Gaze and Arrows: does the Gaze Following Patch in the posterior temporal cortex differentiate social and symbolic spatial cues?
Bibliographic record
Abstract
Abstract The Gaze Following Patch (GFP) is located in the posterior temporal cortex and has been described as a cortical module dedicated to processing other people’s gaze direction in a domain-specific manner. Thus, it appears to be the neural correlate of Baron-Cohen’s Eye-Direction Detector (EDD) which is one of the core modules in his Mindreading System - a neurocognitive model for the Theory of Mind concept. Inspired by Jerry Fodor’s ideas on the modularity of the mind, Baron-Cohen proposed that, among other things, the individual modules are domain-specific. In the case of the EDD this means that it exclusively processes eye-like stimuli to extract gaze direction and that other stimuli, that may carry directional information as well, are processed elsewhere. If the GFP is indeed EDD’s neural correlate it must meet this expectation. To test this, we compared the GFP’s BOLD activity during gaze-direction following with the activity during arrow-direction following. Contrary to the expectation based on the assumption of domain specificity we did not find a differentiation between gaze and arrow-direction following. In fact, we were not able to reproduce the GFP as presented in previous studies. A possible explanation is that in the present study – unlike previous work –, the gaze stimuli did not contain an obvious change of direction that represented a visual motion. Hence, the critical stimulus component responsible for the identification of the GFP in previous experiments might have been visual motion.
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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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| 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".