Neck Muscle Synergies During Stimulation and Inactivation of the Interstitial Nucleus of Cajal (INC)
Bibliographic record
Abstract
The interstitial nucleus of Cajal (INC) is thought to control torsional and vertical head posture. Unilateral microstimulation of the INC evokes torsional head rotation to positions that are maintained until stimulation offset. Unilateral INC inactivation evokes head position-holding deficits with the head tilted in the opposite direction. However, the underlying muscle synergies for these opposite behavioral effects are unknown. Here, we examined neck muscle activity in head-unrestrained monkeys before and during stimulation (50 muA, 200 ms, 300 Hz) and inactivation (injection of 0.3 mul of 0.05% muscimol) of the same INC sites. Three-dimensional eye and head movements were recorded simultaneously with electromyographic (EMG) activity in six bilateral neck muscles: sternocleidomastoid (SCM), splenius capitis (SP), rectus capitis posterior major (RCPmaj.), occipital capitis inferior (OCI), complexus (COM), and biventer cervicis (BC). INC stimulation evoked a phasic, short-latency ( approximately 5-10 ms) facilitation and later ( approximately 100-200 ms) a more tonic facilitation in the activity of ipsi-SCM, ipsi-SP, ipsi-COM, ipsi-BC, contra-RCPmaj., and contra-OCI. Unilateral INC inactivation led to an increase in the activity of contra-SCM, ipsi-SP, ipsi-RCPmaj., and ipsi-OCI and a decrease in the activity of contra-RCPmaj. and contra-OCI. Thus the influence of INC stimulation and inactivation were opposite on some muscles (i.e., contra-OCI and contra-RCPmaj.), but the comparative influences on other neck muscles were more variable. These results show that the relationship between the neck muscle responses during INC stimulation and inactivation is much more complex than the relationship between the overt behaviors.
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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 | 0.000 |
| 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".