Executive task-set inertia manifests via response suppression and not vector inversion
Bibliographic record
Abstract
Alternating between different tasks represents an executive function essential to daily living. In the oculomotor literature reaction times (RT) for a 'standard' stimulus-driven (SD) prosaccade (i.e., saccade to veridical target location at target onset) increase when preceded by a 'non-standard' antisaccade (i.e., saccade mirror-symmetrical to target location at target onset), whereas the converse does not elicit a switch-cost. The prosaccade switch-cost has been attributed to lingering neural activity – or task-set inertia – related to prosaccade suppression (i.e., response suppression) and decoupling stimulus-response spatial relations (i.e., vector inversion). It is, however, unclear whether response suppression and/or vector inversion contribute to this switch-cost. Here, Experiment 1 had participants alternate (i.e., AABB paradigm) between minimally delayed (MD) pro- and antisaccades. MD saccades require responses after target extinction necessitating response suppression across pro- and antisaccades – used to determine whether vector inversion contributes to a task-set inertia. In Experiment 2, participants alternated between SD pro- and MD antisaccades to determine if a task switch-cost is selectively imparted when a stimulus-driven and standard response is preceded by a non-standard response. Experiment 1 showed that RTs for MD pro- and antisaccades were not influenced by the preceding trial-type; i.e., vector inversion did not engender a switch-cost. Experiment 2 showed that RTs for SD prosaccades were increased when preceded by a MD antisaccade. Accordingly, the executive demands of response suppression engendered a task-set inertia for a subsequent stimulus-driven and standard response (i.e., SD prosaccade) – a finding supporting the view that response suppression is a hallmark feature of executive function.Acknowledgments: Natural Sciences and Engineering Research Council (NSERC)
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".