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Record W2051203380 · doi:10.1152/jn.01156.2003

Time Course of Vestibuloocular Reflex Suppression During Gaze Shifts

2004· article· en· W2051203380 on OpenAlexaff
Kathleen E. Cullen, Marko Huterer, Danielle A. Braidwood, Pierre A. Sylvestre

Bibliographic record

VenueJournal of Neurophysiology · 2004
Typearticle
Languageen
FieldNeuroscience
TopicVestibular and auditory disorders
Canadian institutionsMcGill University
Fundersnot available
KeywordsGazeVestibulo–ocular reflexAudiologyPsychologyReflexNeuroscienceMedicine

Abstract

fetched live from OpenAlex

Although numerous investigations have probed the status of the vestibuloocular (VOR) during gaze shifts, its exact status remains strangely elusive. The goal of the present study was to precisely evaluate the dynamics of VOR suppression immediately before, throughout, and just after gaze shifts. A torque motor was used to apply rapid (100 degrees/s), short-duration (20-30 ms) horizontal head perturbations in three Rhesus monkeys. The status of the VOR elicited by this transient head perturbation was first compared during 15, 40, and 60 degrees gaze shifts. The level of VOR suppression just after gaze-shift onset (40 ms) increased with gaze-shift amplitude in two monkeys, approaching values of 80 and 35%. In contrast, in the third monkey, the VOR was not significantly attenuated for all gaze-shift amplitudes. The time course of VOR attenuation was then studied in greater detail for all three monkeys by imposing the same short-duration head perturbations 40, 100, and 150 ms after the onset of 60 degrees gaze shifts. Overall we found a consistent trend, in which VOR suppression was maximal early in the gaze shift and progressively recovered to reach normal values near gaze-shift end. However, the high variability across subjects prevented establishing a unifying description of the absolute level and time course of VOR suppression during gaze shifts. We propose that differences in behavioral strategies may account, at least in part, for these differences between subjects.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.043
Threshold uncertainty score0.483

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.015
GPT teacher head0.269
Teacher spread0.254 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations67
Published2004
Admission routes1
Has abstractyes

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