Event-related brain potentials reveal differences in emotional processing in alexithymia
Bibliographic record
Abstract
The inability to recognise and describe emotions in the self is known as Alexithymia. In the present study we used event-related potentials (ERPs) to examine the locus of processing emotional differences in alexithymia. We tested men, both those scoring high (score > 61) and controls who scored low (score < 51) on the Toronto Alexithymia Scale-20 on an emotional face discrimination task. We assessed three ERP components: P1 (an index of early perceptual processing), N170 (an index of early facial processing) and P3 (an index of late attentional suppression). While controls showed a stronger P3 effect for angry faces relative to happy and neutral faces, Alexithymic men showed no significant differences in P3 across emotions. Alexithymic men showed delayed P1 and N170 amplitudes compared to controls. These results suggest that the locus of processing differences between alexithymic men and controls occur both early in perceptual processing and later in conscious processing.
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 | 0.001 | 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".