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Boven, E.

Publications and source records attributed to Boven, E..

2 recordsLinked to original sources

Cerebellar involvement in self-timing

The cerebellum is well-established in sub-second motor timing, but its role in supra-second interval timing remains unclear. Here, we investigate how cerebellar output influences time estimation over longer timescales. Rats performed an interval timing task, estimating time based on an auditory cue, while chemogenetic inhibition of the lateral cerebellar nucleus assessed its role in both predictable (externally cued) and unpredictable (internally cued) timing conditions. Cerebellar inhibition produced bidirectional effects: delayed action initiation in predictable trials and premature responses in unpredictable trials. Despite slowed movement, overall task success rates remained unchanged, suggesting a specific impairment in temporal estimation rather than motor execution. These findings demonstrate that the cerebellum integrates motor and cognitive processes for supra-second timing, with differential effects on externally guided and self-generated timing. Our results provide evidence that the lateral cerebellum contributes to supra-second interval timing, supporting its role in adaptive behavior across extended timescales.

neuroscience↗

Cerebro-cerebellar networks facilitate learning through feedback decoupling

Behavioural feedback is critical for learning in the cerebral cortex. However, such feedback is often not readily available. How the cerebral cortex learns efficiently despite the sparse nature of feedback remains unclear. Inspired by recent deep learning algorithms, we introduce a systems-level computational model of cerebro-cerebellar interactions. In this model a cerebral recurrent network receives feedback predictions from a cerebellar network, thereby decoupling learning in cerebral networks from future feedback. When trained in a simple sensorimotor task the model shows faster learning and reduced dysmetria-like behaviours, in line with the widely observed functional impact of the cerebellum. Next, we demonstrate that these results generalise to more complex motor and cognitive tasks. Finally, the model makes several experimentally testable predictions regarding (1) cerebro-cerebellar task-specific representations over learning, (2) task-specific benefits of cerebellar predictions and (3) the differential impact of cerebellar and inferior olive lesions. Overall, our work offers a theoretical framework of cerebro-cerebellar networks as feedback decoupling machines.

neuroscience↗