A neuroreceptor-based modeling framework using cortical density maps of 19 neuroreceptors and transporters from PET scans can reconstruct BOLD-derived brain activity. The framework identified two neuroreceptor modules: one linked to higher-order associative networks and another to somatomotor and visual networks. Applied to independent datasets, it recovered the binding profiles of LSD and Modafinil, consistent with known pharmacology. It also uncovered associations between neuroreceptors and altered brain activity in neuropsychiatric disorders. The findings suggest the framework can elucidate neuromodulatory mechanisms and advance understanding of brain function across diverse states and conditions.
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.