Individual Differences in Face Identity Processing with Fast Periodic Visual Stimulation
Bibliographic record
Abstract
A growing body of literature suggests that human individuals differ in their ability to process face identity. These findings mainly stem from explicit behavioral tasks, such as the Cambridge Face Memory Test (CFMT). However, it remains an open question whether such individual differences can be found in the absence of an explicit face identity task and when faces have to be individualized at a single glance. In the current study, we tested 49 participants with a recently developed fast periodic visual stimulation (FPVS) paradigm [Liu-Shuang, J., Norcia, A. M., & Rossion, B. An objective index of individual face discrimination in the right occipitotemporal cortex by means of fast periodic oddball stimulation. Neuropsychologia, 52, 57-72, 2014] in EEG to rapidly, objectively, and implicitly quantify face identity processing. In the FPVS paradigm, one face identity (A) was presented at the frequency of 6 Hz, allowing only one gaze fixation, with different face identities (B, C, D) presented every fifth face (1.2 Hz; i.e., AAAABAAAACAAAAD…). Results showed a face individuation response at 1.2 Hz and its harmonics, peaking over occipitotemporal locations. The magnitude of this response showed high reliability across different recording sequences and was significant in all but two participants, with the magnitude and lateralization differing widely across participants. There was a modest but significant correlation between the individuation response amplitude and the performance of the behavioral CFMT task, despite the fact that CFMT and FPVS measured different aspects of face identity processing. Taken together, the current study highlights the FPVS approach as a promising means for studying individual differences in face identity processing.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.004 |
| Open science | 0.001 | 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".