The structure of the serotonin system: A PET imaging study
The human brain atlas of the serotonin (5-HT) system does not conform with commonly used parcellations of neocortex, since the spatial distribution of homogeneous 5-HT receptors and transporter is not aligned with such brain regions. This discrepancy indicates that a neocortical parcellation specifi...
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| Veröffentlicht in: | NeuroImage (Orlando, Fla.) Jg. 205; S. 116240 |
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| Hauptverfasser: | , , , , , , |
| Format: | Journal Article |
| Sprache: | Englisch |
| Veröffentlicht: |
United States
Elsevier Inc
15.01.2020
Elsevier Limited Elsevier |
| Schlagworte: | |
| ISSN: | 1053-8119, 1095-9572, 1095-9572 |
| Online-Zugang: | Volltext |
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| Zusammenfassung: | The human brain atlas of the serotonin (5-HT) system does not conform with commonly used parcellations of neocortex, since the spatial distribution of homogeneous 5-HT receptors and transporter is not aligned with such brain regions. This discrepancy indicates that a neocortical parcellation specific to the 5-HT system is needed. We first outline issues with an existing parcellation of the 5-HT system, and present an alternative parcellation derived from brain MR- and high-resolution PET images of five different 5-HT targets from 210 healthy controls. We then explore how well this new 5-HT parcellation can explain mRNA levels of all 5-HT genes. The parcellation derived here represents a characterization of the 5-HT system which is more stable and explains the underlying 5-HT molecular imaging data better than other atlases, and may hence be more sensitive to capture region-specific changes modulated by 5-HT.
•We evaluate a previous parcellation of the 5-HT system and propose an improvement.•Our new parcellation achieves a higher explained variance and is more stable.•The parcellation includes less regions, so region-based analysis are less penalized.•mRNA data for the HTR1A, HTR1F and HTR2C genes are well captured by the parcellation. |
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| Bibliographie: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 content type line 23 |
| ISSN: | 1053-8119 1095-9572 1095-9572 |
| DOI: | 10.1016/j.neuroimage.2019.116240 |