Multisensory integration of emotionally valenced olfactory–visual information in patients with schizophrenia and healthy controls
Bibliographic record
Abstract
BACKGROUND: Patients with schizophrenia frequently have deficits in social cognition, and difficulties in the discrimination of emotional facial expressions have been discussed as an important contributing factor. We investigated whether this impairment is aggravated by difficulties relating the observed facial expression to contextual information, as is often provided by emotionally valenced crossmodal stimulation. METHODS: We investigated the effects of odorant primes on the accuracy and speed of emotional face recognition. Healthy controls and patients with schizophrenia were exposed to 2-second odorant stimuli: vanillin (pleasant), ambient air (neutral) and hydrogen sulfide (unpleasant). The odours were followed by an emotional face recognition task, in which participants determined if a face showed happiness, disgust or neutral affect. RESULTS: Controls showed improved performance in the categorization of disgusted faces after all types of odour stimulation irrespective of the emotional valence. However, in controls, the response time for happy faces was slower after presentation of any odour. Schizophrenia patients showed an attenuated effect of olfactory priming on disgust recognition, which resulted in the increased performance differences between the groups. This effect was particularly strong for the unpleasant odour. LIMITATIONS: The study design did not allow us to fully differentiate between the effects of perceived odour intensity and valence. A possible contribution of cognitive deficits on the observed effects should be investigated in future studies. CONCLUSION: Our results provide novel evidence for a special connection between the presentation of odorant cues and the accuracy of recognition of disgusted faces in healthy controls. This recognition advantage is disturbed in patients with schizophrenia and appears to contribute to the observed deficit in emotional face recognition.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".