal prediction may originate from the cerebellar cortex and are integrated within the deep nuclei before being sent to other brain regions. Furthermore, changes in complex spike activity were observed in more than half of the PCs, suggesting that synaptic plasticity in the cerebellar cortex may contribute to modulating these signals.