LSD microdosing attenuates the impact of temporal priors in time perception
Bibliographic record
Abstract
Abstract Recent theoretical work embedded within the predictive processing framework has proposed that the neurocognitive and therapeutic effects of psychedelics are driven by the modulation of priors (Carhart-Harris & Friston, 2019). We conducted pre-registered re-analyses of previous research (Yanakieva et al., 2019) to examine whether microdoses of lysergic acid diethylamide (LSD) alleviate the temporal reproduction bias introduced by priors, as predicted by this theoretical framework. In a between-groups design, participants were randomly assigned to one of four groups receiving LSD (5, 10, or 20 μg) or placebo (0 μg) and completed a visual temporal reproduction task spanning subsecond to suprasecond intervals (0.8 to 4 sec). Using mixed-effects modelling, we evaluated the impact of the treatment group, and of the overall history of stimulus intervals ( global priors) and the local stimulus history ( local priors), weighted by their respective precision weights (inverse of variance), on temporal reproduction. Our principal finding was that the precision-weighted local priors and their precision weights reduced the under-reproduction bias observed under LSD in the original research. Furthermore, controlling for the precision- weighted local prior eliminated the reduced temporal reproduction bias under LSD, indicating that LSD microdosing mitigated the temporal under-reproduction by reducing the relative weighting of priors. These results suggest that LSD microdosing alters human time perception by decreasing the influence of local temporal priors.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.001 |
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".