Back

Behavior-Dependent Immediate Early Gene Activation in the Mouse Cerebellum

Sholomiski, M.; Yon, V.; Mudlaff, F.; Suvrathan, A.

2026-09-08 neuroscience
10.64898/2026.09.03.745918 bioRxiv
Show abstract

The cerebellum supports a wide range of motor and non-motor behaviors, yet the specific cerebellar regions and neuronal populations underlying this functional diversity remain poorly understood. Here, we mapped patterns of immediate early gene activation in the cerebellar cortex during the accelerating rotarod task, an established form of cerebellum-dependent motor learning. Using the immediate early gene c-Fos to identify cells active during the task, we found significantly greater activation throughout the vermis and in crus I of the hemispheres, specifically within the molecular and granule cell layers, compared to naive controls. However, a second control group, which was exposed to the rotarod apparatus but not placed on the rotating rod, revealed similar patterns of c-Fos expression, suggesting that novelty contributed substantially to the observed activation. To separate this potential novelty signal from the motor component of the task, mice were habituated to the apparatus prior to testing. This habituation resulted in an overall decrease in c-Fos expression across cerebellar lobules, with significant motor activity-related differences found in the anterior vermis. Finally, to determine how learning influences c-Fos expression patterns, mice were subjected to a multi-day motor learning paradigm in which genetic tagging of c-Fos-expressing neurons was performed on day 1, followed by c-Fos immunostaining on day 5. We found that, in mice that had learned the task, there was no significant increase in c-Fos signal above naive controls, indicating that rotarod task performance no longer recruited the same level of cerebellar cortical activity, consistent with a potentially reduced role for the cerebellar cortex once the task is well learned. Overall, these findings reveal distinct patterns of activation associated with novelty, motor behaviour, and learning, providing a framework for linking behavior to regional cerebellar function.

Matching journals

The top 5 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.