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Record W2169820728 · doi:10.4236/jbbs.2013.31014

How the Brain Process Stimulus-Response Conflict? New Insights from Lateralized Readiness Potentials Scalp Topography and Reaction Times

2013· article· en· W2169820728 on OpenAlexafffund
Marc E. Lavoie, Johannes Stauder

Bibliographic record

VenueJournal of Behavioral and Brain Science · 2013
Typearticle
Languageen
FieldNeuroscience
TopicNeural and Behavioral Psychology Studies
Canadian institutionsUniversité de MontréalInstitut universitaire en santé mentale de Montréal
FundersCanadian Institutes of Health ResearchU.S. Public Health Service
KeywordsStimulus (psychology)PsychologyScalpNeuroscienceCognitive psychologyBiology

Abstract

fetched live from OpenAlex

Stimulus-Response Compatibility (SRC) refers to the fact that some tasks are performed easier and better than others because of the way stimuli and responses are paired with each other. To assess the brain responses to stimulus-response conflicts, we investigated the behavioral (accuracy and Reaction Times: RTs) as well as the physiological response (Lateralized Readiness Potentials: LRP) modulations in a positional blocked and a conditional mixed design in twelve university students. Results revealed that the performance was less accurate and the RTs, as well as the LRP onset, were delayed under the mixed conditional design. A greater compatibility effect was also noted on accuracy, RTs and LRP onset latency in the mixed design. Consistent with these findings, smaller peak activation at fronto-central areas suggests that more selective inhibition is needed in a mixed design context. Despite a smaller activation, the topographical distribution is similar in both designs. These results indicate that the translation time between stimulus- and response codes are greater under the mixed instruction, while the similar LRP topography suggests that common neural structures underlie LRPs in response to both type of designs.

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 score0.543
Threshold uncertainty score0.607

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.002
Scholarly communication0.0010.002
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 head0.085
GPT teacher head0.364
Teacher spread0.279 · 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

Citations3
Published2013
Admission routes2
Has abstractyes

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