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Bilateral parietal and contralateral responses during maintenance of unilaterally encoded objects in visual short‐term memory: Evidence from magnetoencephalography

2009· article· en· W2131831134 on OpenAlexaff
Nicolas Robitaille, Stéphan Grimault, Pierre Jolicœur

Bibliographic record

VenuePsychophysiology · 2009
Typearticle
Languageen
FieldNeuroscience
TopicNeural dynamics and brain function
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsMagnetoencephalographyPosterior parietal cortexPsychologyNeuroscienceNegativity effectParietal lobeCortex (anatomy)Visual fieldElectrophysiologyElectroencephalographyCognitive psychology

Abstract

fetched live from OpenAlex

A component of the event-related magnetic field (ERMF) response was observed in magnetoencephalographic signals recorded during the maintenance of information in visual short-term memory (VSTM). This sustained posterior contralateral magnetic (SPCM) field is likely the magnetic equivalent of the sustained posterior contralateral negativity (SPCN) found in electrophysiology. Magnetoencephalography data showed, at the sensor level, a bilateral activation over the parietal cortex that increased in amplitude for higher memory load. Others sensors, also over the parietal cortex, showed an activation pattern similar to the SPCN with higher activation for the hemisphere contralateral to the visual field from which visual information was encoded. These two activation patterns suggest that the SPCN and SPCM are generated by a network of cortical sources that includes bilateral parietal loci, likely intra-parietal/intra-occipital cortex, and contralateral parietal sources.

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 score0.003
Threshold uncertainty score0.010

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)0.0030.000

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 head0.019
GPT teacher head0.279
Teacher spread0.260 · 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

Citations80
Published2009
Admission routes1
Has abstractyes

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