Journal of The Royal Society Interface
October 29, 2014
Giovanni Petri, Paul Expert, Federico Turkheimer et al.
689 citations
Functional brain networks can be studied through homological cycles—topological objects that capture mesoscopic structure in weighted correlation networks. A new method, homological scaffolds, compactly represents these cycles and makes them amenable to standard network analysis. Applied to resting-state fMRI data from 15 healthy volunteers given placebo or psilocybin, the homological structure of brain activity changed dramatically after psilocybin, producing many transient, low-stability cycles and a few persistent ones absent under placebo.
NeuroImage
April 4, 2019
Ottavia Dipasquale, Pierluigi Selvaggi, Mattia Veronese et al.
79 citations
A double-blind, placebo-controlled study combined resting-state fMRI with a molecular atlas of serotonin receptors to examine how MDMA alters functional connectivity. Using the REACT method, the researchers found that MDMA-induced connectivity changes were specifically linked to brain regions rich in the serotonin transporter (5-HTT) and the 5-HT1A receptor, the drug's primary targets. Changes in 5-HT1A-enriched maps correlated with MDMA blood levels, while changes in 5-HT2A-enriched maps correlated with spiritual experiences reported by participants. The approach shows that MDMA's effects on brain connectivity can be explained by the distribution of its serotonergic targets, offering a new way to characterize psychoactive compounds.
bioRxiv : the preprint server for biology
June 12, 2026
Timothy Lawn, Johan Nakuci, Steve Cr Williams et al.
Spatial overlap among brain receptor maps derived from PET imaging can distort analyses that model multiple receptors together. Using test-retest fMRI data, the authors show that as more receptors are included in a multivariate model, the reliability of the resulting functional connectivity networks decreases, and this degradation is driven by collinearity among the receptor maps. A univariate approach, modeling each receptor independently, produces more reliable networks and, in a study comparing LSD to placebo, better captured the known role of the 5HT-2A receptor. Spatial collinearity is a fundamental constraint on multivariate molecular-enriched network estimation, and univariate modeling is recommended as a more robust default.