Activation of Preexisting and Acquired Face Representations: The N250 Event-related Potential as an Index of Face Familiarity
Bibliographic record
Abstract
Electrophysiological studies using event-related potentials have demonstrated that face stimuli elicit a greater negative brain potential in right posterior recording sites 170 msec after stimulus onset (N170) relative to nonface stimuli. Results from repetition priming paradigms have shown that repeated exposures of familiar faces elicit a larger negative brainwave (N250r) at inferior temporal sites compared to repetitions of unfamiliar faces. However, less is known about the time course and learning conditions under which the N250 face representation is acquired. In the familiarization phase of the Joe/no Joe task, subjects studied a target "Joe" face ("Jane" for female subjects) and, during the course of the experiment, identified a series of sequentially presented faces as either Joe or not Joe. The critical stimulus conditions included the subject's own face, a same-sex Joe ( Jane) face and a same-sex "other" face. The main finding was that the subject's own face produced a focal negative deflection (N250) in posterior channels relative to nontarget faces. The task-relevant Joe target face was not differentiated from other nontarget faces in the first half of the experiment. However, in the second half, the Joe face produced an N250 response that was similar in magnitude to the own face. These findings suggest that the N250 indexes two types of face memories: a preexperimentally familiar face representation (i.e., the "own face" and a newly acquired face representation (i.e., the Joe/Jane face) that was formed during the course of the experiment.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".