Beta band oscillations in the motor thalamus are modulated by visuomotor coordination in essential tremor patients
Bibliographic record
Abstract
Introduction: Beta oscillations in sensorimotor structures contribute to the planning, sequencing, and stopping of movements, functions that are typically associated with the role of the basal ganglia. The presence of beta oscillations (13-30 Hz) in the cerebellar zone of the thalamus (the ventral intermediate nucleus - Vim) indicates that this rhythm may also be involved in cerebellar functions such as motor learning and visuomotor adaptation. Methods: To investigate the possible role of Vim beta oscillations in visuomotor coordination, we recorded local field potential (LFP) and multiunit activity from the Vim of essential tremor (ET) patients during neurosurgery for the implantation of deep brain stimulation (DBS) electrodes. Using a computer, patients performed a visuomotor adaptation task that required coordinating center-out movements with incongruent visual feedback imposed by inversion of the computer display. Results: The results show that, in ET, Vim beta oscillations of the LFP were lower during the incongruent center-out task than during the congruent orientation. Vim firing rates increased significantly during periods of low beta power, particularly on approach to the peripheral target. In contrast, beta power in the subthalamic nucleus of Parkinson's disease (PD) patients did not differ significantly between the incongruent and the congruent orientation of the center-out task. Discussion: The findings support the hypothesis that beta oscillations of the Vim are modulated by novel visuomotor tasks. The inverse relationship between the power of Vim-LFP beta oscillations and Vim firing rates suggest that the suppression of beta oscillations may facilitate information throughput to the thalamocortical circuit by modulation of Vim firing rates.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 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) | 0.002 | 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".