PsiConnect: A Multimodal Neuroimaging Study of Psilocybin-Induced Changes in Brain and Behaviour
Bibliographic record
Abstract
ABSTRACT PsiConnect is a large-scale neuroimaging study designed to investigate the neural and subjective effects of psilocybin using multimodal neuroimaging. It combines functional, structural, and diffusion-weighted MRI with EEG to examine brain activity in 62 participants before and after a 19 mg dose of psilocybin. The design includes resting-state scans and three naturalistic conditions: guided meditation, music listening, and movie watching. Half of the cohort underwent an 8-week meditation training program, enabling the exploration of interactions among meditation, psilocybin, and brain function. The fMRI data was obtained through multi-echo fMRI, which enhances the signal-to-noise ratio and reduces susceptibility artifacts, thereby improving the reliability of the analyses. A comprehensive battery of behavioural and self-report measures captured both acute and longitudinal cognitive and subjective effects, with follow-ups extending to one year post-administration. The large sample size, multimodal neuroimaging, diversity of contexts, and longitudinal behavioural follow-ups enable the study of psilocybin-induced changes in brain and behaviour with an unprecedented level of detail and reliability. Furthermore, the data is curated according to open science principles to ensure accessibility and interoperability with established neuroimaging processing pipelines. These factors make PsiConnect a valuable and highly reusable resource for researchers in cognitive and computational neuroscience.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".