The role of the cannabinoid receptor in adolescents′ processing of facial expressions
Bibliographic record
Abstract
The processing of emotional faces is an important prerequisite for adequate social interactions in daily life, and might thus specifically be altered in adolescence, a period marked by significant changes in social emotional processing. Previous research has shown that the cannabinoid receptor CB1R is associated with longer gaze duration and increased brain responses in the striatum to happy faces in adults, yet, for adolescents, it is not clear whether an association between CBR1 and face processing exists. In the present study we investigated genetic effects of the two CB1R polymorphisms, rs1049353 and rs806377, on the processing of emotional faces in healthy adolescents. They participated in functional magnetic resonance imaging during a Faces Task, watching blocks of video clips with angry and neutral facial expressions, and completed a Morphed Faces Task in the laboratory where they looked at different facial expressions that switched from anger to fear or sadness or from happiness to fear or sadness, and labelled them according to these four emotional expressions. A-allele versus GG-carriers in rs1049353 displayed earlier recognition of facial expressions changing from anger to sadness or fear, but not for expressions changing from happiness to sadness or fear, and higher brain responses to angry, but not neutral, faces in the amygdala and insula. For rs806377 no significant effects emerged. This suggests that rs1049353 is involved in the processing of negative facial expressions with relation to anger in adolescence. These findings add to our understanding of social emotion-related mechanisms in this life period.
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) | 0.001 | 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".