Local Field Potential Oscillations in Primate Cerebellar Cortex: Synchronization With Cerebral Cortex During Active and Passive Expectancy
Bibliographic record
Abstract
Many brain regions, such as the cerebellum, primary somatosensory cortex (SI), and primary motor cortex (MI), interact to produce coordinated actions. Synchronization of local field potentials (LFPs) in sensorimotor cerebral areas has been related to motor performance, often through 10- to 25-Hz oscillatory LFPs. The macaque cerebellar paramedian lobule (PM) also shows 10- to 25-Hz LFP oscillations, which are modulated in a stimulus-response lever press task to get reward (active condition), but also, albeit differently, in a similarly timed stimulus-reward relation (passive condition). This study focuses on simultaneous LFP activity in primate SI or MI and the PM cerebellum during the active (left- or right-hand lever presses) and passive conditions. Results show a similar modulation pattern of 10- to 25-Hz oscillations in the cerebellum, MI, and SI during the active condition (left or right hand), decreasing after stimulus onset, returning, and again decreasing after movement onset. In the passive condition, when the monkey did not move but got reward, all 3 areas show an oscillatory profile where oscillations increase after stimulus onset and last until reward, denoting a role for these oscillations in passive expectancy. However, synchronization between cerebellar LFPs and SI LFPs is higher during the active condition than during the passive condition, and highest for the interested hand. This greater PM-SI synchronization, when the monkey had to press the lever, could represent a form of cerebro-cerebellar communication, perhaps to serve somatosensory processing to accomplish the task; PM-MI synchronization was less selective for the hand used and might carry a more general type of information.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".