Differences in own-face but not own-name discrimination between autistic and neurotypical adults: A fast periodic visual stimulation-EEG study
Bibliographic record
Abstract
Self-related processing is thought to be altered in autism, with several studies reporting that autistic individuals show a diminished neural response relative to neurotypicals for their own name and face. However, evidence remains scarce and is mostly based on event-related potential studies. Here, we used EEG to measure the neural activity of autistic adults (20 for faces, 27 for names) and neurotypical adults (24 for faces, 25 for names) while they were watching rapidly alternating faces and names, through a relatively new technique called Fast Periodic Visual Stimulation. We presented strangers' faces or names at a base frequency of 5.77 Hz, while one's own, a close other's, and a specific stranger's face/name was presented at an oddball frequency of 1.154 Hz. The neurotypical group showed a significantly greater response to their own face than both close other and stranger faces, and a greater response for close other than for stranger faces. In contrast, in the autism group, own and close other faces showed stronger responses than the stranger's face, but the difference between own and close other faces was not significant in a bilateral parieto-occipital cluster. No group differences in the enhanced response to familiar names were found. These results replicate and extend results obtained using traditional electroencephalographic techniques which suggest atypical responses to self-relevant stimuli in autism.
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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 | 0.000 |
| 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".