Tsukuba, Japan—Everyday behaviors, such as braking at a red light or opening an app upon seeing a notification, are shaped by associative learning, wherein the brain links sensory cues to motor actions. Although recent studies have suggested that the cerebellum contributes to this process, the precise neural mechanism underlying its involvement has remained unclear.
In this study, researchers recorded neuronal activity in the cerebellar dentate nucleus of Japanese monkeys performing a visuomotor association task. The monkeys learned to make leftward or rightward eye movements in response to two distinct images. The team discovered numerous neurons exhibiting sustained visual activity, particularly during the learning phase. These responses varied according to the image, indicating that sustained activity encodes both the learning state and image-movement associations. Moreover, stronger responses during learning corresponded to greater differentiation between images. This finding suggests that cerebellar signals enhance visual discrimination in a learning-dependent manner, thereby facilitating the formation of precise visuomotor associations.
These findings uncover a previously unknown mechanism wherein cerebellar signals amplify goal-related information to support associative learning. Given the cerebellum's uniform circuitry, this mechanism could influence a wide range of cognitive functions beyond motor control.
###
This work was supported in part by grants from JST, PRESTO (grant numbers: JPMJPR21S4; MEXT, 21H05800 and 21H05036), and the Takeda Science Foundation.
Original Paper
Title of original paper:
Sustained visual signals in the primate cerebellar dentate nucleus drive associative learning
Journal:
Communications Biology
DOI:
10.1038/s42003-025-09068-7
Correspondence
Assistant Professor KUNIMATSU, Jun
Institute of Medicine, University of Tsukuba
Related Link
Journal
Communications Biology
Article Title
Sustained visual signals in the primate cerebellar dentate nucleus drive associative learning
Article Publication Date
18-Nov-2025