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Spatial layout of letters in nonwords affects visual short‐term memory load: Evidence from human electrophysiology

2010· article· en· W2166345164 on OpenAlexafffund
David Prime, Roberto Dell’Acqua, Martin Arguin, Frédéric Gosselin, Pierre Jolicœur

Bibliographic record

VenuePsychophysiology · 2010
Typearticle
Languageen
FieldNeuroscience
TopicNeural and Behavioral Psychology Studies
Canadian institutionsUniversité de Montréal
FundersCanadian Institutes of Health Research
KeywordsPsychologyNegativity effectElectrophysiologyContrast (vision)CommunicationWord (group theory)Visual short-term memoryCognitive psychologyNeuroscienceVisual memoryArtificial intelligenceLinguisticsComputer scienceCognition

Abstract

fetched live from OpenAlex

The sustained posterior contralateral negativity (SPCN) was used to investigate the effect of spatial layout on the maintenance of letters in VSTM. SPCN amplitude was measured for words, nonwords, and scrambled nonwords. We reexamined the effects of spatial layout of letters on SPCN amplitude in a design that equated the mean frequency of use of each position. Scrambled letters that did not form words elicited a larger SPCN than either words or nonwords, indicating lower VSTM load for nonwords presented in a typical horizontal array than the load observed for the same letters presented in spatially scrambled locations. In contrast, prior research has shown that the spatial extent of arrays of simple stimuli did not influence the amplitude of the SPCN. Thus, the present results indicate the existence of encoding and VSTM maintenance mechanisms specific to letter and word processing.

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 categoriesMeta-epidemiology (narrow)
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 score0.281
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.066
GPT teacher head0.388
Teacher spread0.321 · 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 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

Citations9
Published2010
Admission routes2
Has abstractyes

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