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Object‐substitution masking modulates spatial attention deployment and the encoding of information in visual short‐term memory: Insights from occipito‐parietal ERP components

2010· article· en· W1523024705 on OpenAlexafffund
David J. Prime, Patrik Pluchino, Martin Eimer, Roberto Dell’Acqua, Pierre Jolicœur

Bibliographic record

VenuePsychophysiology · 2010
Typearticle
Languageen
FieldNeuroscience
TopicNeural and Behavioral Psychology Studies
Canadian institutionsUniversité de Montréal
FundersCanadian Institutes of Health Research
KeywordsBackward maskingPsychologyN2pcCognitive psychologyMasking (illustration)Offset (computer science)Visual maskingVisual short-term memoryEvent-related potentialNeuroscienceComputer scienceCommunicationVisual attentionElectroencephalographyWorking memoryVisual perceptionCognition

Abstract

fetched live from OpenAlex

If object-substitution masking (OSM) arises from mask representations replacing target representations, OSM should impede the formation of representations in visual short-term memory (VSTM). We utilized event-related potentials to examine the effect of OSM on target processing. An N2pc was observed on trials with delayed-offset masks, indicating that focused attention was directed to the target. The sustained posterior contralateral negativity (SPCN), an index of VSTM storage, was observed in delayed-offset trials only on trials with correct responses. This supports the hypothesis that inaccurate performance on delayed-offset trials arises from a failure to encode the target in VSTM. On co-termination trials, accuracy was high and neither the N2pc nor SPCN was observed. This indicates that, in the absence of masking, the task was accomplished by maintaining a diffuse attentional state that enabled the joint encoding of the potential target items.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.669
Threshold uncertainty score0.421

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 studies0.0000.001
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 head0.043
GPT teacher head0.319
Teacher spread0.276 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations33
Published2010
Admission routes2
Has abstractyes

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