A Cortical Network Sensitive to Stimulus Salience in a Neutral Behavioral Context Across Multiple Sensory Modalities
Bibliographic record
Abstract
Stimulus salience depends both on behavioral context and on other factors such as novelty and frequency of occurrence. The temporo-parietal junction (TPJ) responds preferentially to behaviorally relevant stimuli and is thought to play a general role in detecting salient stimuli. If so, it should respond preferentially to novel or infrequent events, even in a neutral behavioral context. To test this hypothesis, we used event-related functional magnetic resonance imaging (fMRI) to identify brain regions sensitive to the novelty of visual, auditory, and tactile stimuli during passive observation. Cortical regions with a greater response to novel than familiar stimuli across all modalities were identified at two sites in the TPJ region: the supramarginal gyrus (SMG) and superior temporal gyrus. The right inferior frontal gyrus (IFG), right anterior insula, left anterior cingulate cortex (ACC), and left inferior temporal gyrus also showed sensitivity to novelty. The novelty-sensitive TPJ activation in SMG overlaps a region previously identified as sensitive behavioral context. This region may play a general role in identifying salient stimuli, whether the salience is due to the current behavioral context or not. The IFG activation overlaps regions previously identified as responsive to nonnovel sensory events regardless of behavioral context. The IFG may therefore play a general role in stimulus evaluation rather than a specific role in identifying novel stimuli. The ACC activation lies in a region active during complex response-selection tasks, suggesting a general role in detecting and/or planning responses to salient events. A frontal-parietal-cingulate network may serve to identify and evaluate salient sensory stimuli in general.
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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 | 0.001 |
| 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 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".