Synchronization in primate cerebellar granule cell layer local field potentials: Basic anisotropy and dynamic changes during active expectancy
Bibliographic record
Abstract
The cerebellar cortex is remarkable for its organizational regularity, out of which task-related neural networks should emerge. In Purkinje cells, both complex and simple spike network patterns are evident in sensorimotor behavior. However, task-related patterns of activity in the granule cell layer (GCL) have been less studied. We recorded local field potential (LFP) activity simultaneously in pairs of GCL sites in monkeys performing an active expectancy (lever-press) task, in passive expectancy, and at rest. LFP sites were selected when they showed strong 10-25 Hz oscillations; pair orientation was in stereotaxic sagittal and coronal (mainly), and diagonal. As shown previously, LFP oscillations at each site were modulated during the lever-press task. Synchronization across LFP pairs showed an evident basic anisotropy at rest: sagittal pairs of LFPs were better synchronized (more than double the cross-correlation coefficients) than coronal pairs, and more than diagonal pairs. On the other hand, this basic anisotropy was modifiable: during the active expectancy condition, where sagittal and coronal orientations were tested, synchronization of LFP pairs would increase just preceding movement, most notably for the coronal pairs. This lateral extension of synchronization was not observed in passive expectancy. The basic pattern of synchronization at rest, favoring sagittal synchrony, thus seemed to adapt in a dynamic fashion, potentially extending laterally to include more cerebellar cortex elements. This dynamic anisotropy in LFP synchronization could underlie GCL network organization in the context of sensorimotor tasks.
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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) | 0.000 | 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".