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Record W2152029346 · doi:10.1162/jocn.2009.21098

When Time Shapes Behavior: fMRI Evidence of Brain Correlates of Temporal Monitoring

2008· article· en· W2152029346 on OpenAlexaff
Antonino Vallesi, Anthony R. McIntosh, Tim Shallice, Donald T. Stuss

Bibliographic record

VenueJournal of Cognitive Neuroscience · 2008
Typearticle
Languageen
FieldNeuroscience
TopicNeural and Behavioral Psychology Studies
Canadian institutionsUniversity of TorontoBaycrest Hospital
Fundersnot available
KeywordsPsychologyFunctional magnetic resonance imagingStimulus (psychology)Cognitive psychologyPrefrontal cortexNeural correlates of consciousnessNeuroscienceCognitionAudiology

Abstract

fetched live from OpenAlex

Time processing may shape behavior in several ways, although the underlying neural correlates are still poorly understood. When preparatory intervals between stimuli vary randomly in a block, for instance, responses are faster as the interval gets longer. This effect, known as variable foreperiod (FP) effect, has been attributed to a process monitoring the conditional probability of stimulus occurrence as the interval increases. Previous evidence points to the right dorsolateral prefrontal cortex (DLPFC) as a possible node for this time-monitoring process. The present study addresses this hypothesis with functional magnetic resonance imaging (fMRI). Block-design fMRI was used on 14 young participants while they performed a visual discrimination task with fixed and variable preparatory intervals (FPs) of 1 and 3 sec. In the variable versus fixed FP contrast, the right DLPFC and a visual area were more activated in the subgroup of participants who showed a reliable variable FP effect than in another subgroup who did not show that effect. Only the activation in the right DLPFC was supported by a significant interaction between FP condition (variable vs. fixed) and group. This finding may reflect possible differences in the strategy adopted by the two subgroups of participants while performing the task. Although results suggest that many brain areas may be involved in preparation over time, the role of the right DLPFC is critical to observe the strategically mediated behavioral effects in the variable FP paradigm.

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)0.004
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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.122
Threshold uncertainty score0.682

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.002
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.209
GPT teacher head0.397
Teacher spread0.188 · 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

Citations100
Published2008
Admission routes1
Has abstractyes

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