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Neural control of three-dimensional gaze shifts

2011· book· en· W346301515 on OpenAlexaff
J. Douglas Crawford, Eliana M. Klier

Bibliographic record

VenueOxford University Press eBooks · 2011
Typebook
Languageen
FieldComputer Science
TopicGaze Tracking and Assistive Technology
Canadian institutionsYork University
Fundersnot available
KeywordsGazeSuperior colliculusOrientation (vector space)Reticular formationComputer visionComputer scienceHorizontal planeHead (geology)Artificial intelligenceCommunicationPsychologyNeuroscienceMathematicsGeometryGeologyNucleus

Abstract

fetched live from OpenAlex

In laboratory conditions, with the head restrained and held upright, eye-in-head orientation vectors are constrained to a tilted two-dimensional (2D) range called Listing’s plane. However, in most real-world conditions gaze control utilizes a three-dimensional (3D) range. For example, when the head is allowed to move naturally, the accompanying saccades and vestibulo-ocular reflex movements include coordinated torsional components, out of, and then back into Listing’s plane. The head itself rotates more like a set of Fick gimbals, resulting in a non-planar range of orientation vectors. To control this complex behaviour, the brainstem reticular formation appears to have struck upon an elegant solution: it encodes the 3D components of posture and movement in coordinates that align with the Listing and Fick behavioural constraints, such that its control signals collapse to 2D (zero torsion) when these constraints are upheld, but it retains the capacity for torsional control whenever required. In contrast, the superior colliculus and cortex appear to only encode 2D gaze direction. Surprisingly, after many years of research on this topic, we still know very little—other than a few clues—about the neural mechanisms that transform high-level 2D gaze direction commands into the 3D control signals for eye and head orientation.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.979
Threshold uncertainty score1.000

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 science0.0020.001
Research integrity0.0000.001
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 head0.025
GPT teacher head0.194
Teacher spread0.169 · 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 designTheoretical or conceptual
Domainnot available
GenreOther

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

Citations4
Published2011
Admission routes1
Has abstractyes

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