The auditory-visual integration of anger is impaired in alcoholism: an event-related potentials study
Bibliographic record
Abstract
Objectives: Chronic alcoholism leads to impaired visual and auditory processing of emotions, but the cross-modal (auditory-visual) processing of emotional stimuli has not yet been explored. Our objectives were to describe the electrophysiological correlates of unimodal (visual and auditory) impairments in emotion processing in people suffering from alcoholism, to determine whether this deficit is general or emotionspecific, and to explore potential deterioration in the specific cross-modal integration processes in alcoholism. Methods: We used an emotion-detection task, with recording of event-related potentials (ERPs), in which 15 patients suffering from alcoholism and 15 matched healthy control subjects were asked to detect the emotion (angry, happy or neutral) displayed by auditory, visual or auditory-visual stimuli. Behavioural performance and ERP data recorded between June 2005 and April 2006 were analyzed. Results: ERPs demonstrated that the deficit in alcoholism originates earlier in the cognitive stream than has previously been described (mainly P300), namely, at the level of specific face (N170) and voice (N2) perceptive processing. Moreover, while patients with alcoholism did not show impaired processing of happy and neutral audio-visual stimuli, they did have a specific impairment in the cross-modal processing of anger. A source location analysis was used to confirm and illustrate the results. Conclusion: These results suggest that the specific deficit that people with alcoholism demonstrate in processing anger stimuli, widely described in clinical situations but not clearly identified in earlier studies (using unimodal stimuli), is particularly obvious during cross-modal processing, which is more common than unimodal processing in everyday life.
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".