Abstract
Psychedelics have emerged as promising candidate treatments for various psychiatric conditions, and given their clinical potential, there is a need to identify biomarkers that underlie their effects. Here, we investigate the neural mechanisms of lysergic acid diethylamide (LSD) using regression dynamic causal modelling (rDCM), a novel technique that assesses whole-brain effective connectivity (EC) during resting-state functional magnetic resonance imaging (fMRI). We modelled data from two randomised, placebo-controlled, double-blind, cross-over trials, in which 45 participants were administered 100 μg LSD and placebo in two resting-state fMRI sessions. We compared EC against whole-brain functional connectivity (FC) using classical statistics and machine learning methods. Multivariate analyses of EC parameters revealed predominantly stronger interregional connectivity and reduced self-inhibition under LSD compared to placebo, with the notable exception of weakened interregional connectivity and increased self-inhibition in occipital brain regions as well as subcortical regions. Together, these findings suggests that LSD perturbs the Excitation/Inhibition balance of the brain. Notably, whole-brain EC did not only provide additional mechanistic insight into the effects of LSD on the Excitation/Inhibition balance of the brain, but EC also correlated with global subjective effects of LSD and discriminated experimental conditions in a machine learning-based analysis with high accuracy (91.11%), highlighting the potential of using whole-brain EC to decode or predict subjective effects of LSD in the future.
| Original language | English |
|---|---|
| Journal | Neuropsychopharmacology |
| Volume | 48 |
| Issue number | 8 |
| Pages (from-to) | 1175-1183 |
| Number of pages | 9 |
| ISSN | 0893-133X |
| DOIs | |
| Publication status | Published - 07.2023 |
Funding
We are grateful for support from the Swiss National Science Foundation (trial A: SNF project grant, 320030_1449493 to MEL, trial B: SNF project grant, 320030_170249 to SB and MEL, Doc.Mobility, P1BSP3_200054 to DJH, Ambizione, PZ00P3_167952 to AOD) and the Krembil Foundation (to AOD).
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
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SDG 10 Reduced Inequalities
Research Areas and Centers
- Academic Focus: Center for Brain, Behavior and Metabolism (CBBM)
DFG Research Classification Scheme
- 2.23-04 Cognitive, Systems and Behavioural Neurobiology
- 2.22-09 Pharmacology
- 2.23-09 Biological Psychiatry
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