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Record W2066968856 · doi:10.1167/iovs.14-16177

Neural Circuits That Drive Binocular Eye Movements: Implications for Understanding and Correcting Strabismus

2015· review· en· W2066968856 on OpenAlexaff
Kathleen E. Cullen

Bibliographic record

VenueInvestigative Ophthalmology & Visual Science · 2015
Typereview
Languageen
FieldMedicine
TopicOphthalmology and Eye Disorders
Canadian institutionsMcGill University
Fundersnot available
KeywordsStrabismusBinocular visionEye movementOptometryPsychologyNeuroscienceComputer scienceMedicineOphthalmologyComputer vision

Abstract

fetched live from OpenAlex

Strabismus is the misalignment of the eyes and is estimated to be present in ~2% to 4% of the North American infant population. Surprisingly, to date, there is no consensus regarding the cause of strabismus. While it is commonly thought to be the result of dysfunctional orbital and/or eye muscle properties (reviewed in Refs. 1, 2), recent work emphasizes that strabismus can also be caused by the brain’s inability to transform binocular visual inputs into the motor commands required for coordinated eye motion at cortical as well as subcortical levels (reviewed in Refs. 3, 4). To gain a better understanding of the underlying changes in sensorimotor control that are responsible for strabismus, researchers have begun to perform studies in nonhuman primates. Typically, eye misalignment is induced using either surgical or visual methods (e.g., the weakening of the eye muscles or nerves versus the wearing of prism goggles). As adults, these strabismic monkeys make eye movements much like strabismus patients (i.e., consistent with estropia or exotropia). A study in this month’s issue of IOVS by Walton et al. demonstrates that when strabismus is induced in young monkeys either by the wearing of prism goggles or by medial rectus tenotomy, the activity of individual abducens nucleus neurons is reduced compared to that observed in monkeys raised with normal visual input. Since abducens neurons control the eye muscles that drive horizontal eye movements, these results provide evidence that changes in either sensory input or the eye muscles during development can have profound effects on the set point of the motor pathways required for accurate binocular control. In normal animals, the premotor and motoneurons that control eye movements preferentially encode the movement of an individual eye rather than the conjugate component of each eye movement (reviewed in Ref. 8). In their current study, Walton and colleagues found that this is also true for abducens neurons in strabismic monkeys. Moreover, both neuronal monocular tuning and eye movement sensitivities were normal. Instead, the authors’ data indicate a marked loss of tonic activity in the motoneuron input to the eye muscles. While premotor pathways are also altered in strabismic monkeys (the stimulation of premotor saccadic neurons in the pons produces abnormally disconjugate eye movements, and neurons in the supraoculomotor area [SOA] statically encode the angle of strabismus), there is currently no clear explanation for the observed loss of tonic activity in abducens. In this context, further studies of visuomotor pathways, as well as the abducens internuclear neuron to medial rectus motoneuron pathway, will likely reveal key abnormalities. For instance, Van Horn et al. recently identified a subclass of neurons in the rostral superior colliculus that robustly encode vergence angle in normal animals, suggesting this as a potentially interesting site to explore. Ultimately, such targeted experiments, comparing how the brain is normally circuited to how it develops in animals with different forms of strabismus, are needed to develop more optimally directed therapies for correcting this relatively common condition.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.704
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0010.001
Science and technology studies0.0010.006
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
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 head0.264
GPT teacher head0.454
Teacher spread0.190 · 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.

Study designOther design
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

Citations5
Published2015
Admission routes1
Has abstractyes

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