Cognitive effects of placebo antipsychotics: Investigating their mechanisms using event-related potentials (ERPs) in a cognitive test and a self-referential task
Bibliographic record
Abstract
Abstract Placebos modulate neurocognitive processes. We examined whether a fully deceptive antipsychotic-placebo changes cognition not only by enhancing arousal and attention but also by changing self-representations, namely, by adding that of being under a treatment related to psychosis and by weakening the binding of experience to reality. Drug-naive healthy participants (N = 83) were split into a group (N = 40) who took a pill described as an antipsychotic and a no-pill control group (N = 43). Participants performed a cognitive test (CogTest), that is, a semantic categorization task and a self-referential role judgment task (SRT). Behavioral responses and event-related potentials (ERPs) were recorded. In the CogTest, placebos showed faster response times and higher accuracy than no-pills. This cognitive improvement was associated with more negative occipito-temporal early ERPs (OTEEs), larger central P2s (CentP2s), and larger late positive potentials (LPPs), with the latter correlating with response times. As in the literature, CentP2s were maximal in the SRT, possibly because it maximally stimulates the binding of the stimulus to long-term self-representations. The larger CentP2s and LPPs for placebos than for no-pills in the CogTest were thus tentatively related to the binding of the stimulus with egocentric self-representations, temporarily enriched by the addition of the representation of being on drug. On the contrary, the more negative OTEEs were related to a weaker binding to allocentric ones, preventing a strong binding of experience with reality. The smaller N400s observed for placebos than for no-pills in both tasks were related to greater openness to new experiences.
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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 | 0.002 |
| 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) | 0.002 | 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".