Dissociating Response Conflict from Numerical Magnitude Processing in the Brain: An Event-Related fMRI Study
Bibliographic record
Abstract
Functional neuroimaging studies of numerical cognition have repeatedly associated activation of the intraparietal sulcus (IPS) with number processing. During number comparison, the IPS has been found to be modulated by the numerical distance. This has lead to the contention that the IPS houses the internal representation of numerical magnitude. However, this theory has been challenged by the argument that IPS activation may reflect domain-general response selection. In the present study, we used the numerical size congruity paradigm to further elucidate the role played by the IPS in number comparison. In an event-related, functional magnetic resonance imaging (fMRI) study, participants judged which of two number words was numerically larger. In addition to the numerical distance, physical stimulus size was varied such that physical size and numerical magnitude were either (a) congruent (e.g., numerically smaller number printed in smaller font) or (b) incongruent (e.g., numerically larger number printed in smaller font). This allowed for the study of both the main effects and the interaction of numerical distance and stimulus congruency. A main effect of numerical distance was found in bilateral regions of the IPS. However, these parietal areas were not significantly modulated by congruency or the interaction of distance and congruency. Instead, the main effect of congruency and an interaction of distance and congruency were observed in anterior cingulate and prefrontal cortices. These findings suggest some degree of independence between the processing of numerical distance and size congruity, lending support for the hypothesis that distance effects in IPS reflect the underlying representation of numerical magnitude.
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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 | 0.001 | 0.003 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".