Asymmetric relationship in representations of facial identity and expression for novel faces within the human visual system
Bibliographic record
Abstract
Cognitive models of face processing suggest the existence of parallel streams that are specialized for identity versus expression perception; furthermore, neuroimaging data suggests that there may be distinct anatomic correlates for each of these processes. However, there is evidence that the neural representations of expression and identity are not completely independent. We have shown that aftereffects in the perception of expression are modulated by the identity of the adapting face, suggesting both identity-dependent and identity-independent representations of facial expression. In the present experiment, we asked whether aftereffects in the perception of identity showed a similar modulation by facial expression, which would suggest the existence of expression-dependent and expression-independent representations of facial identity. We measured the magnitude of aftereffects from three different adapting stimuli on the perception of identity in ambiguous morphed faces. ‘Same-picture/expression-congruent’ adapting stimuli were the images used to create the morphs. ‘Different-picture/expression-congruent’ adapting stimuli were different pictures of the same individuals displaying the same expression as was present in the morphs. ‘Different-picture/expression-incongruent’ adapting stimuli were pictures of the same individuals displaying different expressions than those present in the morphs. Images were cropped to eliminate the possibility of adaptation to non-face features of the image (i.e.-hair color). Images were novel faces selected from the Karolinska Database of Emotional Faces. We found that the aftereffects on identity perception did not differ significantly between the three different types of adapting stimuli. This suggests that the neural representations activated by novel identities are largely independent of expression, in contrast to the significant identity-dependent component seen in representations of expression that we previously reported. However, unlike learned categorical expressions, novel identities would not activate learned categorical representations of identity. Thus it seems important to determine whether this asymmetric relationship between identity and expression holds true for categorical representations of familiar identities.
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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 | 0.002 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".