Parcellation of the Human Cerebral Cortex Based on Molecular Targets in the Serotonin System Quantified by Positron Emission Tomography In vivo. (24th October 2018)

• Record Type: Journal Article
• Authors: James, Gregory M; Gryglewski, Gregor; Vanicek, Thomas; Berroterán-Infante, Neydher; Philippe, Cécile; Kautzky, Alexander; Nics, Lukas; Vraka, Chrysoula; Godbersen, Godber M; Unterholzner, Jakob; Sigurdardottir, Helen L; Spies, Marie; Seiger, René; Kranz, Georg S; Hahn, Andreas; Mitterhauser, Markus; Wadsak, Wolfgang; Bauer, Andreas; Hacker, Marcus; Kasper, Siegfried; Lanzenberger, Rupert
• Is Part Of: Cerebral cortex. Volume 29:Number 1(2019)
• Page Start: 372
• Page End: 382
• Publication Date: 2018-10-24
• Subjects: cortex -- cortical reconstruction -- molecular imaging -- parcellation -- PET -- serotonin; Cerebral cortex -- Periodicals; Brain -- Periodicals; 612.825
• DOI: 10.1093/cercor/bhy249
• Languages: English
• ISSNs: 1047-3211

Abstract

Abstract: Parcellation of distinct areas in the cerebral cortex has a long history in neuroscience and is of great value for the study of brain function, specialization, and alterations in neuropsychiatric disorders. Analysis of cytoarchitectonical features has revealed their close association with molecular profiles based on protein density. This provides a rationale for the use of in vivo molecular imaging data for parcellation of the cortex with the advantage of whole-brain coverage. In the current work, parcellation was based on expression of key players of the serotonin neurotransmitter system. Positron emission tomography was carried out for the quantification of serotonin 1A (5-HT1A, n = 30) and 5-HT2A receptors ( n = 22), the serotonin-degrading enzyme monoamine oxidase A (MAO-A, n = 32) and the serotonin transporter (5-HTT, n = 24) in healthy participants. Cortical protein distribution maps were obtained using surface-based quantification. Based on k-means clustering, silhouette criterion and bootstrapping, five distinct clusters were identified as the optimal solution. The defined clusters proved of high explanatory value for the effects of psychotropic drugs acting on the serotonin system, such as antidepressants and psychedelics. Therefore, the proposed method constitutes a sensible approach towards integration of multimodal imaging data for research and development in neuropharmacology and psychiatry.