Comparing mouse and human cingulate cortex organization using functional connectivity

Abstract

The subdivisions of the extended cingulate cortex of the human brain are implicated in a number of high-level behaviors and affected by a range of neuropsychiatric disorders. Its anatomy, function, and response to therapeutics are often studied using non-human animals, including the mouse. However, the similarity of human and mouse frontal cortex, including cingulate areas, is still not fully understood. Some accounts emphasize resemblances between mouse cingulate cortex and human cingulate cortex while others emphasize similarities with human granular prefrontal cortex. We use comparative neuroimaging to study the connectivity of the cingulate cortex in the mouse and human, allowing comparisons between mouse ‘gold standard’ tracer and imaging data, and, in addition, comparison between the mouse and the human using comparable imaging data. We find overall similarities in organization of the cingulate between species, including anterior and midcingulate areas and a retrosplenial area. However, human cingulate contains subareas with a more fine-grained organization than is apparent in the mouse and it has connections to prefrontal areas not present in the mouse. Results such as these help formally address between-species brain organization and aim to improve the translation from preclinical to human results.

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Brain Structure and Function (2024) 229:1913–1925
https://doi.org/10.1007/s00429-024-02773-9
ORIGINAL ARTICLE
Comparing mouse andhuman cingulate cortex organization using
functional connectivity
AranT.B.vanHout1· SabrinavanHeukelum1· MatthewF.S.Rushworth2,3· JoanesGrandjean1,4· RogierB.Mars1,2
Received: 6 October 2023 / Accepted: 30 January 2024 / Published online: 13 May 2024
© The Author(s) 2024
Abstract
The subdivisions of the extended cingulate cortex of the human brain are implicated in a number of high-level behaviors and
affected by a range of neuropsychiatric disorders. Its anatomy, function, and response to therapeutics are often studied using
non-human animals, including the mouse. However, the similarity of human and mouse frontal cortex, including cingulate
areas, is still not fully understood. Some accounts emphasize resemblances between mouse cingulate cortex and human cingu-
late cortex while others emphasize similarities with human granular prefrontal cortex. We use comparative neuroimaging to
study the connectivity of the cingulate cortex in the mouse and human, allowing comparisons between mouse ‘gold standard’
tracer and imaging data, and, in addition, comparison between the mouse and the human using comparable imaging data.
We find overall similarities in organization of the cingulate between species, including anterior and midcingulate areas and
a retrosplenial area. However, human cingulate contains subareas with a more fine-grained organization than is apparent in
the mouse and it has connections to prefrontal areas not present in the mouse. Results such as these help formally address
between-species brain organization and aim to improve the translation from preclinical to human results.
Keywords Cingulate cortex· Frontal lobe· Functional connectivity· Mouse· Comparative· Translational neuroscience
Introduction
Much of our knowledge about the human brain is based on
knowledge obtained in other species. While numerous spe-
cies have been used to model the human brain, the mouse
has emerged as the most prominent of these, due to its rapid
life cycle, straightforward husbandry, and amenability
to genetic engineering (Dietrich etal. 2014). The overall
assumption in this work is that the knowledge obtained in
the mouse ‘model species’ is translatable to the human, due
to overall similarities in biological properties of the two spe-
cies. However, the success rate of such translations have
sometimes been disappointing, especially in the case of
neuropsychopharmacology (Hay etal. 2014). This is due,
in part, to assumptions of between-species similarities not
holding (Striedter 2022). As such, it is becoming increas-
ingly apparent that these assumption should be subjected to
explicit empirical validation.
The various divisions of cingulate cortex have repeatedly
been shown to be important in many aspects of emotional
processing, decision making, and cognitive control (Behrens
etal. 2013; Leech and Sharp 2014; Kolling etal. 2016) and
alterations in cingulate morphology (Goodkind etal. 2015;
Opel etal. 2020) and functional connectivity (Marusak etal.
2016) are a common observation across a range of psychiat-
ric disorders. Cingulate cortex is thought to be an evolution-
ary conserved region in mammals. Indeed, an analysis of
common areas across six major mammalian clades suggests
that cingulate cortex is present in all and that it could have
been part of a limited set of neocortical regions present in
early mammals (Kaas 2011). The combination of common
alterations in disease and apparent evolutionary conservation
Joanes Grandjean and Rogier B. Mars shared last authors.
* Rogier B. Mars
Rogier.mars@donders.ru.nl
1 Donders Institute forBrain, Cognition andBehaviour,
Radboud University Nijmegen, Nijmegen, TheNetherlands
2 Wellcome Centre forIntegrative Neuroimaging, Nuffield
Department ofClinical Neurosciences, John Radcliffe
Hospital, University ofOxford, Oxford, UK
3 Department ofExperimental Psychology, University
ofOxford, Oxford, UK
4 Department forMedical Imaging, Radboud University
Medical Center, Nijmegen, TheNetherlands
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1914 Brain Structure and Function (2024) 229:1913–1925
make cingulate cortex an important target for translational
neuroscience research.
However, the similarity of rodent and human cingulate
has been called into question on a number of grounds. First,
it has been argued by some authors that rodent cingulate
cortex has organizational featuressimilar to those of pri-
mate dorsolateral prefrontal cortex or that at leastit per-
formshomologous functions (Brown and Bowman 2002;
Uylings etal. 2003; Carlén, 2017). Second, among research-
ers who reject these claims, there still is some debate about
how rodent cingulate should be subdivided and how its
organization relates to that of the primate (Laubach etal.
2018; van Heukelum etal. 2020). Third, even if cingulate
cortex were found to be fully homologous in mouse and
human it would be embedded within the larger prefrontal
network within the human brain compared to other species
(Schaeffer etal. 2020). These arguments continue to be reas-
sessed with the appearance of new data types that enable
better and more complete comparisons across species.
One way to explore similarities and differences in brain
organization across species is by studying connectivity.
The connections of brain areas constitute a unique ‘finger-
print’ and provide information aboutthe area’s incoming
information and the influence it exerts on other parts of the
brain (Passingham etal. 2002; Mars etal. 2018). We have
previously employed functional connectivity as assessed
using resting state fMRI to compare connectivity across
humans and non-human primates (Mars etal. 2011, 2016)
and humans and mice (Balsters etal. 2020). Cingulate con-
nectivity has been studied using neuroimaging in a number
of studies using both diffusion MRI tractography (Beckmann
etal. 2009; Smith etal. 2018) and functional connectivity
(Margulies etal. 2007; Hutchison etal. 2012; Schaeffer etal.
2020). Even if the species studied have diverged such a long
time ago that assessing homology purely by means of con-
nectivity is likely to be difficult, studying the patterns of con-
nectivity across cingulate cortex is likely to provide insight
in the similarities and differences in cortical organization
(cf. Van Heukelum etal. (2020)). Here, we study mouse
cingulate functional connectivity, assessing it against the
‘gold standard’ of tracer-based structural connectivity, and
compare it with similar data from the human. The goal of the
study is to assess to what extent the general organizational
principles of cingulate organization are comparable across
the two species.
Materials andmethods
Data‑driven analysis ofmouse tracer data
We first performed a data-driven parcellation of the
rodent cingulate cortex based on structural connectivity as
established using tracers following the strategy of Mandino
etal. (2022). This serves as a baseline for the subsequent
analyses using functional MRI data.
We downloaded data from 498 tracer experiments from
the independent tracer-based connectivity dataset of the
Allen Institute (Oh etal. 2014) using a custom interface
(https:// github. com/ neuro ecolo gy/ allen- tracer- downl oad).
In these experiments C57BL/6 male mice received a viral
anterograde tracer injection in various subcortical and corti-
cal sites of the right hemisphere. This viral tracer initiates
the coding of a fluorescent protein which accumulates in the
axons of neurons. Through visualising this fluorescence, a
detailed description of the structural connections between
the site of injection and the rest of the brain can be created.
After downloading these tracer experiments, 2000 seeds
were placed at even intervals along a region of interest span-
ning the left hemisphere anterior cingulate area, infralimbic
area, prelimbic area, and retrosplenial area (hence referred
to as the ‘cingulate ROI’) according to the nomenclature of
the Allen mouse brain reference atlas (Wang etal. 2020).
Where possible, we will use the terminology of Vogt and
Paxinos (2014) for the cingulate and Paxinos and Franklin
(2019) for the rest of the brain when discussing our results.
Subsequently, we extracted the tracerdensity in these
seeds and correlated these with the tracerdensity recorded
in the rest of the brain, thus resulting in a seeds by whole-
brain correlation map. The left hemisphere was selected for
the seed locations to extract axonal projections, as opposed
to cell body-related tracerdensity. This allowed us to gener-
ate connectivity maps based on axonal projection similarity.
Having created the correlation maps, we grouped seed
voxels together as a function of their connectivity profiles
by performing an independent component analysis (ICA) on
the correlations maps using FSL’s melodic (Beckmann and
Smith 2005). An independent component provides a spatial
map of voxels that have similar correlations to the cingu-
late seed voxels. Thus, ICA essentially divides the brain,
including the cingulate cortex itself, into components based
upon their connections with the cingulate cortex. We ran
ICA multiple times, each time requesting a different number
of components, ranging from four to nine. In general, the
components remained stable for the different amount levels
of granularity. However more subtle effects become apparent
at greater granularities.
Mouse structural connectivity fingerprints
To summarize the connectivity of the different parts of the
cingulate ROI with the rest of the brain, we describe the
correlation of connectivity of seed areas in the cingulate
with target areas in the rest of the brain as ‘connectivity
fingerprints’ (cf. Passingham etal. 2002; Mars etal. 2018).
To this end, we placed ten seeds in the cingulate ROI at
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1915Brain Structure and Function (2024) 229:1913–1925
even intervals along the rostral-caudal axis. Anteriorly, one
seed was placed in area 25 and another one in area 32. More
caudally, four seeds were placed in area 24 and 24′ of the
mid-cingulate. Finally, we placed an additional four seeds in
the retrosplenial area; one of which was placed in the most
posterior-lateral part of RSA, just above the post-subiculum.
We chose target regions on the basis of multiple criteria.
Firstly, regions were selected that receive projections from,
or project to, the cingulate according to existing literature.
Importantly, the target areas should have a connectivity
profile that is able to dissociate different parts of cingulate
cortex, to illustrate the principles of connectivity across this
part of cortex. For instance, regions involved in control of
arousal (e.g., hypothalamus, anterior insula) and reward pro-
cessing (e.g., amygdala, anterior insula, nucleus accubens,
and orbitofrontal cortex) are expected to show connectiv-
ity to anterior and, in humans, subgenual cingulate cortex
(Medford and Critchley 2010; Alexander etal. 2019); areas
involved in motor control (e.g., caudoputamen, premotor
cortex, and parietal cortex) to mid-cingulate areas involved
in motor control (Beckmann etal. 2009; Vogt 2016); and
medial temporal areas (e.g., hippocampus) to posterior areas
(Margulies etal. 2009). Secondly, the results from the ICA
were used to ensure that the target regions would be able to
differentiate between the seeds. For instance, a nucleus of
the thalamus that projects strongly to the entire cingulate
ROI is of little use for distinguishing between the different
cingulate subregions. Finally, target regions were only con-
sidered if their homology across mouse and human brains
is well established. By these criteria, the following 9 target
regions were selected for the mouse connectivity finger-
prints: (1) hippocampal formation, (2) amygdala, (3) nucleus
accumbens, (4) hypothalamus, (5) caudoputamen, (6) sec-
ondary motor area, (7) medial parietal association cortex,
(8) dorsal agranular insular cortex, (9) ventral orbital cortex.
Mouse resting state fMRI data
To compare the organization of the cingulate across spe-
cies, it is preferable to use the same type of data (Mars
etal. 2021). We obtained publicly available resting state
functional MRI data from both mice and humans. We
used these data to estimate ‘functional connectivity’, i.e.,
similarity in time courses of spontaneous blood oxygena-
tion level dependant contrast fluctuations across voxels.
Mouse resting state fMRI scans were downloaded from
an existing pre-processed dataset collection (https:// doi.
org/ 10. 34973/ 1he1- 5c70) (Grandjean 2020). For these
datasets, mouse functional MRI acquisitions were con-
ducted in accordance with the Swiss federal guidelines
and under a license from the Zurich Cantonal Veterinary
Office (149/2015) as well as the ethical standards of the
Institutional Animal care and use Committee (A*STAR
Biological Resource Centre, Singapore). Scans from 182
(111 male, 71 female) healthy wild-type mice (C57BL/6
strain) were downloaded. These scans, in turn, belong to
different sub-datasets (Table1).
In all these sub-datasets, the mice were anesthetised
with isoflurane (see Grandjean etal. (2014) for a detailed
protocol). Subsequently, the mice were mechanically ven-
tilated and placed on an MRI-compatible cradle. During
the scanning, the anaesthesia was maintained with a com-
bination of isoflurane (0.5%) and medetomidine infusion
(0.1mg/kg/h). Different scanner settings were used for
each of the datasets.
The mouse scans were preprocessed as described in
Huntenburg etal. (2020). Briefly, the anatomical scans
were corrected for the B1-field inhomogeneity (ANTs,
N4BiasFieldCorrection), denoised (ANTs, DenoiseImage),
brain-masked (ANTs, antsBrainExtraction.sh) and, via the
study template, registered to the Allen reference template
(resampled to a 0.2 mm3 resolution, ANTs, antsRegistra-
tion). The functional scans were despiked (AFNI, 3dDe-
spike), motion corrected (AFNI, 3dvolreg), corrected
for the B1 field, denoised, brain masked and registered
to their anatomical images. Finally, they were bandpass
filtered (0.01–0.25Hz, AFNI, 3dBandpass) and an ICA
was applied to determine nuisance components which were
subsequently filtered out (https:// github. com/ grand jeanl ab/
Mouse MRIPr ep, FSL, FIX).
The mean timeseries were extracted from the seed and
target locations for each scan using fslmeants and correla-
tions between the timeseries was calculated for each sub-
ject using 1ddot. Finally, the correlations were averaged
over the subjects and visualised into a fingerprint which
indicates how a single target regions connects to the dif-
ferent cingulate seeds.
Table 1 rs-fMRI mouse datasets Dataset N subjects (M/F) DOI
AD2 14/18 https:// doi. org/ 10. 1016/j. neuro image. 2016. 03. 042
AD3 20/0 https:// doi. org/ 10. 1177/ 02716 78CX2 10820 16
CSD1 77/0 https:// doi. org/ 10. 1016/j. neuro image/ 2016. 08. 013
aes1 0/2 https:// doi. org/ 10. 1016/j. neuro image/ 2014. 08. 043
aes2 0/51 https:// doi. org/ 10. 18112/ openn euro. ds001 653. v1.0.2
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1916 Brain Structure and Function (2024) 229:1913–1925
Human resting state fMRI data
To study human functional connectivity, we used the S1200
7T rs-fMRI dataset of the Human Connectome Project
(HCP, available at https:// db. human conne ctome. org) (Van
Essen etal. 2013). The precise parameters for both the data
acquisition and preprocessing have been described elsewhere
(Glasser etal. 2013; Smith etal. 2013). In short, rs-fMRI
was acquired using a gradient-echo EPI sequence at 7T
with the following parameters: TR = 1000ms, TE = 22.2ms,
multiband-factor = 5, isotropic resolution = 1.6mm, field-
of-view = 208 × 208mm, bandwidth = 1924Hz/px, Image
Acceleration factor = 2. Subjects were scanned four times,
each session lasted approximately 16min during which 900
volumes were acquired. For the current research, only the
first of these scanning sessions with posterior-anterior phase
encoding was used.
We carried out quality control based on functional con-
nectivity specificity in the S1200 7T dataset (Grandjean
etal. 2023). We define functional connectivity using strong
(r > 0.1) homotopic interhemispheric correlation within
sensory networks, and absence or anti-correlations (r < 0.1)
between task-positive (sensory) and task-negative networks
(default-mode). To do so practically, we estimated seed-
based connectivity maps relative to a seed in the sensory
cortex. We selected scans with strong homotopic correla-
tions with a contralateral seed and weak correlation with
a seed in the anterior cingulate. The code to achieve this
is available at: https:// github. com/ grand jeanl ab/ Multi Rat.
In the end, 127 scans were downloaded from the HCP (39
male, 88 female). The scans were already preprocessed with
the HCP pipeline (Griffanti etal. 2014; Salimi-Khorshidi
etal. 2014) and were further preprocessed by smoothing
and bandpass filtering (0.01–0.1Hz) the scans using AFNI
3dTproject. The mean timeseries were extracted for the
seed and target locations and correlated to each other using
fslmeants and AFNI’s 1ddot, respectively, for each subject.
As for the mouse, the correlations were averaged over the
subjects and visualised as a single fingerprint for each target
region.
To create the human connectivity fingerprints analogous
to those in the mouse, seeds were placed in the cingulate
along the rostral–caudal axis at even intervals. We used the
atlases of Neubert etal. (2015) and Beckmann etal. (2009)
to assign approximate area names for anterior and midcin-
gulate and for posterior cingulate and retrosplenial cortex,
respectively. Twelve seeds were placed at the following MNI
[x y z] coordinates: seed 1 [4 18 − 10] (area 25), seed 2 [4
30 − 6] (ventral border of area 24 and dorsal border of area
14m), seed 3 [4 40 0] in area 24, seed 4 [4 38 12] (area 24),
seed 5 [4 30 22] (area 24), seed 6 [4 16 32] (border of area
24 and RCZa), seed 7 [4 0 38] (area 23ab/RCZp), seed 8 [4
− 14 36] (area 23ab/RCZp), seed 9 [4 − 30 38] (area 23ab/
RCZp), seed 10 [4 -40 32] (area 31/23ab), seed 11 [4 − 48
16] (area 23ab), seed 12 [10 − 46 8] (area 23ab).
Subsequently, nine target regions were selected which are
considered to be homologues to the mouse target regions,
namely: the hippocampal formation [26 − 16 − 20] (accord-
ing to Amunts etal. (2000), the amygdala [22 − 6 − 16]
(Amunts etal. 2005), the nucleus accumbens [10 16 − 4], the
hypothalamus [4 − 6 − 8], the caudate nucleus [12 16 4], the
supplementary motor area [8 − 4 60] (Neubert etal. 2015),
the superior parietal lobule [30 − 56 62] (SPLC; Mars etal.
(2011)), anterior insula [42 12 − 6], and orbitofrontal cortex
[6 30 − 20] (area 14m; Neubert etal. (2015)).
For a follow-up analysis to investigate connectivity of the
cingulate seeds with human granular prefrontal areas, we
placed additional seeds in granular orbitofrontal cortex [4 46
− 12] (area 11m; Neubert etal. (2015), medial frontal pole
[6 62 4] (FPm; Neubert etal. (2015)), lateral frontal pole [25
57 5] (FPl; Neubert etal. (2014)), medial frontal gyrus [28
40 32] (area 9/46D; Sallet etal. (2013), and area 9m [8 58
28] (Neubert etal. 2015).
To determine whether cingulate seeds possessed charac-
teristic patterns of connectivity probability from the target
areas considered, we carried out repeated-measures analyses
of variance on the data, with factors for seed and target area.
Huyhn-Feldt adjustment was applied where necessary.
Ethics statement
Mouse functional MRI acquisitions were conducted in
accordance with the Swiss federal guidelines and under
a license from the Zurich Cantonal Veterinary Office
(149/2015) as well as the ethical standards of the Institu-
tional Animal care and use Committee (A*STAR Biolocial
Resource Centre, Singapore, IACUC £171203). Mouse
viral tracer experiments were approved by the Institutional
Animal Care and Use Committee of the Allen Institute for
Brain Science, in accordance with NIH guidelines. Human
functional MRI data are publicly available and described in
the core literature referenced here.
Results
Mouse tracer data
We set out to examine the structural networks of the cin-
gulate area in the mouse. Earlier studies demonstrated that
projection similarity across a viral tracer dataset can be
used to examine the projectome of seed regions (Mandino
etal. 2022). Here, we applied the same method by sampling
2000 seeds across the cingulate cortex. To summarize the
outcomes of the seed-based maps, we applied an independ-
ent component analysis. In general, the components of the
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1917Brain Structure and Function (2024) 229:1913–1925
ICA remained stable for the different levels of granularity,
although more subtle effects become apparent at greater
granularities. We here present the solution for six compo-
nents, to provide a balance between granularity and coarse-
ness. Cluster solutions for n = 4 and 9 components are pre-
sented in the Supplementary Material.
The first component overlapped with the anterior part of
our ROI, in the territory delineated as area 25 and partly
as area 32 by Vogt and Paxinos (2014) (Fig.1A). Outside
the cingulate this component overlapped with limbic struc-
tures such as the hippocampal formation, amygdala, and the
nucleus accumbens. Another, weaker, orbitofrontal compo-
nent (Fig.1F) was mostly associated with the anterior cin-
gulate areas, but did not show much association outside the
ROI.
At the posterior end of the ROI, a component overlapped
with the retrosplenial area (Fig.1B). This component was
relatively self-contained and did not extend to as many struc-
tures apart from the superior colliculus and the midbrain. In
addition, there was a component that overlapper with parts
of the retrosplenial area and with visual regions such as the
primary visual areas, the lateral geniculate complex, and the
superior colliculus (Fig.1C).
Two components showed strong overlap with the mid part
of the cingulate, overlapping with the territory of areas 24
and 24′ (Fig.1D/E). The first of these components also over-
lapped with the periaqueductal grey, the pons, the cerebral
peduncles, and various nuclei of the thalamus. The other
component also overlapped with parts of the caudoputamen,
periaqueductal grey, the thalamus and pons (nucleus raphe).
In sum, the data-driven decomposition from the tracer
studies identified components mostly organized along the
anterior–posterior axis. Anterior components showed over-
lap with amygdala and nucleus accumbens, among other
areas. Mid-cingulate areas overlapped with caudate and sec-
ondary motor cortex, posterior areas overlapped with visual
and hippocampal structures. To confirm these results and
allow more direct comparisons across the length of the ROI,
we placed ten seeds spread across the anterior to posterior
dimension. For each seed, we established the whole-brain
tracer connectivity and correlated that with the connectivity
of a series of target areas. This allows a more direct compari-
son across different parts of the cingulate as well as a com-
parison with the resting state fMRI data described below.
The connectivity fingerprints recapitulated the observa-
tions from the ICA. Specifically, anterior seeds tended to
show high connectivity with amygdala and nucleus accum-
bens targets. Orbitofrontal cortex connectivity was also
mostly associated with anterior cingulate seeds, but more
widespread. Hippocampus and hypothalamus both reach
Fig. 1 Independent component analysis of mouse structural connec-
tivity from viral anterograde tracer injection studies relative to the
cingulate area. Six component solution depicting the spatial maps
(hot colors) and the cingulate area seeds associated with the compo-
nent (blue to red) projected onto the outline of the cingulate area
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1918 Brain Structure and Function (2024) 229:1913–1925
the most anterior seed, with the hippocampus also show-
ing strong connectivity with the most posterior seed in the
retrosplenial area.
Again in accordance with the ICA decomposition results,
caudoputamen and secondary motor cortex showed strong
connectivity with mid-cingulate seeds, with caudoputamen
connectivity a bit more widespread than that of secondary
motor cortex. The medial parietal association area followed
a pattern similar to that of secondary motor cortex. Finally,
we looked at the connectivity of the anterior insula. This
showed a quite confined connectivity with the two most
anterior seeds.
Mouse andhuman resting state fMRI data
To enable comparison of cingulate connectivity across the
mouse and the human, we analysed resting state functional
MRI data. This allows us to assess the similarity in the time
courses of spontaneous activation of all areas of the brain.
Such ‘functional connectivity’ is not the same as the ana-
tomical connectivity assessed using tracers, but the two have
been shown to correlate (Grandjean etal. 2017). Using func-
tional connectivity allows us to compare human and mouse
brain organization using the same method. We examined
functional connectivity, using MRI data, of the mouse seed
areas in cingulate cortex with the same targets examined in
the tracer data set. We then compared the MRI-based esti-
mates of cingulate connectivity in the mouse to connectiv-
ity of twelve seeds placed in anterior-to-posterior locations
and the homologous target areasin the human. For both the
mouse (F(72, 12,240) = 59.409, p < 0.001) and the human
(F(88, 10,912 = 53.050, p < 0.001), functional connectivity
showed a seed by target interaction, indicating that the target
areas can be used to distinguish between different cingulate
seeds.
Functional connectivity of mouse amygdala, nucleus
accumbens, and orbitofrontal cortex followed a pattern very
similar to that of the tracer data, with connectivity mostly
restricted to the anterior seeds (Fig.2). The same was true
for human amygdala and to a lesser extent orbitofrontal cor-
tex, which also showed some more posterior connectivity.
Nucleus accumbens, in contrast, has a more widespread con-
nectivity pattern in the human. As was the case in the mouse
tracer data set, human hippocampus showed functional con-
nectivity with the anterior and posterior, but not mid, cingu-
late seeds, although the human pattern is more widespread
than the mouse tracer. Mouse hippocampal functional con-
nectivity, in contrast, showed a very widespread pattern of
functional connectivity. Hypothalamic connectivity was also
more widespread in functional data than in tracer data.
We next investigated a number of target areas that in the
human are known to show connectivity mostly with the mid
part of the cingulate, including the territory of the cingulate
motor areas (Fig.3). Mouse caudoputamen and human cau-
date both showed a widespread connectivity with the cin-
gulate seeds, but mostly peaking in midcingulate areas. The
pattern was much more clear-cut in the cases of connectiv-
ity with the human supplementary motor area and posterior
parietal cortex; these areas had a clear peak of connectivity
with midcingulate areas. We also observed a higher func-
tional connectivity of the mouse secondary motor area and
parietal association area with midcingulate areas, although
the patterns was much less clear than in the human and the
peaks of the two target areas did not overlap. This differ-
ence in pattern was apparent in both the mouse tracer and
resting state functional MRI data. The biggest difference
between mouse and human was observed in connectivity
with the insular target area. In the human, insula showed a
clear affinity with the midcingulate seeds, but in the mouse
both the tracer and functional data showed strongest connec-
tivity with anterior, and to a lesser extent posterior, cingulate
seed areas.
To further illustrate the division of labor between anterior
and mid-cingulate seeds for the mouse, we created whole-
brain functional connectivity maps of Seed 1 (the most ante-
rior seed) and Seed 5 (a mid-cingulate seed). As shown in
Fig.4, these maps replicate the data shown in the bar graphs
of Figs.2 and 3. Seed 2 shows preferential connectivity with
the amygdala and nucleus accumbens, while seed 5 shows
preferential connectivity with caudoputamen and parietal
association cortex. Additional seeds’ connectivity maps are
shown in the Supplementary Material.
Human prefrontal connectivity
As a follow-up, we investigated the connectivity of human
prefrontal areas with the cingulate seeds. Granular tissue
of the sort found in human prefrontal cortex is not found in
rodents (Preuss and Wise 2022). It is therefore important to
quantify how our region of interest, the cingulate cortex, is
connected to it in order to understand any claims of similar-
ity or difference across species. In addition to the agranular
area 14m described above, we quantified functional con-
nectivity of the cingulate seeds with granular orbital area
11m, medial area 9, dorsolateral area 9/46D, and the medial
(FPm) and lateral frontal pole (FPl).
All of these regions showed at least some functional con-
nectivity to at least some of the cingulate regions, although
there were marked differences in the profile of connections
(F(50, 6250) = 25.130, p < 0.001) (Fig.5). Medial prefrontal
areas tended to show stronger connectivity with the most
anterior and posterior cingulate seeds. In contrast, lateral
9/46D shows strongest connectivity with the mid part of the
cingulate. The lateral frontal pole provided a mixture, with
strongest connectivitywith anterior and posterior cingulate
cortex, but noticeably also with mid-level cingulate cortex.
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1919Brain Structure and Function (2024) 229:1913–1925
In sum, all frontal areas tested showed a positive functional
connectivity with human cingulate cortex.
Discussion
We set out to investigate whether the mouse and human cin-
gulate cortex are organized according to similar principles in
terms of their connectivity to other parts of the brain. Over-
all, we show that the two species’ cingulate cortices follow
broadly similar principles, with anterior areas mostly inter-
acting with amygdala, nucleus accumbens, and orbitofrontal
cortex; a midcingulate territory interacting with premotor
and posterior parietal cortex; and a retrosplenial zone inter-
acting with hippocampus. The similarity of these patterns
is inconsistent with theories ascribing homology of rodent
anterior cingulate with primate granular prefrontal cortex
(Krettek and Price 1977; Eichenbaum etal. 1983) or that
suggest rodent cingulate contains a mixture of primate cin-
gulate and granular prefrontal features (Uylings etal. 2003).
Rather, it is consistent with notions that infralimbic cortex
in the mouse is similar to primate area 25 (Alexander etal.
2019), that there is a midcingulate zone with parietal and
premotor connections in both species (Vogt 2016), and a
Fig. 2 Connectivity of subcortical and orbitofrontal target areas with cingulate seed areas in all modalities and species. Error bars indi-
cate ± SEM
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1920 Brain Structure and Function (2024) 229:1913–1925
generally similar anterior–posterior organization in both spe-
cies (cf. Van Heukelum etal. (2020)).
These similarities between species notwithstanding, some
differences are apparent. Overall, many human cingulate
areas have connectivity profiles that seem more distinct from
one another that do those of the mouse cingulate cortex.
Earlier work suggested parietal connectivity in the mouse
is with both midcingulate and retrosplenial cortex (Zingg
etal. 2014) and we indeed see rather widespread parietal
connectivity in the mouse. Premotor and parietal connec-
tivity are more restricted to the mid-cingulate cortex in the
human. Human midcingulate cortex is thought to contain
distinct anterior and posterior subdivisions (Vogt 2016), the
first of which is not present in the mouse (Vogt and Paxinos
2014). In the human, parietal connectivity is stronger in the
posterior part of midcingulate.
Mouse connectivity as assessed using tracers and using
resting state functional MRI were overall in agreement,
but some differences were noticeable. Hypothalamic con-
nectivity as assessed using tracers was very strong in the
most anterior parts of the cingulate, consistent with earlier
reports (van Heukelum etal. 2020), but functional con-
nectivity was more broadly distributed in both species.
Human hippocampal functional connectivity resembled
Fig. 3 Connectivity of caudate, motor and parietal, and insula target areas with cingulate seed areas in all modalities and species. Error bars indi-
cate ± SEM
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1921Brain Structure and Function (2024) 229:1913–1925
that of mouse tracers, but not mouse functional connec-
tivity. This could be due to the effect of anaesthesia on the
resting state fMRI of the mouse, but this awaits systematic
comparison. Hippocampal and hypothalamic connectivity
to posterior seeds was much stronger in the human than
in the mouse. This is potentially due to the presence of a
large posterior cingulate in the human (Bzdok etal. 2015),
whereas in the mouse, this area only contains a retrosple-
nial cortex (Vogt and Paxinos 2014).
The clearest dissociation between the mouse and human
data was in the connectivity of the insula. This is true even
though we seeded in territory commonly described as agran-
ular anterior insula in both species. In the mouse, the insula
seed showed connectivity with anterior parts of the cingulate
Fig. 4 Connectivity of mouse
anterior and midcingulate
seeds. Color strength indicate
z-statistics
Fig. 5 Human functional connectivity of all cingulate seed areas with six prefrontal areas. Error bars indicate ± SEM
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1922 Brain Structure and Function (2024) 229:1913–1925
in both tracer and rs-fMRI data, while in the human, the
insula seed showed strong functional connectivity with
midcingulate areas. The human results are in accordance
with models of dorsal anterior cingulate function in cog-
nitive control and the participation of the two regions in
a so-called salience network (Seeley etal. 2007; Menon
2011). Previous work has shown that the salience network,
although present in both species, has different associations
with the serotonergic network across human and mouse
(Mandino etal. 2022), suggesting that the area has changed
substantially since the last common ancestor of mice and
humans. Alternatively, the insula seed areas we selected
in human and mouse are not homologous. We have taken
a region commonly used in neuroimaging studies as our
human anterior insula (Cieslik etal. 2015; Molnar-Szakacs
and Uddin 2022), but Öngür and Price (2000) describe a
number of insular regions more anteriorly, on the caudal
orbital surface. Whether the anatomical similarity between
these humancaudal orbital areas and mouse insular areas
is greater than that between our human insula seed and the
mouse is a topic for further investigation.
It is important to emphasize that we here compare prin-
ciples of cingulate connectivity across species, rather than
matching cingulate areas across the human and mouse brain
one by one. We have previously used connectivity finger-
prints to make more explicit, quantitative comparisons
between regions of the human and macaque monkey brain
(Mars etal. 2013; Sallet etal. 2013; Neubert etal. 2014); we
developed a formal framework to do so (Mars etal. 2016)
which has been used by a number of other groups since
(Thompkins etal. 2018; Wang etal. 2019; Schaeffer etal.
2020). However, humans and mice share a common ances-
tor about 87 millions years ago, which is much more than
the 29 million years of humans and macaques (Kumar etal.
2022). This means that changes in how connections relate
to other aspects of brain organization, such as gene expres-
sion, receptor architecture, and cytoarchitecture, might have
occurred (cf. Krubitzer and Kaas 2005). Testing hypotheses
of similarity between distinct cortical areas in the two spe-
cies should, therefore, ideally use a multi-modal approach.
The current study is a first test of similarity in principles
of connectivity, ongoing and future work will supplement
this work by investigations in other modalities, after which
a more detailed areal comparisons across species can be
achieved.
In general, it is important that the target areas used are
homologous when comparing connectivity across species.
Here, we have taken care to use regions that are identified
as such, but some discussion is in order especially when in
case of targets in the neocortex. The approach used here
can be used to ascertain the degree of similarity/difference
between any areas in human and mouse. With respect to
premotor cortex, the human brain contains areas that have
no homolog in the rodent (Wise 2006), but the two brains’
premotor cortices do follow largely similar organizational
principles (Lazari etal. 2023). The human ventral frontal
cortex contains agranular, dysgranular, and granular areas,
but rodent prefrontal cortex contains only agranular areas
(Wise 2008; Rudebeck and Izquierdo 2022). We here used
human area 14m as defined by Neubert etal. (2015), which
is posterior to the granular areas, as our orbitofrontal cortex
seed. We do note that similar results could we obtained using
targets in granular area 11m. Posterior parietal cortex is dra-
matically expanded in primates compared to other mammals
(Krubitzer and Padberg 2009), but a mouse parietal associa-
tion area that is homologous to primate posterior parietal
cortex has been identified (Lyamzin and Benucci 2019). The
current human parietal results are similar for targets overlap-
ping with human MIP or 7A (Mars etal. 2011).
Apart from these differences described earlier, it should
be taken into account that the human cingulate is embedded
within a much larger and more elaborate neocortical network
than that of the mouse. This means that, even if the overall
organization of the two species’ cingulate with homologous
areas is comparable, connectivity with non-homologous
areas mean that the overall connectivity profile can still be
quite distinct. This was previously shown to be the case for
the human dorsal caudate, although striatal connectivity fol-
lows similar organisational principles in both species, con-
nectivity of the dorsal caudate with the human frontal pole
means that its connectivity profile is distinct from any found
in the mouse (Balsters etal. 2020). Connectivity between
the human medial frontal gyrus and human cingulate is evi-
dent in the present data, in particular area 9/46D as defined
by Sallet etal. (2013), and in previous studies (Sallet etal.
2013; Loh etal. 2018). In the striatum, areas with a distinct
human connectivity profile were associated with higher
order cognitive processes, including executive control and
language. It remains to be seen whether functional differ-
ences are found between the two species’ cingulate regions.
Model species are an essential part of research in biology
and by extension neuroscience (Striedter 2022). Differences
between the model and the species of ultimate interest, i.e.,
the human, are to be expected and do not necessarily present
a problem for translational neuroscience, as long as these
differences are properly understood. Whole-brain, high-
throughput data are now increasingly available and allow us
to gain a much more systematic understanding of such differ-
ences than ever before (Mars etal. 2014). The present work
contributes to this effort by comparing a major target area
for clinical research across species by means of connectivity.
Future work will focus on comparing these results obtained
using comparative connectivity with those obtained using
other modalities, such as spatial patterns of gene expression,
tissue properties, and receptor densities (Vogt etal. 2013;
Beauchamp etal. 2022).
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1923Brain Structure and Function (2024) 229:1913–1925
In sum, this work shows the feasibility of extending exist-
ing approaches of comparing frontal cortical organization
across species using functional MRI to rodent-human com-
parisons. The results show a generally conserved macro-
level organization, although there are important differences
in both regional specialization and embedding within larger
cortical networks. Such differences are important to take
into account when performing between-species translations
in the context of clinically relevant research.
Supplementary Information The online version contains supplemen-
tary material available at https:// doi. org/ 10. 1007/ s00429- 024- 02773-9.
Author contributions ATBvH: conceived experiment, data analysis,
data interpretation, writing—first draft; SvH: data interpretation, writ-
ing—review and editing; MFSR: data interpretation, writing—review
and editing; JG: conceived experiment, data analysis, data interpre-
tation, writing—review and editing, project supervision; RBM: con-
ceived experiment, data analysis, data interpretation, writing—first
draft.
Funding The work of RBM was supported by the EPA Cephalosporin
Fund and the Biotechnology and Biological Sciences Research Council
(BBSRC) UK [BB/X013227/1]. The Wellcome Centre for Integrative
Neuroimaging is supported by core funding from the Wellcome Trust
[201319/Z/16/Z]. For the purpose of open access, the authors have
applied a CC BY public copyright licence to any Author Accepted
Manuscript version arising from this submission.
Data availability The Allen Institute tracer data are available for non-
commercial purpose (http:// conne ctivi ty. brain- map. org/). The mouse
resting-state fMRI data are available under the terms of the CC-BY-4.0
licence (https:// doi. org/ 10. 34973/ 1he1- 5c70). The human resting-state
fMRI data are available under the terms of the HCP Data Use terms
(https:// human conne ctome. org/). Mouse resting state fMRI pipelines
are available at https:// github. com/ grand jeanl ab/ Mouse MRIPr ep.
Declarations
Conflict of interest None.
Open Access This article is licensed under a Creative Commons Attri-
bution 4.0 International License, which permits use, sharing, adapta-
tion, distribution and reproduction in any medium or format, as long
as you give appropriate credit to the original author(s) and the source,
provide a link to the Creative Commons licence, and indicate if changes
were made. The images or other third party material in this article are
included in the article’s Creative Commons licence, unless indicated
otherwise in a credit line to the material. If material is not included in
the article’s Creative Commons licence and your intended use is not
permitted by statutory regulation or exceeds the permitted use, you will
need to obtain permission directly from the copyright holder. To view a
copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
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