Face, the final frontier: An ERP study probing processing of human and alien faces in Trekkies and non-Trekkies
Bibliographic record
Abstract
Experience can change the face processing system in infancy (e.g., Kelly et al., 2009) and childhood (e.g., Sangrigoli et al., 2005). This flexibility is less evident in adulthood (Dufour et al., 2004), potentially due to age-related declines in plasticity. Alternatively, reduced flexibility may be due to changes in the environment that decrease the likelihood of massive, individuated experience with novel face types (see Scott & Monesson, 2009). One population that has this type of experience with novel face types, to which they likely had no exposure in early development, are fans of the science-fiction franchise Star Trek (i.e., Trekkies). To determine whether exposure to Star Trek alien faces changes the face-processing system we are comparing self-identified Trekkies' and non-Trekkies' behavioral and brain responses to Star Trek human and alien faces. Thirty-eight non-Trekkies and 5 Trekkies have been tested and recruitment is ongoing. In preliminary analyses, we found no difference in memory for human faces between the groups (t(36) = -.067, p = .947) and significantly greater memory for alien faces in Trekkies than non-Trekkies (t(36) = 3.45, p = .001). Non-Trekkies' memory performance did not significantly relate to how alien they rated alien faces to be, though there appears to be a trend in that direction (r = -.32, p = .073). We expect that Trekkies will show comparable face-specific ERP responses (N170) to human and alien faces and that non-Trekkies will show a clear difference in the N170 response to human vs. alien faces. These findings of increased specialization for alien faces in Trekkies would suggest that there remains flexibility in the adult face processing system. Future research should investigate how much experience with different face types is required to tune the adult face-processing system. Meeting abstract presented at VSS 2014
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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) | 0.003 | 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".