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@INPROCEEDINGS{Savli:150643,
author = {Savli, Markus and Ding, Yu-Shin and Neumeister, Alexander
and Bauer, Andreas and Häusler, Daniela and Wadsak,
Wolfgang and Mitterhauser, Markus and Lanzenberger, Rupert},
title = {{H}ierarchical organization of the serotonergic system: {A}
multi-tracer {PET} study on healthy subjects},
reportid = {FZJ-2014-00690},
year = {2013},
abstract = {Introduction The serotonergic system is a highly diverse
composition of various pre- and postsynaptic receptor
subtypes and the serotonin transporter. Previous in vivo and
postmortem studies revealed a rather distinct distribution
pattern of these proteins throughout the human brain [1-2].
The cerebral cortex has often been subdivided into numerous
areas characterized by structural, functional and
cytoarchitectonic features [3] while protein-based
organizations schemes are lacking. In the current study we
propose a new organizational model of the brain based on
protein distributions of the serotonergic system including
the major inhibitory (5-HT1A and 5-HT1B), the major
excitatory (5-HT2A) receptors and the transporter (SERT) of
healthy subjects. Methods Dynamic PET scans were performed
in 95 healthy subjects (age=28.0±6.9 years; $59\%$ males)
divided into 4 groups using the selective radioligands
[carbonyl-11C]WAY100635 for 5-HT1A, [18F]altanserin for
5-HT2A, [11C]P943 for 5-HT1B and [11C]DASB for SERT. After
motion correction and spatial normalization in SPM8 dynamic
PET scans were quantified from radioactivity concentrations
by a multi-linear reference tissue model (MRTM2; 5HT1A,
5-HT1B, SERT; BPND) and a bolus/infusion approach (5HT2A;
BPP) in PMOD 3.3. A standard template in MNI stereotactic
space served for ROI delineation. The ROI template based on
the macro-anatomical criteria according to AAL (automated
anatomical labeling) including 52 regions [4]. Similarities
between receptor distribution patterns were analyzed by
means of a hierarchical cluster analysis using Euclidean
distances in combination with the Ward-linkage method as
implemented in R2.15.0. All values were z-transformed across
areas prior to analysis in order to establish equal weight
between the protein bindings. Results Receptor densities as
represented by binding potentials were computed for all
ROIs. Hierarchical cluster analysis of group-average BP
values revealed two main protein-distinct clusters. The
first exclusively comprised subcortical areas such as the
raphe nuclei, thalamus, pallidum, caudate nucleus, putamen,
midbrain, and striatum, whereas in the second the remaining
cortical areas were aggregated. Of note is the strikingly
pronounced dissimilarity between these two clusters given by
the high distance. In the cortical cluster occipital,
parietal and frontal ROIs displayed closer similarities than
temporal ROIs. Basal ganglia ROIs showed shorter Euclidean
distance than raphe nuclei in the subcortical cluster. XIth
International Conference on Quantification of Brain Function
with PET, May 20-23, 2013, Shanghai, China Discussion We
quantified in vivo PET data of 4 key proteins of the
serotonergic system and subsequently used a data-driven
approach to identify brain regions of similar features
within the serotonergic system. Interestingly, spatially
distant ROIs such as the subcortical areas were identified
with close molecular similarity in contrast to cortical ROIs
as given by the large Euclidean distance between these two
clusters. The two clusters found were in accordance with the
familiar classification of cortical und subcortical ROIs.
Furthermore, temporal ROIs but also some frontal ROIs (ACC,
Insula) exert a similar role as opposed to the remaining
lobes. This result reflects an explicit hierarchical
organization of the serotonergic system and emphasizes
functions and interactions of the binding proteins beyond
topologies.},
month = {May},
date = {2013-05-20},
organization = {XIth International Conference on
Quantification of Brain Function with
PET, Shanghai (China), 20 May 2013 - 23
May 2013},
cin = {INM-2},
cid = {I:(DE-Juel1)INM-2-20090406},
pnm = {333 - Pathophysiological Mechanisms of Neurological and
Psychiatric Diseases (POF2-333)},
pid = {G:(DE-HGF)POF2-333},
typ = {PUB:(DE-HGF)1},
url = {https://juser.fz-juelich.de/record/150643},
}