Psilocybin exerts distinct effects on resting state networks associated with serotonin and dopamine in mice
Year: 2020
Type: article
Abstract: Hallucinogenic agents have been proposed as potent antidepressants; this includes the serotonin (5-HT) receptor 2A agonist psilocybin. In human subjects, psilocybin alters functional connectivity (FC) within the default-mode network (DMN), a constellation of inter-connected regions that displays altered FC in depressive disorders. In this study, we investigated the effects of psilocybin on FC across the entire brain with a view to investigate underlying mechanisms. Psilocybin effects were investigated in lightly-anaesthetized mice using resting-state fMRI. Dual-regression analysis identified reduced FC within the ventral striatum in psilocybin- relative to vehicle-treated mice. Refinement of the analysis using spatial references derived from both gene expression maps and viral tracer projection fields revealed two distinct effects of psilocybin: it increased FC between 5-HT-associated networks and cortical areas, including elements of the murine DMN, thalamus, and midbrain; it decreased FC within dopamine (DA)-associated striatal networks. These results suggest that interactions between 5-HT- and DA-regulated neural networks contribute to the neural and therefore psychological effects of psilocybin. Furthermore, they highlight how information on molecular expression patterns and structural connectivity can assist in the interpretation of pharmaco-fMRI findings.
Source: NeuroImage
Language: English
Subfield: Clinical Psychology
Field: Psychology
Domain: Social Sciences
Open Access status: gold
Estimated APC paid: $3,000
Awards: The proinflammatory cytokine hypothesis of depression: An integrative study of mouse models to investigate cytokine-astrocyte mediation of the effects of psychosocial stress on emotional-cognitive dysfunction, G544591541, G8105150848, fMRI in mice: enhancing the specificity of fMRI procedures and application to models of chronic pain, G8690818240
OpenAlex ID: W3093454394
