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The Migraine Aura: A Problem for Vision Theory?

2016· article· en· W2737248451 on OpenAlexaff
Alan J. McComas, A.R.M. Upton

Bibliographic record

VenueCritical Reviews in Biomedical Engineering · 2016
Typearticle
Languageen
FieldMedicine
TopicMigraine and Headache Studies
Canadian institutionsMcMaster UniversityMcMaster University Medical Centre
Fundersnot available
KeywordsReceptive fieldVisual cortexOrientation columnNeuroscienceOrientation (vector space)Cortex (anatomy)Binocular neuronsOptical illusionPhysicsBinocular visionSurround suppressionArtificial intelligenceIllusionRetinaStriate cortexComputer visionPsychologyOpticsComputer scienceVisual perceptionGeometryMathematicsPerception

Abstract

fetched live from OpenAlex

The scintillating zigzag pattern that a migraine patient may see as an illusion before the onset of headache offers a unique investigative approach to visual mechanisms. The likeliest interpretation of these zigzags is that they are the spontaneous discharges of the orientation-selective neurons first described in the striate cortex by Hubel and Wiesel (Hubel DH, Wiesel TN. Receptive fields, binocular interaction and functional architecture in the cat's visual cortex. J Physiol (Lond). 1962 Jan;160:106-54; and Hubel DH, Wiesel TN. Receptive fields and functional architecture of monkey striate cortex. J Physiol (London). 1968 Mar;195(1):215-43). Although these cells appear to lie in rows in V1, as Hubel and Wiesel found, very few angles in the visual field are represented; this, and the coarseness of the representation, makes it unlikely that the cells act as feature detectors. The orientation-selective cells could, however, monitor the amount of light falling on the retina and thereby enable color constancy to be achieved. The cells may also serve as coarse movement detectors. The new model of cell organization in human V1 enables us to determine the approximate sizes of the receptive fields of the orientation-selective cells.

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)0.002
metaresearch head score (Gemma)0.017
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.872
Threshold uncertainty score0.992

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.017
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 head0.022
GPT teacher head0.354
Teacher spread0.332 · 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 designNot applicable
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

Citations2
Published2016
Admission routes1
Has abstractyes

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