Modulation of oculomotor control & adaptation with cerebellar TMS: effects on saccades.
Bibliographic record
Abstract
The cerebellum plays a significant role in oculomotor control. Previous fMRI, repetitive TMS and lesion studies indicate its involvement in the adaptation of saccadic eye movements in humans. Building on this work, we applied continuous theta-burst (cTBS) TMS to the oculomotor vermis (OMV) of the posterior cerebellum to investigate its specific role in the execution of reactive pro-saccades and their adaptation to a double-step stimulus. 16 healthy controls completed 2 study visits where reactive pro-saccades and their adaptation to a gain reducing double-step stimulus were measured binocularly via infrared oculography at 250Hz. Active or sham cTBS (3-50Hz pulses at 200ms intervals for 40 seconds) was applied to the OMV using a 2x75mm butterfly coil at 80% of the individual's active motor threshold before completing the saccadic tasks at each visit. Stimulation sites were localized using the BrainSight® neuro-navigation system and anatomical landmarks. Compared to sham, active cTBS significantly reduced the adaptation of saccadic gain by 46.8% (p< 0.0001). The adaptive reduction of peak velocity after active cTBS was 79.4% less than sham (p< 0.0001), while the reduction of saccade duration was 55.2% less (p=0.009). Baseline pro-saccade gain was reduced by active (0.97±0.01) vs. sham (0.99±0.009) stimulation (p = 0.034). Baseline latency was not different between active (185ms) and sham (181ms) conditions (p = 0.34) and was not affected by stimulation type after adaptation (active = +1.2ms, sham = +2.5ms, p>0.50). These results demonstrate the central role of the OMV in the feed-forward control and feed-back driven adaptation of reactive pro-saccades, consistent with previous work. In addition, the results are the first to clearly establish the robust inhibitory effects of cTBS on oculomotor control and adaptation when applied to the OMV of the posterior cerebellum. Meeting abstract presented at VSS 2017
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 | 0.000 |
| 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".