Cerebellar associative learning underlies skilled reach adaptation

Autor: Dylan J. Calame, Matthew I. Becker, Abigail L. Person
Rok vydání: 2023
Předmět:
Zdroj: Nature Neuroscience.
ISSN: 1546-1726
1097-6256
Popis: Cerebellar output has been shown to enhance movement precision by scaling the decelerative phase of reaching movements in mice. We hypothesized that during reach, initial kinematics cue late-phase adjustments through cerebellar associative learning. We identify a population-level response in mouse PCs that scales inversely with reach velocity, suggesting a candidate mechanism for anticipatory control to target limb endpoint. We next interrogate how such a response is generated by combining high-density neural recordings with closed-loop optogenetic stimulation of cerebellar mossy fiber afferents originating in the pontine nuclei during reach, using perturbation schedules reminiscent of classic adaptation paradigms. We found that reach kinematics and PC electrophysiology adapt to position-locked mossy fiber perturbations and exhibit aftereffects when stimulation is removed. Surprisingly, we observed partial adaptation to position-randomized stimulation schedules but no opposing aftereffect. A model that recapitulated these findings provided novel insight into how the cerebellum deciphers cause-and-effect relationships to adapt.
Databáze: OpenAIRE
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