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The interdependence of spatial attention and lexical access as revealed by early asymmetries in occipito‐parietal ERP activity

2007· article· en· W2117263134 on OpenAlexaff
Roberto Dell’Acqua, Francesca Pesciarelli, Pierre Jolicœur, Martin Eimer, Francesca Peressotti

Bibliographic record

VenuePsychophysiology · 2007
Typearticle
Languageen
FieldNeuroscience
TopicNeural and Behavioral Psychology Studies
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsPsychologyN2pcEvent-related potentialNegativity effectLexical decision taskString (physics)Fixation (population genetics)Cognitive psychologyVisual spatial attentionWord (group theory)Selective attentionElectroencephalographyCommunicationVisual attentionNeuroscienceLinguisticsCognition

Abstract

fetched live from OpenAlex

A test of the possible functional interaction between mechanisms subserving spatial attention and lexical access was devised by displaying one green and one red string of letters, one to the left and one to the right of fixation, and having participants attend to a target string defined by color while ignoring the other distractor string. The target string for a delayed lexical decision task could be a word or a nonword. The distractor was always a word. When the target was a word, target and distractor were associatively related on half of the trials and not related in the other trials. The event-related potential time-locked to the onset of the letter strings produced an N2pc (a greater negativity at scalp sites contralateral to the target relative to the ipsilateral sites arising at about 170 ms poststimulus). N2pc amplitude was reduced when the words were related relative to when they were not related. The results provide direct, online evidence that the rapid activation of meaning by visual words can influence the efficiency of the deployment of spatial attention.

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)0.002
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 score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
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)0.0020.000

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 head0.068
GPT teacher head0.411
Teacher spread0.343 · 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

Citations49
Published2007
Admission routes1
Has abstractyes

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