Dexamphetamine widens temporal and spatial binding windows in healthy participants
Bibliographic record
Abstract
Background: The pathophysiology of psychosis is complex, but a better understanding of stimulus binding windows (BWs) could help to improve our knowledge base. Previous studies have shown that dopamine release is associated with psychosis and widened BWs. We can probe BW mechanisms using drugs of specific interest to psychosis. Therefore, we were interested in understanding how manipulation of the dopamine or catecholamine systems affect psychosis and BWs. We aimed to investigate the effect of dexamphetamine, as a dopamine-releasing stimulant, on the BWs in a unimodal illusion: the tactile funneling illusion (TFI). Methods: We conducted a randomized, double-blind, counterbalanced placebo-controlled crossover study to investigate funnelling and errors of localization. We administered dexamphetamine (0.45 mg/kg) to 46 participants. We manipulated 5 spatial (5–1 cm) and 3 temporal (0, 500 and 750 ms) conditions in the TFI. Results: We found that dexamphetamine increased funnelling illusion ( p = 0.009) and increased the error of localization in a delay-dependent manner ( p = 0.03). We also found that dexamphetamine significantly increased the error of localization at 500 ms temporal separation and 4 cm spatial separation ( pinteraction = 0.009; p500ms|4cm v. baseline = 0.01). Limitations: Although amphetamine-induced models of psychosis are a useful approach to understanding the physiology of psychosis related to dopamine hyperactivity, dexamphetamine is equally effective at releasing noradrenaline and dopamine, and, therefore, we were unable to tease apart the effects of the 2 systems on BWs in our study. Conclusion: We found that dexamphetamine increases illusory perception on the unimodal TFI in healthy participants, which suggests that dopamine or other catecholamines have a role in increasing tactile spatial and temporal BWs.
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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) | 0.003 | 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".