Distributions of transmitter receptors in the macaque cingulate cortex.

Abstract

The primate cingulate cortex is structurally and functionally complex. Although no studies have investigated the regional densities of multiple neurotransmitter receptor systems, such information would be useful for assessing its functions and disease vulnerabilities. We quantified nine different receptors in five transmitter systems by in vitro autoradiographic mapping of the cingulate cortex of macaque monkeys with the aim to link cytoarchitectonic regions and functional specialization. Receptor mapping substantiated the subdivision of the cingulate cortex into anterior versus posterior regions. In anterior cingulate cortex (ACC) AMPA glutamatergic receptors and GABA(A) inhibitory receptors were present in significantly higher concentrations than the modulatory alpha-adrenergic and muscarinic receptors. These differences were absent in the posterior cingulate cortex (PCC). By contrast, NMDA receptor densities were significantly higher than AMPA receptor densities in PCC, but not in ACC. The midcingulate area 24' shared more features with ACC than PCC. This area was characterized by the highest ratios of NMDA receptors to alpha-adrenergic, muscarinic and 5-HT2 receptors among all cingulate regions. Compared to rostrocaudal divisions, the differences between dorsoventral subdivisions a-c were small in all regions of cingulate cortex, and only muscarinic and alpha-adrenergic receptor densities followed the degree of cytoarchitectonic differentiation. We conclude that multiple receptor mapping reveals a highly differentiated classification of cingulate cortex with a characteristic predominance of fast ionotropic excitatory and inhibitory receptors in ACC, but a strong and varied complement of NMDA and metabotropic receptors in PCC.

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Distributions of transmitter receptors in the macaque cingulate cortex
Ahmet Bozkurt,a,1Karl Zilles,a,bAxel Schleicher,aLars Kamper,aErnesto Sanz Arigita,c
Harry B.M. Uylings,c,dand Rolf Kfttera,e,*
aC. and O. Vogt Brain Research Institute, Heinrich Heine University, D-40225 Du ¨sseldorf, Germany
bInstitute of Medicine, Research Center Ju ¨lich, D-52425 Ju ¨lich, Germany
cNetherlands Institute for Brain Research, Meibergdreef 33, NL-1105 AZ Amsterdam ZO, The Netherlands
dDepartment Anatomy, VU University Medical Center, Amsterdam, The Netherlands
eInstitute of Anatomy II, Heinrich Heine University, D-40225 Du ¨sseldorf, Germany
Received 28 July 2004; revised 18 October 2004; accepted 28 October 2004
Available online 4 January 2005
The primate cingulate cortex is structurally and functionally complex.
Although no studies have investigated the regional densities of multiple
neurotransmitterreceptorsystems,suchinformationwouldbeusefulfor
assessing its functions and disease vulnerabilities. We quantified nine
different receptors in five transmitter systems by in vitro autoradio-
graphic mapping of the cingulate cortex of macaque monkeys with the
aim to link cytoarchitectonic regions and functional specialization.
Receptor mapping substantiated the subdivision of the cingulate cortex
into anterior versus posterior regions. In anterior cingulate cortex
(ACC)AMPAglutamatergicreceptorsandGABAAinhibitoryreceptors
were present in significantly higher concentrations than the modulatory
a-adrenergicandmuscarinicreceptors.Thesedifferenceswereabsentin
the posterior cingulate cortex (PCC). By contrast, NMDA receptor
densities were significantly higher than AMPA receptor densities in
PCC, but not in ACC. The midcingulate area 24V shared more features
withACCthanPCC.Thisareawascharacterizedbythehighestratiosof
NMDA receptors to a-adrenergic, muscarinic and 5-HT2 receptors
among all cingulate regions. Compared to rostrocaudal divisions, the
differences between dorsoventral subdivisions a–c were small in all
regions of cingulate cortex, and only muscarinic and a-adrenergic
receptor densities followed the degree of cytoarchitectonic differentia-
tion. We conclude that multiple receptor mapping reveals a highly
differentiated classification of cingulate cortex with a characteristic
predominance of fast ionotropic excitatory and inhibitory receptors in
ACC, but a strong and varied complement of NMDA and metabotropic
receptors in PCC.
D 2004 Elsevier Inc. All rights reserved.
Keywords: Cerebral cortex; Cytoarchitecture; Mapping; Multivariate
statistics; Neurotransmitter; Primate
Introduction
The cingulate cortex is involved in complex sensory, motor,
cognitive, emotional, and behavioral functions (for reviews, see
Devinsky et al., 1995; Koski and Paus, 2000; Paus et al., 1998;
Vogt and Gabriel, 1993; Vogt et al., 2003). Its cytoarchitectonical
subdivision into anterior (ACC) and posterior cingulate cortex
(PCC) is supported by connectional and functional studies: The
ACC is predominantly connected with the amygdala, with
dorsomedial, midline and intralaminar thalamic nuclei, and with
motor, premotor, dorso-medial, dorso-lateral and orbital prefrontal
cortical areas (Devinsky et al., 1995; Uylings and Van Eden, 1990;
Uylings et al., 2003; Van Hoesen et al., 1993; Vogt and Pandya,
1978; Vogt et al., 1979). Functionally, the ACC has been
associated particularly with the pain system (Craig et al., 1996;
Petrovic et al., 2002), regulation of attention (Botvinick et al.,
1999), emotion (Davidson et al., 2000), vocalization (Ju ¨rgens and
Ploog, 1970), cognition (MacDonald et al., 2000), reward
expectancy (Shidara and Richmond, 2002), and other complex
functions (reviewed by Paus, 2001). By contrast, PCC is
connected mainly with anterior and laterodorsal thalamic nuclei,
visual, temporal association, lateral prefrontal, and parahippocam-
pal cortex (Van Hoesen et al., 1993; Vogt et al., 1979). It appears
preferentially involved in visuospatial cognition (Olson et al.,
1993) and spatial memory (Sutherland and Hoesing, 1993; Vogt
et al., 1992). There is weaker evidence for its association with
sleep (Maquet et al., 1996).
To characterize the architecture and organization of the
cingulate cortex further and to explore possible links between its
structural and functional features, the study of neurotransmitter
receptors is of particular significance. Transmitters and their
receptors mediate excitatory, inhibitory, or modulatory effects
from pre- to postsynaptic neurons and between brain regions. The
topographic and quantitative distribution of transmitter receptors is
largely unknown in the cingulate cortex in contrast to other
regions, such as the prefrontal cortex (Goldman-Rakic et al., 1990;
Lidow et al., 1989a,b), visual cortex (Gebhard et al., 1993; Rakic,
1053-8119/$ - see front matter D 2004 Elsevier Inc. All rights reserved.
doi:10.1016/j.neuroimage.2004.10.040
* Corresponding author. C. und O. Vogt-Institut fqr Hirnforschung,
Heinrich-Heine-Universit7t Dqsseldorf, Moorenstr. 5, D-40225 Dqsseldorf,
Germany. Fax: +49 211 8112095.
E-mail address: rk@hirn.uni-duesseldorf.de (R. Kftter).
1Current address: Department of Plastic and Reconstructive Surgery,
Burns Unit, RWTH, University Hospital Aachen, D-52074 Aachen.
Available online on ScienceDirect (www.sciencedirect.com).
www.elsevier.com/locate/ynimg
NeuroImage 25 (2005) 219–229

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1988; Rosier et al., 1993; Zilles and Clarke, 1997; Zilles et al.,
2002), parietal cortex (Zilles and Palomero-Gallagher, 2001; Zilles
et al., 2002), motor and somatosensory cortex (Geyer et al., 1997,
1998; Ko ¨tter et al., 2001; Schwark et al., 1994; Zilles et al., 1995,
2002), and hippocampus (Kraemer et al., 1995; Martens et al.,
1998; Zilles et al., 1991).
Although regional measurements of receptor densities are not
necessarily directly related to the functional impact of the
respective neurotransmitter system on that particular area, quanti-
tative mapping of multiple transmitter receptors provides valuable
information that can be taken as bground truthQ for comparison
against context-dependent in vivo studies, such as positron
emission tomography (PET) and single photon emission computer
tomography (SPECT).
In this study, we addressed the following questions:
– What are the receptorarchitectural characteristics of cytoarch-
itectonically defined cingulate areas in the macaque monkey?
Does the receptorarchitecture of the cingulate cortex reflect its
rostrocaudal division into ACC and PCC and their distinct
subregions?
What is the receptorarchitectural evidence for a ventrodorsal
differentiation of cingulate areas?
Do the receptorarchitectural features support the functional
differentiation of the cingulate cortex?
–
–
–
To answer these questions, we measured the densities of nine
different receptor (sub-)types in cytoarchitectonically defined
cingulate areas of macaque monkeys using in vitro receptor
autoradiography and ligands for glutamatergic (AMPA, kainate
and NMDA), GABAergic (GABAA), muscarinic (M1and M2),
noradrenergic (a1and a2), and serotoninergic (5-HT2) receptors.
The rationale for selecting these receptors was to provide baseline
indicators of a variety of functional processes including excitatory
and inhibitory processes, as well as modulatory mechanisms
relating to learning, arousal, and behavioral functions. Multivariate
statistical analyses on the basis of receptor distributions showed
clear regional subdivisions of cingulate cortex with a predominance
of ionotropic glutamatergic and GABAergic receptors in ACC and
a strong complement of NMDA and metabotropic receptors in
PCC.
Materials and methods
Preparation of the tissue
The brains of five adult male macaque monkeys (Macaca
fascicularis) were used for this study. All experimental protocols
complied with the German and European laws on the care and
use of laboratory animals. The animals had no history of
neurological diseases or behavioral abnormalities. They were
anesthetized with ketamine hydrochloride (15 mg/kg i.m.)
followed by an intravenous lethal injection of sodium thiopental,
and the entire brain, including the leptomeninges, was immedi-
ately removed from the skull. The arachnoidea was carefully
dissected off, the hemispheres were cut into blocks, and the
unfixed blocks were frozen in isopentane at ?408C without delay
and stored at ?708C in airtight plastic bags until sectioning.
Serial sectioning of the blocks in the frontal (coronal) plane took
place on a cryostat microtome for large sections (Cryo Polycut
CM 3500R, Leica, Nugloch, Germany). The 20-Am-thick sections
were thaw-mounted on gelatine-coated slides and freeze-dried
overnight at 500 Torr and ?208C. They were subsequently
processed for receptor autoradiography as described below.
Adjacent sections were stained with a modified silver method
(Merker, 1983), which yields Nissl-like images for cytoarchitec-
tonic analysis.
Autoradiographic labeling of binding sites
Details of the autoradiographic labeling procedure were
published previously (Zilles and Schleicher, 1995; Zilles et al.,
1988, 1995). Three steps were performed in the following
sequence: (1) the preincubation step removed endogenous ligand
from the tissue. (2) During the main incubation step, binding sites
were labeled with tritiated ligands (total binding). Co-incubation of
the tritiated ligand and a 1000- to 10,000-fold excess of an
appropriate non-labeled ligand (displacer) determined non-specific
binding (control sections). (3) A final rinsing step eliminated
unbound radioactive ligand from the sections.
The following binding sites were labeled with tritiated ligands
(purchased from DuPont, NENk Life Science Products, Boston,
USA): a-Amino-3-hydroxy-5-methylisoxazole-4-propionic acid
(AMPA), kainate, and N-methyl-d-aspartate (NMDA) binding
sites with [3H]AMPA, [3H]kainate, and [3H]MK-801, respectively
(Berger et al., 1994; Ho ¨fner and Wanner, 1996; Johnson et al.,
1989; Watson and Girdlestone, 1995; Zilles et al., 2002); two
different muscarinic cholinergic binding sites with [3H]pirenzepine
(mainly the M1-receptor) (Bonner, 1989; Buckley et al., 1989;
Hammer et al., 1980; Watson and Girdlestone, 1995; Zilles et al.,
2002) or [3H]oxotremorine-M (mainly the M2-receptor) Vilaro ¨ et
al., 1992; Watson and Girdlestone, 1995; Zilles et al., 2002); two
different noradrenergic binding sites with [3H]prazosin (mainly the
a1-adrenoceptor) (Ruffolo et al., 1994a,b; Watson and Girdlestone,
1995; Zilles et al., 1991, 2002) or [3H]UK-14304 (mainly the a2-
adrenoceptor) (Limberger et al., 1995; Trendelenburg et al., 1995,
1996a,b; Watson and Girdlestone, 1995); g-aminobutyric acid
(GABA)Abinding sites with [3H]muscimol (Rabow et al., 1995;
Watson and Girdlestone, 1995; Zilles et al., 2002); serotoninergic
binding sites with [3H]ketanserine (mainly the serotonergic 5-HT2
receptor Leysen et al., 1982; Sleight et al., 1996; Watson and
Girdlestone, 1995; Zilles et al., 2002). Table 1 summarizes
receptors, radioactive ligands, non-labeled displacers, incubation
buffers, and other details of the labeling procedures. The labeled
sections were rinsed in de-ionized water and dried in a stream of
cold air. They were then exposed to [3H]-sensitive film (Hyper-
filmR; Amersham, Braunschweig, Germany) at 48C for 4 weeks
([3H]AMPA, [3H]kainate), 5 weeks ([3H]MK-801, [3H]pirenze-
pine, [3H]muscimol) or 6 weeks ([3H]prazosin, [3H]UK-14304,
[3H]oxotremorine-M, [3H]ketanserine). The films were developed
with Kodak D 19 developer for 5 min and fixed with Kodak Unifix
for 10 min at room temperature. Co-exposed plastic [3H]-standards
(MicroscalesR; Amersham), cut to the same thickness as tissue
sections, enabled the calibration of grey values to concentrations of
radioactivity and, thus, the quantification of binding site densities.
Image analysis
Details of the processing of autoradiographs have also been
published elsewhere (Zilles and Schleicher, 1995; Zilles et al.,
A. Bozkurt et al. / NeuroImage 25 (2005) 219–229
220

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1988, 2002). The autoradiographs were digitized using an image
analysis system (KS400R, Zeiss, Oberkochen, Germany) con-
nected to a CCD camera (SonyR, Tokyo, Japan) equipped with a S-
Orthoplanar 60-mm macro lens (Zeiss) (Zilles et al., 2002). The
images were stored in tiff format with a resolution of 756 ? 512
pixels and 8-bit grey values. The grey value images of the co-
exposed Microscales were used to compute a calibration curve by
non-linear least-squares fitting, which defined the relationship
between the grey values in the autoradiographs and the concen-
trations of radioactivity in the Microscales. This allowed the pixel-
wise conversion of the grey values of each autoradiograph into the
corresponding concentrations of radioactivity. These binding
densities under incubation conditions were subsequently expressed
as fmol/mg values, approximating binding densities at saturation
conditions:
Bmax¼ c ? KDþ L
ðÞ=L ;
where c is the measured concentration of radioactivity, KDis the
equilibrium dissociation constant of ligand-binding kinetics, and L
is the incubation concentration of ligand. Since KDvalues in non-
homogeneous tissue slices cannot be determined with the same
accuracy as in homogenates, approximate values were used (see
Geyer et al., 1998).
The borders of cortical areas were cytoarchitectonically
identified on adjacent cell body stained (Merker, 1983) sections,
and traced in the digitized autoradiographs with a drawing
microscope and a graphics tablet connected to the image analysis
system. For each hemisphere processed, the mean receptor
concentrations in a specific region (in fmol/mg protein, averaged
over all cortical layers) were calculated from measurements in all
sections that contained the respective area (for each ligand at least
10 sections through areas 24 and 23, and at least five sections
through area 24V per hemisphere). Final receptor density values
represent the mean and standard deviation across all analyzed
hemispheres. We obtained measurements of all receptors in all
areas except of GABAAreceptors in midcingulate area 24V.
Multivariate analysis of variance (MANOVA)
Receptor densities were tested for significant differences
between areas per receptor type and between receptor (sub-)types
per area using standard multivariate analysis of variance
(MANOVA; SPSS 10, SPSS Inc., Chicago, IL, USA). Receptor
densities were mean values from each animal for each (sub-)area.
We used Tukey’s method for post hoc tests of pairwise differ-
ences of means to determine if at least one difference was
significantly different from zero. A level of P b 0.05 was
regarded as significant.
Multidimensional scaling (MDS)
We used multidimensional scaling to provide an intuitive
representation of the multidimensional feature space of receptor
patterns in a space of reduced dimensionality (two dimensions
in our examples) (Backhaus et al., 1996; Borg and Groenen,
1997). This multivariate analysis method has been extensively
used in the past to analyze cytoarchitectonics (Schleicher et al.,
2000), structural (Bozkurt et al., 2001, 2002; Kftter et al., 2001;
Young et al., 1995), and functional connectivity (Stephan et al.,
2000), and, recently, receptor binding data (Kftter et al., 2001).
The area vectors of mean receptor density values were trans-
formed into a matrix of Pearson product-moment correlation
coefficients. Since MDS operates on dissimilarity matrices, the
similarities contained in the matrices of correlation coefficients
were transformed into dissimilarities (1-r; Systat 10, SPSS Inc.).
For the multidimensional scaling, we calculated the goodness-
of-fit as Kruskal’s STRESS, fitting a monotonic function of
Table 1
Summary of incubation conditions for receptor autoradiography
[3H]LigandReceptorDisplacer
KDvalue (nM) Pre-incubationMain incubationRinsing
[3H]AMPA
(10 nM)
AMPAQuisqualate
(10 AM)
103 ? 10 min at 48C in
incubation buffer
45 min at 48C in
incubation buffer +
100 mM KSCN
4 ? 4 s at 48C in
incubation buffer +
2 ? 2 s at 48C in
acetone/glutaraldehyde
4 ? 4 s at 48C in
incubation buffer +
2 ? 2 s at 48C in
acetone/glutaraldehyde
2 ? 5 min at 48C in
incubation buffer
[3H]kainate
(8 nM)
KainateKainate
(100 AM)
103 ? 10 min at 48C
in incubation buffer
45 min at 48C in
incubation buffer +
10 mM Ca-acetate
[3H]MK-801
(5 nM)
NMDA MK-801
(100 AM)
815 min at 258C
in incubation buffer
60 min at 258C in
incubation buffer +
30 AM glycine +
50 AM spermidine
60 min at 258C in
incubation buffer
60 min at 258C in
incubation buffer
45 min at 308C in
incubation buffer
90 min at 228C in
incubation buffer
40 min at 48C in
incubation buffer
120 min at 258C in
incubation buffer
[3H]pirenzepine
(1 nM)
[3H]oxotremorine
(0.8 nM)
[3H]prazosin
(0.2 nM)
[3H]UK-14304
(1.4 nM)
[3H]muscimol
(6 nM)
[3H]ketanserine
(0.5 nM)
Muscarinic
M1
Muscarinic
M2
Adrenoceptor
a1
Adrenoceptor
a2
GABAA
Pirenzepine
(10 AM)
Carbachol
(1 AM)
Phentolamine
(10 AM)
Noradrenaline
(100 AM)
GABA
(10 AM)
Mianserine
(10 AM)
9.36 20 min at 258C
in incubation buffer
20 min at 258C
in incubation buffer
30 min at 378C
in incubation buffer
15 min at 228C
in incubation buffer
3 ? 5 min at 48C
in incubation buffer
30 min at 258C
in incubation buffer
2 ? 5 min at 48C in
incubation buffer
2 ? 2 min at 48C in
incubation buffer
2 ? 5 min at 48C in
incubation buffer
5 min at 48C in
incubation buffer
3 ? 3 s at 48C in
incubation buffer
2 ? 10 min at 48C in
incubation buffer
1.74
0.07
1.4
15.1
Serotoninergic
5-HT2
1
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distances onto input dissimilarities. STRESS is the square root
of the normalized squared differences between interpoint
distances in the MDS plot and the smooth distances predicted
from the dissimilarities. Thus, a smaller STRESS value indicates
a better fit. In practical terms, the MDS procedure displays
dissimilarities between objects as distances in space, where in
our case, the dissimilarities refer to the patterns of receptor
distributions among the cingulate cortical areas.
Hierarchical clustering analysis (HCA)
As a complementary approach we produced hierarchical trees
of clusters based on the similarities among the objects under
scrutiny (Systat 10, SPSS Inc.). This procedure forms cluster
hierarchies of areas or receptors by successive amalgamation
according to the increasing dissimilarity of the correlation
coefficients between their receptor patterns or area distributions,
respectively. At any one level of the procedure, each object belongs
exclusively to one cluster. We applied the complete linkage
method, which takes the most distant pair of objects in two
clusters to calculate inter-cluster distance and, thereby, tends to
produce compact clusters. We had previously demonstrated the
usefulness of this method in the analysis of receptor data, as well as
of anatomical connectivity of prefrontal cortical areas (Bozkurt et
al., 2001, 2002; Kftter et al., 2001; Passingham et al., 2002;
Stephan et al., 2001), and in the visualization of functional
connectivity in the cerebral cortex (Kftter and Stephan, 2003;
Stephan et al., 2000).
Results
Anatomical organization of the cingulate cortex
Measurements of binding site densities in the respective areas
required the anatomical identification of the cytoarchitectonic
organization and boundaries of the cingulate areas. Here, we
provide a brief overview of the criteria that we used to identify the
cingulate areas. These were based primarily on the criteria laid out
by Vogt (1993) (see Fig. 1).
The cingulate cortex consists rostrally of agranular areas 25 and
24, while the caudal part comprises granular area 23, cingulopa-
rietal area 31 and retrosplenial areas 29 and 30. As has now been
established in the human (Vogt et al., 2003), there is a distinct
midcingulate area termed 24V, which extends over the middle tier
of the cingulate gyrus.
Area 25 is located ventral to the genu of the corpus callosum
and is characterized by a bilaminar layout and absence of granular
layer IV. Area 24 occupies the rostral third of the cingulate gyrus
and constitutes the main part of the ACC. Agranular area 24 differs
from 25 by showing a clear five-layered structure with layer V
further divided in high- and low-density strata.
Area 24 has three subdivisions (24a–c) with a progressive
laminar differentiation (prominence of layer II, thickness of layer
III, width, cellular composition, and sublayering of layer V) from
ventral to dorsal: 24a in the depth of the callosal sulcus, 24b on the
medial wall of the cingulate gyrus, and 24c on the ventral lip of the
cingulate sulcus. Interposed between areas 24 and 23 is the
midcingulate cortex known as area 24V, which shares cytoarchitec-
tural features with both area 24 and area 23. In agreement with
Vogt (1993), we recognized the same subdivisions as present in
area 24: subareas 24aV, 24bV, and 24cV are therefore positioned
between their counterparts in areas 24 and 23. Matelli et al. (1991)
also recognized the distinct character of this region and introduced
the term b24dQ, which corresponds to our 24cV.
Area 23 occupies the caudal tier of the cingulate gyrus. The
major difference to the rostral cingulate cortex is its granular
character expressed in a well-developed layer IV. At the level of
the splenium of the corpus callosum, retrosplenial areas 29 and 30
are found on the medial bank of the cingulate gyrus and continue
to the rostral tip of the calcarine sulcus. Area 29 is agranular and
consists of two main subdivisions, lateral area 29l (earlier referred
to as 29abc in an attempt to align with rat nomenclature, Vogt,
1993) and medial area 29m, which are distinguished by the degree
of differentiation of their upper layers. Area 30 lies medial to area
29m and, although more developed, it is still dysgranular and
layers III and V are merged. Cinguloparietal area 31 is the caudal
continuation of area 23 and has been described as a proisocortical
area in the transition to the medial parietal isocortex.
Qualitative receptor autoradiography of the cingulate cortex
Projecting the cytoarchitectonically defined borders onto the
autoradiographs, we recognized clear variations in the binding
densities depending on the receptor type, the cytoarchitectonical
area and the cortical layer: binding densities were generally high
for glutamatergic and GABAergic receptors, and lower for most
receptors in other transmitter systems. However, already a
qualitative inspection showed that the concentration of AMPA
receptors was higher in ACC than in PCC (see Figs. 2A–C),
whereas NMDA, M2- and a2-receptors had the reverse distribution
(Figs. 2D–I). Borders between ventrodorsal subareas a, b, and c
were occasionally visible as regional concentration changes (e.g.,
lower AMPA binding in area 24b compared to 24a and 24c, Fig.
2A). Laminar patterns in binding densities were most differentiated
for M2 receptors (Figs. 2G–H) with highest concentrations in the
infragranular layers. By contrast, both AMPA and NMDA
receptors were preferentially present in the supragranular layers
(Figs. 2A–F). The rich laminar information is particularly valuable
for distinguishing adjacent areas. Figs. 2C, F, and I also show
retrosplenial areas 29 and 30. These areas generally had similar
receptorarchitectonic features as PCC.
Examples of original autoradiographs as well as contrast-
enhanced and color-coded images are shown in Fig. 2.
Quantitative analysis of autoradiographic results
The full quantitative results of this study are provided in Fig. 3.
The results of MANOVA for differences between areas as
shown in Fig. 3 was highly significant (Wilks’s ?, F = 2.993,
df = 72, P b 0.001). Significant interareal differences were
found for GABAA receptor densities (F = 3.232, df = 8,
P = 0.007). The striking laminar differences, however, are not
reflected in the aggregate numbers for each area, and Tukey’s
correction for multiple comparisons showed no significant pairs
between areas 24 and 23 (lowest P values: areas 23a/b/c vs.
24c, P = 0.062/0.069/0.069). By contrast, pairwise comparisons
between receptor densities per area revealed significant differ-
ences as listed in Table 2.
In general, binding densities of glutamatergic and GABAer-
gic receptors were higher than those of muscarinic, a-
adrenergic, and serotoninergic receptors. For GABAAreceptors,
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the differences against M1-muscarinic and a1-adrenergic recep-
tors present in ACC were not significant in PCC (compare Fig.
3 and Table 2). Similarly for AMPA receptors, the predom-
inance over M2-muscarinic, a2-adrenergic, and 5-HT2receptors
in ACC (areas 24 and 24V) was not significant in PCC.
Relatively constant in all cingulate areas was the predominance
of kainate and NMDA receptors over muscarinic, a-adrenergic,
and serotoninergic receptors, with highest ratios of NMDA
receptors reached in midcingulate area 24V. We found no
significant differentiation between subareas a, b, and c in any
of these regions.
Hierarchical clustering of correlated (normalized) binding site
densities showed a clear differentiation of the cingulate cortex into
two groups corresponding to a rostrocaudal division (Fig. 4A). The
rostral division consisted again of anterior areas 24a–c, on the one
hand, and midcingulate areas 24aV–cV, on the other hand, whereas
the posterior division comprised areas 23a–c. Similarities between
subareas a, b, and c were very high in each of the three regions
without a consistent sequence of similarity. Multidimensional
scaling fully confirmed this constellation (Fig. 4B). It showed, in
addition, that the receptor patterns in midcingulate area 24V were
between those of areas 24 and 23, although they clearly resembled
more those of anterior cingulate area 24.
Orthogonal correlation of the same binding data to determine
the similarities between receptor (sub-)types (Figs. 4C, D)
showed the receptors that had similar distributions across
cingulate areas. Hierarchical clustering analysis revealed two
general groups: GABAA, AMPA and kainate had similar
distribution patterns across cingulate areas (Fig. 4C); as shown
in Fig. 3, their concentrations were high in the rostral and low in
the caudal division. These fast excitatory and inhibitory receptors
were well separated from the modulatory set of receptors, which
were comparatively scarce in the rostral and equally or even
more highly concentrated in the caudal division (see also
examples in Fig. 2). In the first group, the distribution of
GABAAand AMPA receptors was clearly more similar than that
of kainate receptors. In the second group, NMDA-, M2-, and
M1-muscarinic, and a2-adrenergic receptors formed a core,
which was accompanied by the more dissimilar 5-HT2-serotoni-
nergic and a1-adrenergic binding sites. Again, multidimensional
scaling analysis confirmed these arrangements (Fig. 4D).
Comparison between receptorarchitecture and
ventrodorsal differentiation
Differences in receptor distribution between ventrodorsal
subareas a, b, and c within the cingulate areas 24, 24V, and 23
were subtle compared to interareal differences (Figs. 4A–B).
Correspondences with a ventrodorsal gradient were observed only
as increasing concentrations of muscarinic and a-adrenergic
receptor densities (see Fig. 3, and examples in Figs. 2G–I).
Comparison between receptorarchitecture and
laminar differentiation
The laminar distribution patterns were not quantitatively
evaluated, but they clearly differed between the receptor types.
For example, glutamatergic AMPA and NMDA receptors had
higher receptor densities in supragranular (outer) layers of areas 24
and 24V a–c than in infragranular (inner) layers (Figs. 2A, B, D, and
E), whereas the muscarinic M2receptor showed the reverse pattern
(Figs. 2G, H). Area 23 of the PCC showed a more complicated
pattern due to the presence of granular layer IV: concentrations in
this layer were lowest both for M2and AMPA receptors (Figs. 2C,
I), but in between supra- and infragranular layers for NMDA
receptors (Fig. 2F).
Discussion
Summary of main results
Receptor mapping provided a highly differentiated picture of
the architecture of the primate cingulate cortex. Qualitatively,
we observed complex regional and laminar patterns, which
reflected the cytoarchitectural divisions of the cingulate cortex
into anterior, middle, and posterior areas with ventrodorsal
differentiations.
Fig. 1. Scheme of cingulate cortical areas on the medial surface of the macaque brain based on the parcellation of Vogt (1993).
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Multivariate analyses of receptor distributions substantiated the
cytoarchitectural and functional subdivision of the cingulate cortex
into anterior versus posterior regions. In ACC, AMPA glutama-
tergic receptors and GABAAinhibitory receptors were present in
significantly higher concentrations than the modulatory a-adrener-
gic and muscarinic receptors. These differences were absent in
PCC. By contrast, NMDA receptor densities were significantly
higher than AMPA receptor densities in PCC, but not in ACC. The
midcingulate area 24V shared more features with ACC than PCC.
This area was characterized by the highest ratios of NMDA
receptors to a-adrenergic, muscarinic, and 5-HT2receptors among
all cingulate regions.
Compared to rostrocaudal divisions, the differences between
dorsoventral subdivisions a–c were small in all regions of cingulate
cortex, and only muscarinic and a-adrenergic receptor densities
followed the degree of cytoarchitectonic differentiation.
Comparison with other autoradiography studies
5-HT receptors
The serotoninergic receptors of the human cingulate cortex were
studied by Pazos et al. (1987) using [3H]ketanserine. They found
higher densities in layers I, III, and Vof Brodmann’s area 23 than in
the corresponding layers of area 24. This is in agreement with our
observations, since we found decreasing densities of binding sites
from posterior area 23 over intermediate area 24V to anterior area 24.
Muscarinic receptors
Cortes et al. (1987) compared the muscarinic receptor distribu-
tion in Brodmann’s areas 24 and 23 using [3H]N-methylscopol-
amine ([3H]NMS) in combination with carbachol to demonstrate
M1-receptors and with pirenzepine to demonstrate M2-receptors in
the human cingulate cortex. For M2-receptors, they observed that
Fig. 2. Contrast-enhanced and color-coded autoradiographs showing distribution patterns of AMPA (A–C), NMDA (D–F), and M2muscarinic (G–I) binding
sites in coronal sections of the anterior (area 24: A, D, G), middle (area 24V: B, E, H), and posterior (area 23: C, F, I) cingulate cortex. Orientation of all images
is indicated below H. The color scales refer to receptor densities expressed as fmol/mg protein. White lines indicate borders between cytoarchitecturally and
autoradiographically recognized (sub-)areas of cingulate cortex. Insets in C, F, and I show original images of autoradiographs before contrast enhancement and
color coding.
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layers III and Vof posterior parts of area 24 showed lower densities
than their counterparts in area 23. In agreement with Cortes et al.
(1987), we found an increasing gradient from anterior to posterior
regions with higher densities of M2-receptors in caudal cingulate
area 23 than in intermediate area 24V and rostral area 24 (see, for
example, Figs. 2G–I). Their data for the M1-receptor pattern in the
human support our data because anterior and posterior parts of area
24 showed lower densities of M1-receptors than the corresponding
layers of area 23.
a-Adrenoceptors
We are not aware of any other detailed autoradiographic study
describing the distribution of a-adrenoceptors in the cingulate
cortex.
Glutamate receptors
In the macaque monkey, Young et al. (1990) examined
quisqualate and NMDA receptors in area 24 by comparing
unspecified binnerQ and bouterQ layers. Comparing these two
Fig. 3. Receptor binding sites (ordinate: densities in fmol/mg protein; mean F SD) in cingulate sub-areas arranged from rostral to caudal (abscissa: from left to
right). (A) Glutamatergic receptors, (B) muscarinic receptors, (C) noradrenergic receptors, (D) serotoninergic and GABA-ergic receptors.
Table 2
Statistical significance analyses of receptor densities
24a24b24c 24aV
24bV
24cV
23a23b 23c
GABAAvs. 5-HT2
GABAAvs. M1
GABAAvs. M2
GABAAvs. a1
GABAAvs. a2
AMPA vs. 5-HT2
AMPA vs. M2
AMPA vs. a1
AMPA vs. a2
AMPA vs. NMDA
Kainate vs. 5-HT2
Kainate vs. M2
Kainate vs. a1
Kainate vs. a2
NMDA vs. 5-HT2
NMDA vs. M1
NMDA vs. M2
NMDA vs. a1
NMDA vs. a2
0.000
0.001
0.000
0.000
0.000
0.012
0.006
ns
0.016
ns
0.023
0.013
ns
0.031
0.000
0.027
0.000
0.002
0.000
0.000
0.000
0.000
0.000
0.000
0.010
0.008
ns
0.024
ns
0.001
0.001
0.009
0.002
0.000
0.006
0.000
0.000
0.000
0.000
0.001
0.000
0.000
0.000
0.014
0.007
ns
0.024
ns
0.010
0.005
ns
0.017
0.000
0.035
0.000
0.005
0.001
–
–
–
–
–
0.008
0.004
0.027
0.009
ns
0.007
0.004
0.023
0.008
0.000
0.000
0.000
0.000
0.000
–
–
–
–
–
0.005
0.007
ns
0.015
0.015
0.000
0.000
0.005
0.001
0.000
0.000
0.000
0.000
0.000
–
–
–
–
–
0.004
0.004
ns
0.009
ns
0.010
0.010
ns
0.020
0.000
0.000
0.000
0.000
0.000
0.004
ns
0.023
ns
0.020
ns
ns
ns
ns
0.011
0.008
0.045
ns
0.039
0.000
0.001
0.000
0.020
0.000
0.002
ns
0.027
ns
0.013
ns
ns
ns
ns
0.013
0.002
0.025
ns
0.012
0.000
0.004
0.000
0.018
0.000
0.004
ns
ns
ns
0.020
ns
ns
ns
ns
0.021
0.004
ns
ns
0.020
0.000
0.010
0.000
ns
0.000
Significant differences of receptor densities in a given cingulate sub-area evaluated by MANOVA with post hoc Tukey correction for multiple comparisons.
– = not evaluated; ns = not significant.
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glutamate receptor subtypes, they found higher densities of
NMDA receptors in the outer layers and higher densities of
quisqualate in the inner layers of cingulate area 24. We extend
this observation for the NMDA receptor to the entire cingulate
gyrus (see Figs. 2D–F). The results for quisqualate do not match
our observations for AMPA receptors, but quisqualate has a lower
specificity, binding also to metabotropic glutamate receptors. In
the human brain, Jansen et al. (1989) examined glutamate
receptor subtypes in the ACC without specification of particular
areas. They observed higher densities of NMDA and AMPA
receptors in layers 1–3 than in layers 5–6 and layer 4, whereas
they observed higher densities of kainate receptors in layers 5–6
than in layers 1–3 and layer 4. This laminar distribution pattern in
the human is in agreement with our observations in the macaque
monkey (Figs. 2A–F).
Implications for the functional organization of primate
cingulate cortex
The current investigation adds new criteria to the distinction
between anterior, middle, and posterior cingulate areas. On the
basis of the similarity of receptor endowment, midcingulate area
24V clearly belongs to ACC. This is in agreement with the
functional differentiation of ACC described by Devinsky et al.
(1995) in humans, where ACC constitutes the banterior executive
regionQ subdivided into bcomponentsQ for affect (human cingulate
areas 24, 25 and 33) and cognition (areas 24V and 32). The most
characteristic feature found in area 24V is the extremely high ratio
of NMDA receptors to muscarinic, a-adrenergic, and 5-HT2-
serotoninergic receptors (Table 2). Muscarinic, a-adrenergic, and
5-HT2-serotoninergic receptor densities are even lower in the
mesial premotor areas (Zilles et al., 1995). This is interesting in
the context of area 24cV, which overlaps with the cingulate motor
region. As visible in Figs. 2B and E and in a previous study of
the motor cortex (Geyer et al., 1998, their Fig. 8C), 24cV also
contains much higher densities both of AMPA and NMDA
receptors in the infragranular layers than the supplementary motor
area F6. Although we did not investigate the distribution of
dopaminergic receptors these results emphasize the close struc-
ture–function relationships of these distinct motor areas and are
compatible with the idea that the ACC is engaged in the willed
control of behavior, playing a role in the transformation of
information flow from the lateral prefrontal cortex to various
motor channels (Paus, 2001).
Fig. 4. Characteristic patterns of receptor densities in cingulate cortex explored by hierarchical clustering (A, C) and multidimensional scaling (B, D). The
similarities between areas are shown in A and B, the similarities between receptors calculated from the same data are given in C and D (for details, see
Materials and methods). The two methods are independent and provide complementary information beyond simple correlations: hierarchical clustering
allocates each item to exactly one group emphasizing the strongest family relationships, whereas multidimensional scaling can simultaneously display multiple
relationships. STRESS is a measure of the goodness-of-fit of the final configuration with smaller values indicating a better fit. RSQ is the squared correlation
between the predicted and the obtained distances in the configuration.
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We add further specifics to the regional distribution patterns of
different receptor classes found in ACC and PCC, respectively.
ACC is strongly dominated by the fast excitatory and inhibitory
receptors that are activated by the ionotropic glutamatergic
agonists AMPA and kainate, and the GABAA-ergic agonist
muscimol. Thus, we would expect that ACC responds to its
glutamatergic (mainly highly processed frontal cortical, midline
thalamic, and amydalar) inputs very rapidly, and that a strong
activation is balanced by fast intrinsic GABA-ergic inhibition.
PCC has very different receptor characteristics. Here, fast
excitatory and inhibitory receptors are balanced by high concen-
trations of metabotropic glutamatergic NMDA and also noradre-
nergic a1and muscarinic M2-receptors, indicating an important
role of modulatory mechanisms. Note that this relative increase of
modulatory receptor densities does not mean that excitation and
inhibition have no role to play in PCC, but that the latter are
strongly modulated by other mechanisms that are less represented
in ACC. This may concern particularly cortical associative
functions since both AMPA and NMDA receptors predominate
in the supragranular layers (Figs. 2C and F).
The distinct receptor characteristics of ACC and PCC may
relate to the different effects of REM sleep on the two regions
(Maquet et al., 1996). The strong activation of ACC in functional
imaging studies particularly during demanding cognitive and
motivational tasks may be explained by the predominance of fast
glutamatergic receptors in this region combined with the strong
convergence of axonal projections from many areas (Kftter and
Stephan, 2003). In contrast, the modulation of activity in PCC is
generally more subtle and may relate to a complex interplay of
several modulatory processes. In particular, cholinergic receptors
in PCC have been related to the formation of spatial memory
(Sutherland and Hoesing, 1993; Vogt et al., 1992). The distribution
of dopamine receptors, although not investigated in this study, may
also be interesting in this context because of their supposed role in
reinforcement learning and the prediction of reward.
Further work will aim particularly to identify the specific
laminar microcircuits that are influenced by excitatory, inhibitory,
and modulatory receptors to define their role in the various
functions attributed to the subdivisions of the cingulate cortex.
Acknowledgments
A.B. is indebted to the German Merit Foundation
(bStudienstiftung des Deutschen VolkesQ, especially Mrs. Kohrs)
for their support. The authors thank Dr. Nicola Palomero-
Gallagher, Renate Dohm, Marion Mosch and Moritz Kindler for
methodological support, and Mrs. Opfermann for redrawing Fig. 1.
This study was supported by the DFG (Graduiertenkolleg 320) AG
Kftter/Zilles, and by the Human Brain Project/Neuroinformatics
research funded by the National Institute of Biomedical Imaging
and Bioengineering, the National Institute of Neurological Dis-
orders and Stroke, and the National Institute of Mental Health
(K.Z.).
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