A new method to model neuroimaging data could help to predict potential treatment outcomes for patients with mental health disorders. The study by researchers from Pompeu Fabra University, Spain, and the University of Oxford looked specifically at people with mental disorders attributable to diseases of the nervous system such as depression and addiction. The team involved used neuroimaging data of healthy participants who had been given LSD (lysergic acid diethylamide) and placebo treatments to prove the concept of the new computer model.
An advanced computer model of human neuroimaging data that precisely modelled whole-brain dynamics using the actual brain connectivity between regions was used. For the first time, this whole-brain model of neural activity was integrated with the concentrations of the chemical messenger – a serotoninergic neurotransmitter- called 5HT2A, in each brain region. Integrating this information in the model allowed the team to investigate the causal non-linear interactions between neural activity and neurotransmitter concentration. As the concentration of neurotransmitter changes in one or more regions so will the brain dynamics, but crucially in a non-linear way that requires a model to predict.
Professor Gustavo Deco, Pompeu Fabra University, Spain, lead author of the study, explains: “This is potentially a new powerful method which could be used to make rational drug discovery and to better design, test and predict the effects of new drugs.”
Professor Morten Kringelbach, University of Oxford, UK and Aarhus, Denmark, the senior author of the study, says: “Psychedelics hold considerable promise for treating neuropsychiatric diseases such as depression and addiction. However, the underlying brain mechanisms are not currently understood."
- The paper – ‘Whole-brain multimodal neuroimaging model using serotonin receptor maps explains non-linear functional effects of LSD’ by Deco G., Cruzat J., Cabral J., Knudsen G.M., Carhart-Harris R.L., Whybrow P.C., Logothetis N.K. & Kringelbach M.L. was published in the high-impact journal Current Biology.