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Record W2017754366 · doi:10.1162/jocn_a_00005

Object-based Neglect Varies with Egocentric Position

2011· article· en· W2017754366 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Cognitive Neuroscience · 2011
Typearticle
Languageen
FieldNeuroscience
TopicSpatial Neglect and Hemispheric Dysfunction
Canadian institutionsMcGill University
FundersDeutsche Forschungsgemeinschaft
KeywordsNeglectPsychologyReference frameObject (grammar)Frame of referenceUnilateral neglectPosition (finance)Representation (politics)Cognitive psychologyComputer visionHemispatial neglectCommunicationArtificial intelligenceFrame (networking)Computer sciencePhysics

Abstract

fetched live from OpenAlex

Different reference frames have been identified to influence neglect behavior. In particular, neglect has been demonstrated to be related to the contralesional side of the subject's body (egocentric reference frames) as well as to the contralesional side of individual objects irrespective of their position to the patient (object-based reference frame). There has been discussion whether this distinction separates neglect into body- and object-based forms. The present experiment aimed to prove possible interactions between object-based and egocentric aspects in spatial neglect. Neglect patients' eye and head movements were recorded while they explored objects at five egocentric positions along the horizontal dimension of space. The patients showed both egocentric as well as object-based behavior. Most interestingly, data analysis revealed that object-based neglect varied with egocentric position. Although the neglect of the objects' left side was strong at contralesional egocentric positions, it ameliorated at more ipsilesional egocentric positions of the objects. The patients showed steep, ramp-shaped patterns of exploration for objects located on the far contralesional side and a broadening of these patterns as the locations of the objects shifted more to the ipsilesional side. The data fitted well with the saliency curves predicted by a model of space representation, which suggests that visual input is represented in two modes simultaneously: in veridical egocentric coordinates and in within-object coordinates.

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.

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)0.002
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 score0.080
Threshold uncertainty score0.497

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.034
GPT teacher head0.250
Teacher spread0.215 · 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