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Effect of connectivity and bistability on the visual potentials evoked by illusory figures

2006· article· en· W2001605938 on OpenAlexaff
Mathieu B. Brodeur, Franco Leporé, Caroline Veilleux, Yasmine Alyanak, J. Bruno Debruille

Bibliographic record

VenueNeuroreport · 2006
Typearticle
Languageen
FieldNeuroscience
TopicVisual perception and processing mechanisms
Canadian institutionsUniversité de MontréalMcGill UniversityDouglas Mental Health University Institute
Fundersnot available
KeywordsBistabilityPerceptionPsychologyNegativity effectNeuroscienceCognitive psychologyIllusory contoursVisual perceptionOptical illusionPhysicsQuantum mechanics

Abstract

fetched live from OpenAlex

The present study aimed at testing functional hypotheses regarding two brain potentials elicited by illusory figures. Accordingly, the N1 potential indexes mechanisms connecting the separate parts of the illusory form, whereas a subsequent negative potential indexes compensatory processes triggered by perceptual difficulty. Here, perceptual difficulty was induced by bistability; that is, by equating the probability of perceiving the illusory form to that of perceiving the independent separate parts. We compared the brain potentials evoked by a strongly connected illusory square, with almost no bistability, with those evoked by a weakly connected illusory square presenting strong bistability. Consistent with our hypotheses, the latter figure evoked the smallest N1 and a larger negative component peaking at 360 ms (N360). These results strengthen the link between N1 and connection and between negativity to perceptual difficulty and perceptual difficulty.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.023
GPT teacher head0.309
Teacher spread0.287 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations3
Published2006
Admission routes1
Has abstractyes

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