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Record W2047949770 · doi:10.1152/jn.00312.2012

Relationships between neck muscle electromyography and three-dimensional head kinematics during centrally induced torsional head perturbations

2012· article· en· W2047949770 on OpenAlexafffund
Farshad Farshadmanesh, Patrick Byrne, Hongying Wang, Brian D. Corneil, J. Douglas Crawford

Bibliographic record

VenueJournal of Neurophysiology · 2012
Typearticle
Languageen
FieldNeuroscience
TopicMotor Control and Adaptation
Canadian institutionsWestern UniversityYork University
FundersCanadian Institutes of Health ResearchYork University
KeywordsElectromyographyKinematicsNeck musclesAnatomyGazeStimulationPhysical medicine and rehabilitationPsychologyMedicinePhysicsNeuroscience

Abstract

fetched live from OpenAlex

The relationship between neck muscle electromyography (EMG) and torsional head rotation (about the nasooccipital axis) is difficult to assess during normal gaze behaviors with the head upright. Here, we induced acute head tilts similar to cervical dystonia (torticollis) in two monkeys by electrically stimulating 20 interstitial nucleus of Cajal (INC) sites or inactivating 19 INC sites by injection of muscimol. Animals engaged in a simple gaze fixation task while we recorded three-dimensional head kinematics and intramuscular EMG from six bilateral neck muscle pairs. We used a cross-validation-based stepwise regression to quantitatively examine the relationships between neck EMG and torsional head kinematics under three conditions: 1) unilateral INC stimulation (where the head rotated torsionally toward the side of stimulation); 2) corrective poststimulation movements (where the head returned toward upright); and 3) unilateral INC inactivation (where the head tilted toward the opposite side of inactivation). Our cross-validated results of corrective movements were slightly better than those obtained during unperturbed gaze movements and showed many more torsional terms, mostly related to velocity, although some orientation and acceleration terms were retained. In addition, several simplifying principles were identified. First, bilateral muscle pairs showed similar, but opposite EMG-torsional coupling terms, i.e., a change in torsional kinematics was associated with increased muscle activity on one side and decreased activity on the other side. s, whenever torsional terms were retained in a given muscle, they were independent of the inputs we tested, i.e., INC stimulation vs. corrective motion vs. INC inactivation, and left vs. right INC data. These findings suggest that, despite the complexity of the head-neck system, the brain can use a single, bilaterally coupled inverse model for torsional head control that is valid across different behaviors and movement directions. Combined with our previous data, these new data provide the terms for a more complete three-dimensional model of EMG: head rotation coupling for the muscles and gaze behaviors that we recorded.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.062
GPT teacher head0.271
Teacher spread0.209 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations7
Published2012
Admission routes2
Has abstractyes

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