Investigating the face inversion effect in adults with Autism Spectrum Disorder using the fast periodic visual stimulation paradigm
Bibliographic record
Abstract
Fast periodic visual stimulation (FPVS) is a powerful method for investigating the brain activity underlying human face processing. Previous studies have shown that FPVS provides a reliable index of the face inversion effect (FIE) (Liu-Shuang et al., 2013) and individual differences in face recognition ability (Xu et al., 2014). In the current study, the FPVS method was used to compare the discrimination of upright and inverted faces of 6 adults with Autism Spectrum Disorder (ASD) and 6 age-matched typically developed (TD) control participants. A repeated face stimulus (A) was presented at a frequency of 6Hz (F) for a 60-second block with a different oddball face (B, C, D) interspersed at every 5th cycle of presentation (F/5=1.2Hz) (i.e., AAAABAAAACAAAAD....). Faces within each 60-second block were presented either in their upright or inverted orientations. It is hypothesized that the 6Hz response reflects sensitivity to stimuli belonging to the generic face category whereas the 1.2Hz oddball response indicates sensitivity to a particular individuated face. The results showed that the repeated face stimuli produced an enhanced EEG signal at the fundamental 6Hz frequency and its harmonics (12Hz, 18Hz, etc.) with the largest activation found at medial-occipital electrode sites. Both the ASD and TD groups showed the FIE in which upright faces elicited a greater EEG amplitude than inverted faces. At the 1.2Hz frequency and its harmonics (2.4Hz, 3.6Hz, etc.) , participants in the TD group showed the FIE where a greater signal was generated by the upright oddball face than the inverted oddball face. In contrast, participants in the ASD group exhibited the same EEG response to the upright and inverted oddball face. The lack of the FIE to the individuated oddball face in the ASD group is consistent with the behavioral findings indicating that adults with ASD have difficulty discriminating individual faces. Meeting abstract presented at VSS 2015
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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 | 0.000 |
| 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) | 0.001 | 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".