Do developmental prosopagnosics with high vs. low levels of autism traits differ in how they process faces?
Bibliographic record
Abstract
Developmental prosopagnosia (DP) studies have routinely excluded individuals with high autism traits, assuming that DPs with high levels of autism traits have qualitatively different mechanisms of face recognition impairment, e.g., caused by social motivational factors. Indeed, autism spectrum disorders (ASD) are associated with face recognition memory and face emotion processing deficits but largely unimpaired face perception and holistic face processing abilities, whereas DPs without ASD have shown face perception and holistic processing deficits in addition to face memory deficits. To investigate the relationship between autism traits and face processing in DP, we administered a large behavioral battery and a face/scene/object/body fMRI localizer to 43 DPs with a wide range of Autism Quotient (AQ) scores as well as 27 healthy controls. When comparing the high (n=15; met broader autism phenotype classification) and low (n=28) AQ DP groups (AQ: 28.33 vs. 14.50; p<.001), we found a similar pattern across face processing tasks, with no differences in face matching (Cambridge Face Perception Test; p=.617), holistic face processing (Inversion effect: p=.644; Part-whole effect: p=.170), featural processing (Eyes: p=.643; Mouth: p=.984), or face memory (Cambridge Face Memory Test; p=.598). Both DP groups performed significantly worse on the face processing tasks compared to the control group (p’s<.05), with the exception of the mouth composite. As expected, the higher AQ group showed significantly decreased face emotion recognition compared to the low AQ group (p=.028). During the fMRI localizer task, both DP groups showed similarly reduced face selectivity in the left occipital and fusiform face areas compared to controls. Notably, the higher AQ DPs also showed decreased face selectivity in the bilateral posterior superior temporal sulcus compared to the lower AQ DPs. These results suggest that high autism traits do not result in qualitatively different face processing in DPs, but are associated with greater face emotion recognition impairments.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".