Cerebral Cortex, 2022;32: 1608–1624
https://doi.org/10.1093/cercor/bhab285
Advance Access Publication Date: 13 September 2021
Original Article
ORIGINAL ARTICLE
Lea Roumazeilles 1 , Frederik J. Lange2 , R. Austin Benn3 ,
Jesper L. R. Andersson2 , Mads F. Bertelsen4 , Paul R Manger5 , Edmund Flach6 ,
Alexandre A. Khrapitchev7 , Katherine L. Bryant2 , Jérôme Sallet 1,8 and
Rogier B. Mars2,9
1 Wellcome
Centre for Integrative Neuroimaging, Department of Experimental Psychology, University of
Oxford, Oxford OX13TA, UK, 2 Wellcome Centre for Integrative Neuroimaging, Oxford Centre for Functional
MRI of the Brain (FMRIB), Nuffield Department of Clinical Neurosciences, John Radcliffe Hospital, University of
Oxford, Oxford OX39DU, UK, 3 Centro Nacional de Investigaciones Cardiovasculares (CNIC), Madrid 28029,
Spain, 4 Centre for Zoo and Wild Animal Health, Copenhagen Zoo, Frederiksberg 2000, Denmark, 5 School of
Anatomical Sciences, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg 2193, South
Africa, 6 Wildlife Health Services, Zoological Society of London, London NW14RY, UK (now retired), 7 MRC
Oxford Institute for Radiation Oncology, Department of Oncology, University of Oxford, Oxford OX37DQ, UK,
8 Université Lyon 1, Inserm, Stem Cell and Brain Research Institute U1208, Bron 69500, France and 9 Donders
Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen, Nijmegen 6525 HR, The
Netherlands
Address correspondence to Lea Roumazeilles, Department of Experimental Psychology, Tinsley Building, 13 Mansfield Road, Oxford OX1 3SR.
Email: learoumazeilles@gmail.com; Rogier B. Mars, Centre for Functional MRI of the Brain (FMRIB), Nuffield Department of Clinical Neurosciences,
John Radcliffe Hospital, Headington, Oxford OX9 3DU. Email: rogier.mars@ndcn.ox.ac.uk
Abstract
Comparative neuroimaging has been used to identify changes in white matter architecture across primate species
phylogenetically close to humans, but few have compared the phylogenetically distant species. Here, we acquired
postmortem diffusion imaging data from ring-tailed lemurs (Lemur catta), black-capped squirrel monkeys (Saimiri boliviensis),
and rhesus macaques (Macaca mulatta). We were able to establish templates and surfaces allowing us to investigate sulcal,
cortical, and white matter anatomy. The results demonstrate an expansion of the frontal projections of the superior
longitudinal fasciculus complex in squirrel monkeys and rhesus macaques compared to ring-tailed lemurs, which
correlates with sulcal anatomy and the lemur’s smaller prefrontal granular cortex. The connectivity of the ventral pathway
in the parietal region is also comparatively reduced in ring-tailed lemurs, with the posterior projections of the inferior
longitudinal fasciculus not extending toward parietal cortical areas as in the other species. In the squirrel monkeys we note
a very specific occipito-parietal anatomy that is apparent in their surface anatomy and the expansion of the posterior
projections of the optical radiation. Our study supports the hypothesis that the connectivity of the prefrontal-parietal
regions became relatively elaborated in the simian lineage after divergence from the prosimian lineage.
© The Author(s) 2021. Published by Oxford University Press.
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/),
which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
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Cortical Morphology and White Matter Tractography
of Three Phylogenetically Distant Primates: Evidence
for a Simian Elaboration
Cortical Morphology and White Matter Tractography of Three Phylogenetically Distant Primates
Roumazeilles et al.
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Key words: association cortex, association tracts, cercopithecid, connectivity, platyrrhine, strepsirrhine
Introduction
Materials and Methods
Data
For this study we used three postmortem brains from each of
the following species: ring-tailed lemurs (L. catta, between 3 and
11 years, 3 males), black-capped squirrel monkeys (S. boliviensis,
between 2 and 19 years old, 1 female, 2 males), and rhesus
macaques (M. mulatta, between 11 and 15 years old, 1 female,
2 males). The samples were obtained from Copenhagen Zoo
(lemurs and squirrel monkeys), the Zoological Society of London (squirrel monkey), and the University of Oxford’s Biomedical Sciences (macaques). All brains were extracted and fixed
within 24 h after the death of the animal. The brains from
the Copenhagen Zoo were obtained after the animals had been
euthanized with sodium pentobarbital (intravenous) in line with
population management decisions, independent of the current
study (Bertelsen 2019). Once euthanized, the carotid arteries
were immediately cannulated, and the heads were perfused
with an initial rinse of 0.9% saline (1 l/kg) solution at a temperature of 4 ◦ C followed by 4% paraformaldehyde in 0.1 M
phosphate buffer (PB) (1 l/kg) at 4 ◦ C. The brains, which showed
no signs of neuropathology, were removed from the skull and
post-fixed in 4% paraformaldehyde in 0.1 M PB (24 h at 4 ◦ C).
The brains were subsequently formalin-fixed in a phosphatebuffered saline (PBS) solution and shipped to Oxford in PBS. The
brain from the Zoological Society of London was obtained after
the death of the animal from a range of age-related conditions.
No evidence of brain pathology was noticed during the necropsy.
The brain was fixed in a 10% neutral buffered formalin solution
and transported to Oxford in formalin. The brains from the
University of Oxford’s Biomedical Sciences were obtained after
the animals had been euthanized for reasons unrelated to this
study. Immediately after death, the brains were perfusion fixed
with formalin and stored in a 10% neutral buffered formalin
solution with azide.
Imaging Protocol
All brains were rehydrated in a PBS solution 1 week prior to
scanning and placed in fomblin or fluorinert for the scanning
procedure. The diffusion-weighted MRI data were acquired from
the whole brain using a 7 T preclinical MRI scanner (Varian,
Oxford UK). The scanner bore diameter is 210 mm, the gradient
coil references are the following: 205_120_HD (Varian, Oxford
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Comparative neuroscience is an important approach for
understanding general brain anatomy and function. Macaques
are one of the most commonly studied nonhuman primate
species for both ethical and practical reasons (Manger et al. 2008;
Perretta 2009). Cercopithecids (Old World monkeys), such as
macaques, shared a common ancestor with the Hominoids (the
apes including humans) around 25 million years ago (Perelman
et al. 2011). With the Platyrrhines (New World monkeys), the
Cercopithecids and Hominoids form the infraorder Simiiformes
(simian primates), thought to share extensive neuroanatomical
similarities. Such similarities are the basis of the translational
paradigm in neuroscience, using model species to understand
the human brain. However, primates also demonstrate specific
mosaic evolution even when correcting for the size of the
brain (Smaers and Soligo 2013). Therefore, it is important to
compare brain organization in a range of different species
to understand how closely the neuroanatomy of traditional
animal models parallels human brain organization, but also
to elucidate broader principles of neuroanatomical diversity
across primates, and to reveal potential species-specific
specializations.
Neuroimaging techniques, such as magnetic resonance
imaging (MRI), have recently come of age as a tool for wholebrain comparative anatomy (Mars et al. 2014; Rilling 2014).
Although MRI provides an indirect quantification of anatomy
and is of coarser resolution than classical anatomical techniques, it allows fast, whole-brain quantification of potentially
multiple modalities from a single brain (Lerch et al. 2017). These
data can, in turn, be related to histological results where they
are available (Large et al. 2016; Reveley et al. 2017). Several
software packages also permit the reconstruction of cortical
brain surfaces from MRI data, which allows investigation of
cortical morphology. MRI-based investigations of white matter
anatomy in species across the primate order is also facilitated
by standardized tools, leading to the creation of white matter
atlases of the human, chimpanzee, and macaque brain (Bryant
et al. 2020; Warrington et al. 2020).
Comparative neuroimaging studies of white matter architecture in primates have revealed evidence for an expansion of the
frontal association tracts in humans compared to other species
(Rilling et al. 2008; Barrett et al. 2020; Eichert et al. 2020), as well as
more elaborated white matter organization within the great ape
ventral visual stream compared to macaques (Roumazeilles et
al. 2020); however, such studies have rarely included Platyrrhines
and Strepsirrhines (prosimian primates), focusing instead on
the Cercopithecids. This is despite the fact that important brain
characteristics emerged in Simiiformes, and continued to evolve
in this lineage. Such characteristics include additional granular prefrontal cortical areas and more extensive fronto-parietal
connectivity (Preuss and Goldman-Rakic 1991; Krubitzer 2009).
These novel characteristics have been interpreted as adaptations to specific lifestyles and environments (Passingham and
Wise 2012; Genovesio et al. 2014).
Here, we study the neuroanatomy of ring-tailed lemurs
(Lemur catta), black-capped squirrel monkeys (Saimiri boliviensis),
and rhesus macaques (Macaca mulatta), using high-resolution
diffusion MRI in postmortem samples. All three species are
diurnal primates, live in large multi-male/multi-female groups,
and are at least partly arboreal. By taking advantage of newly
developed tools, we established robust MRI templates and reconstructed the cortical surfaces. Using tractography in conjunction
with the templates we reconstructed white matter tracts for
the three species while the surfaces allowed us to visualize
their cortical, sulcal, and white matter organization. This
enabled us to investigate how changes in brain organization,
previously seen across simians, compare to differences with
species belonging to other phylogenetic lineages. Specifically,
we hypothesized that long-range association tracts might be
less extensive in prosimian primates compared to simians.
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Cerebral Cortex, 2022, Vol. 32, No. 8
UK) with a Gmax of 50 G/cm. The radiofrequency coil was
made by Rapid Biomedical GmbH (Rimpar, Germany) and is a
birdcage transmit receive coil with 72 mm ID. We used a 2D
diffusion-weighted spin-echo multi-slice protocol with single
line readout (DW-SEMS; TR = 10 s; TE = 26 ms; Matrix size = 128
× 128 with a sufficient number of slices to cover each brain;
resolution for lemurs and squirrel monkeys: 0.5 × 0.5 × 0.5 mm3 ,
and resolution for macaques: 0.6 × 0.6 × 0.6 mm3 ). A total of
16 non-diffusion-weighted (b = 0 s/mm2 ) and 128 diffusionweighted (b = 4000 s/mm2 ) volumes were acquired with
diffusion encoding directions evenly distributed over the whole
sphere (single shell protocol). To assess the data quality, we
computed the signal-to-noise ratio (SNR) for each individual
scans from the diffusion-weighted volumes. The SNR was
defined as the ratio between the mean signal in the brain and
the mean signal outside the brain. We also computed the mean
fractional anisotropy (FA) and mean diffusivity (MD) in the white
matter of each individual, as well as in the corpus callosum.
Values for these measures are comparable between individuals,
species, and brain providers (Fig. 1).
Diffusion MRI Data Preprocessing
All data were preprocessed using the same protocol implemented in the module phoenix of the MR Comparative Anatomy
Toolbox (Mr Cat; www.neuroecologylab.org). Briefly, the steps
are as follows: We first converted the datasets to NIFTI format,
then built an image based on the volumes acquired without a
diffusion gradient as well as a binary mask of this image. Using
tools from FSL (www.fmrib.ox.ac.uk/fsl), we then fitted a diffusion tensor model using FSL’s dtifit including saving the tensor
image which is used in the subsequent template creation. The
principal direction image helped to reorient the data to approximate AC/PC (anterior commissure/posterior commissure) conventional orientation which sets the origin at the middle of the
anterior commissure, where a small bundle of fibers decussate.
Following the preprocessing, BedpostX (Behrens et al. 2007) was
used to fit a crossing fiber-model to the data, allowing for three
fiber orientations.
Template Creation
We created templates for each of the species using the method
described in Lange et al. (2020b). This method employs a
registration-based, multi-resolution, iterative template creation
strategy including spatial unbiasing of both affine and nonlinear
shape changes. Registration is performed using the MultiMOdal
Registration Framework (MMORF) (Lange et al. 2020a). MMORF
is a multimodal registration tool for simultaneous alignment of
datasets with both scalar and tensor MRI images. Multimodal
registration offers advantages over traditional registration
algorithms, as it is able to exploit the fact that different imaging
modalities provide distinct types of information (e.g., intensity
and orientation) and often contain most information at different
locations in the brain. Here, we utilized the no-diffusion images
with T2 contrast (nodif ) and the tensor images from FSL’s dtifit
(dti_tensor). As these images were generated from the same raw
diffusion-weighted data, they were already co-registered for
each individual and have been oriented to approximate the
AC/PC convention.
Any residual non-brain tissue remaining after dissection was
excluded from the images using a manually defined brain mask
in order to avoid artifacts in the resulting templates. The scalar
images were intensity bias-field corrected using FSL’s FAST tool
(Zhang et al. 2001) and globally intensity normalized. Next, a
random individual was chosen as an initial template space and
all three individual scalar images were then affine registered
to this space using FLIRT (Jenkinson and Smith 2001). The midtransformation matrix was obtained to unbias the template
toward any individual and the scalar images were then resampled to this unbiased reference and voxelwise averaged across
subjects. This averaged image required rigid reorientation to
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Figure 1. Data quality assessment. For each individual, the values of SNR, mean MD, and mean FA in white matter as well as mean FA in the corpus callosum are
reported. The marker shape code identifies the different species, while the color code identifies the provenance of the brain as indicated in the legend. FA: fractional
anisotropy; MD: mean diffusivity; SNR: signal-to-noise ratio.
Cortical Morphology and White Matter Tractography of Three Phylogenetically Distant Primates
Surface Creation and Labeling
Surfaces were generated with the preclinical surface pipeline
precon_all (https://github.com/neurabenn/precon_all). precon_all
is a minimalist adaptation of Freesurfer’s (Fischl 2012) reconall pipeline, aiming to provide broad flexibility to reconstruct
cortical surface meshes without a known segmentation or parcellation scheme. This allows precon_all to generate cortical surface meshes in lesser studied animal models. It consists of a
modularly designed pipeline and can run brain extraction, tissue
segmentation, white matter filling, and surface generation in
a continuous workflow on images with a T1-like contrast. To
accommodate this, we converted the T2 contrast of our templates to obtain T1-like contrast images, using FSL tools. We
inverted the intensities by multiplying the template image by −1
and adding the maximum intensity of the initial image, making
sure the cerebrospinal fluid and ventricle intensities remained
at zero.
In all three templates, we ran precon_all twice; the first run
used the automated segmentation from ANTs Atropos (Avants
et al. 2009), and the second used a hand-edited WM mask. The
WM segmentation was filled with hand-drawn “subcortical” and
“non-cortical” masks. The subcortical mask is an inclusion mask
and begins at the superior border of the corpus callosum and
fills the subcortex between the outer borders of the left and right
lateral ventricles. The non-cortical mask lies directly posterior
and inferior to the subcortical mask and includes the cerebellum
and brainstem. Both subcortical and non-cortical masks
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were drawn using ITK-SNAP (www.itksnap.org, Yushkevich
et al. 2006). The filling process uses these masks to remove
the cerebellum and brainstem and fill the subcortex between
the lateral ventricles beneath the corpus callosum. This created
the prerequisite volumetric image that can be used to create
white, pial, and midthickness surfaces. The final surfaces
presented here all use a hand-edited WM mask and they were
downsampled in connectome workbench to a normal sphere
with 10 242 vertices.
For visual comparison with known anatomical regions, we
also labeled sulci and specific areas on the cortical surface.
Major sulci were labeled on the cortical surface of the rhesus
macaque and squirrel monkey using the terminology used for
the macaque by Petrides (2005, 2011). For the ring-tailed lemurs,
apparent similarities in sulcal patterns could be observed but
only few studies existed on this genus with a lack of consensus
on the labeling to be used for some sulci (Mott and Kelley
1908; Brodmann 1909; Connolly 1936; Radinsky 1975). Therefore,
to be consistent with the macaque terminology, we refer to
the ambiguous lemur sulci with a “l” prefix to reflect on their
probable homology or at least the shared topography with the
macaque sulci.
Cortical labels were drawn from previous illustrations on the
surface using Connectome Workbench tools (Marcus et al. 2011).
For the lemur, the primary visual (V1) and motor cortex (M1)
borders were based on illustrations from histological studies
(Mott and Kelley 1908; Fasemore et al. 2018). For the squirrel
monkey these borders were based on the VALiDATe29 atlas,
providing surface borders based on histological data (Schilling
et al. 2017). For the macaque, V1 and M1 borders were based on
several histological atlases that have been adapted to standard
macaque surface (von Bonin and Bailey 1947; Paxinos et al.
2000). For the prefrontal (PF) cortex, we used the definition from
Passingham and Wise (2012) which defines PF as all the areas
anterior to any of the premotor and supplementary motor areas.
For PF and granular areas in the macaque and squirrel monkey,
we used illustrations from this book (Passingham and Wise
2012), completed by illustrations from another squirrel monkey
source (Rosabal 1967). There exists only a limited amount of
studies about the ring-tailed lemur prefrontal cortex, therefore
we combined illustrations of another prosimian, the bushbaby
(Preuss and Goldman-Rakic 1991), with the previously mentioned lemurs illustrations (Mott and Kelley 1908) to estimate
the extent of the lemur prefrontal cortex and its granular areas.
Tractography
The tracts were reconstructed using probabilistic tractography
as implemented in the Xtract tool (Warrington et al. 2020). We
defined tractography seed, target, and exclusion masks in the
template space of each species. These were then transformed to
the diffusion space of each individual using the warps obtained
during the template creation. We defined all masks to be in as
similar an anatomical position as possible in all three species,
based on anatomical landmarks (see details below). The tractography algorithm starts from the seed, the streamlines follow
local orientations sampled from the posterior distribution given
by BedpostX and only the streamlines that reached or passed
through the target and not through the exclusion mask were
conserved. All the Xtract options were the default, only the step
length was adjusted to 0.2 mm to reflect the small voxel and
brain size of our data. In each seed voxel 1000 samples were
seeded. The output of the tractography is a tractogram image
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match the AC/PC orientation. The rigid reorienting matrix was
combined with the previous affine matrix to obtain our final
affine transformation matrix. This was then applied to both
scalar and tensor images (using FSL’s applywarp and vecreg commands, respectively) and the resulting images were averaged
across each modalities separately, using a log-tensor averaging
for the tensor images, creating our initial scalar and tensor
templates. Both images from each subject were then smoothed
and simultaneously nonlinearly registered to the initial template at a coarse warp resolution (16 mm isotropic). This process
was repeated, doubling the warp resolution every other iteration and reducing the amount of smoothing, for a total of 10
iterations (final warp resolution of 0.5 mm isotropic for lemurs
and squirrel monkeys and 0.6 mm isotropic for macaques). At
each iteration, the warps describing the transformation from
the template space to subject space were spatially unbiased and
the resampled images obtained with these warps were averaged
as before to create the next template iteration. MMORF uses a
cubic B-spline elastic transformation with mean squared error
as the scalar cost function, mean squared Frobenius norm as the
tensor cost function, and regularization based on the singular
values of the local Jacobian field to ensure warps remain diffeomorphic. The combination of scalar, tensor, and regularization
cost functions results in warps which maximize gray and white
matter tissue-type overlap, as well as correctly registering location and orientation of white matter bundles, while adhering to
biologically plausible set of deformation constraints.
Each individual fractional anisotropy image and mean principal diffusion direction distribution (in vector form, output of
BedpostX) were transformed to the template space using the
applywarp and vercreg FSL commands, respectively. We then
averaged these images across individuals of the same species,
to obtain mean principal diffusion image and mean fractional
anisotropy image in template space.
Roumazeilles et al.
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Cerebral Cortex, 2022, Vol. 32, No. 8
which represents the fiber probability distribution. For all protocols, a second tractography was run inverting the roles of the
seed and target and the resulting tractogram of the two protocols
were added and normalized by dividing the path distribution by
the total number of generated streamlines not rejected by target
or exclusion mask criteria. This normalized tractogram obtained
for each subject was transformed back to the template space,
averaged across subjects and log-transformed to obtain a value
between zero and one, facilitating the threshold determination.
We used a threshold of 0.8 which resulted in selecting the most
similar higher densities of streamlines reaching each voxel for
all tracts and all species.
We will now detail the tractography recipes used for each
tract (Fig. 2). The recipes are based on the Xtract recipes for the
macaque and previous literature (Bryant et al. 2020, 2021). As all
the tracts reconstructed here are unilateral, all exclusion masks
contain a sagittal plane at the midline to avoid streamlines
crossing to the other hemisphere.
Cingulum bundle (CB): The CB has previously been segmented
based on the presence of fibers connecting specific targets
(Heilbronner and Haber 2014). This segmentation has informed
previous tractography protocols reconstructing the CB in primates leading to the adaptation of a three sections protocol to
capture the entirety of the CB (Bryant et al. 2020; Warrington et
al. 2020). We reconstructed the CB in three different sections:
dorsal (CBd), peri-genual (CBp), and temporal (CBt). The seed
and target of the CBd were placed in the white matter of the
cingulum gyrus. Dividing the corpus callosum in three equal
segments, the seed of the CBd was placed at the front of the
most posterior segment (Fig. 2A). Its target was placed at the
start of the genu of the corpus callosum. The exclusion mask
was made of a coronal mask through the territory of the SLFc
at the level of the midpoint of the corpus callosum and an
axial mask below the corpus callosum to avoid invading the
SLFc territory and the CBt, respectively. The seed of the CBp
was placed at the ventral terminal point of the genu of the
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Figure 2. Tractography recipes for lemurs, squirrel monkeys, and macaques. The seed mask (red), the target mask (blue), and the exclusion mask (white) are represented
for the left hemisphere protocols on the template image for each species in radiological convention.
Cortical Morphology and White Matter Tractography of Three Phylogenetically Distant Primates
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consisted of an axial block of the brainstem, a coronal block
directly posterior to the LGN to select only fibers that curl around
dorsally, and a coronal plane just anterior to the seed to prevent
invading the longitudinal fibers.
We used a Matlab in-house routine to produce threedimensional visualization of the averaged log-transformed
tractograms for each species, to facilitate the study and the
representation of the whole tract anatomy (as seen in subpanel
A of tract result figure).
We ran two additional control analyses. The first aimed to
confirm that the ILF did not reach parietal cortex in the lemur.
Our previous protocol reconstructed the tracts based on seeds
and targets placed in the core of the tract, letting the extremities
be defined by the tractography algorithm. For this control, we
therefore used a modified protocol in which we placed the seed
at the posterior extremity in the parietal cortex and the target
at the anterior extremity in the temporal pole and assessed the
likelihood of reconstructing a white matter bundle with such
protocol. We used the MdLF for comparison as it reaches the
parietal cortex in all three species and runs parallel to the ILF in
the temporal lobe. The modified protocols used the same seed
and exclusion for both ILF and MLF, only the targets changed.
In more details, the common large seed was placed in the axial
plane encompassing the ventral posterior parietal cortex of the
three species (Fig. 3A). We used the same exclusion masks as
previously defined for the main tractography of MdLF and ILF
except that we did not include the seeds and targets of these
tracts. The ILF target was placed in the anterior inferior temporal
gyrus (Fig. 3B) and the MdLF target in the anterior superior
temporal gyrus (Fig. 3C). These targets contained the same number of voxels for ILF and MdLF in all species. To account for
the plausibility of the tracts, we then computed the ratio of
streamlines surviving these two tractography protocols. If only
a few streamlines survive the target and exclusion criteria, it
means that a tractography protocol is unlikely to reconstruct
one of the major white matter bundles, such as ILF and MdLF.
Therefore, by comparing the number of surviving streamlines
with these two similar protocols we can assess how likely the ILF
reaches the parietal cortex. If the ratio of streamlines surviving
with the MdLF target compared to the ILF is very high, it means
that MdLF reaches parietal cortex more than ILF and vice versa.
The second control analysis aimed to confirm the interspecies findings concerning the SLFc and OR. To ensure these
effects are not due to changes in overall brain size, we aimed to
show that tracts running in similar parts of the brain showed
dissociable changes between species. If this proved to be the
case, our results cannot simply be ascribed to differences due to
overall scaling of the white matter. From the results of the initial
tractography, we have noticed that the CB, an evolutionarily
conserved tract (Bubb et al. 2018) follows a similar course across
species; its dorsal component runs through the dorsal part of the
cortex parallel to the SLFc, while its temporal component runs
close to part of OR. Therefore, we calculated the ratio between
the number of voxels reached by SLFc and OR and the number
of voxels reached by the CB segment running in a similar part of
the cortex.
Surface Projection Maps
Cortical surface representations were obtained for each tract
of each species to investigate the cortical territory reached by
the tracts. We used a recently developed approach to reduce
the issues caused by gyral bias and superficial white matter
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corpus callosum and its target in the dorsal end of the genu
(Fig. 2B). The exclusion mask was made of a coronal plane just
anterior to the temporal lobe to restrict the tractography to this
specific CB section. The seed and target of the CBt were placed
in the white matter just inferior to the parahippocampal gyrus
posterior and anterior, respectively (Fig. 2C). The exclusion mask
was made of a coronal plane at the level of the midpoint of
the extreme/external capsule, a coronal plane posterior to the
corpus callosum and the seeds and targets of the MdLF and ILF
to avoid invading occipitotemporal or extreme/external capsule
fibers.
Uncinate fasciculus (UNC): The UNC was reconstructed by placing a seed in the superior temporal gyrus where the temporal
and frontal cortices are first separated and a target in the same
coronal section but in the ventral part of the extreme capsule
(Fig. 2D). The exclusion mask was made of a frontal coronal
section at the level of the seed and target but excluding the
seed and target, a posterior coronal section to avoid invading
the temporal tracts, and a frontal dorsal coronal section to avoid
invading dorsal tracts.
Middle longitudinal fasciculus (MdLF): The MdLF was reconstructed by placing a seed in the superior temporal gyrus on
a coronal slice slightly anterior to the central sulcus (Fig. 2E).
Its target was placed posteriorly in the superior temporal gyrus,
just anterior to the posterior terminus of the Sylvian fissure. The
exclusion mask was made of a frontal coronal mask through the
extreme capsule and seeds and targets from the ILF, CBt, and
IFOF to prevent leakage in these fibers.
Inferior longitudinal fasciculus (ILF): The ILF was reconstructed
by placing a seed in the anterior inferior temporal gyrus on a
coronal slice slightly anterior to the central sulcus (Fig. 2F). Its
target was placed posteriorly in the inferior temporal gyrus, just
anterior to the posterior terminus of the Sylvian fissure. The
exclusion mask was made of a frontal coronal mask through the
extreme capsule and seeds and targets from the MdLF, CBt, and
IFOF to prevent invading these fibers.
Inferior fronto-occipital fasciculus (IFOF): We reconstructed the
IFOF by placing a seed in the extreme capsule where it connects
temporal and frontal cortex and a target as a coronal plane
just anterior to the lunate sulcus (Fig. 2G). The exclusion mask
was made of a coronal mask encompassing the whole white
matter except the seed at the level of the seed to avoid spurious
anterior–posterior fibers and the seeds and targets from MdLF,
ILF, and SLFc to prevent invading these tracts.
Superior longitudinal fasciculus complex (SLFc): We reconstructed the SLFc as a complex of the three SLF branches
(Thiebaut de Schotten et al. 2011). The seed was defined as a
large coronal mask in the parietal cortex immediately posterior
to the dorsal end of the central sulcus (Fig. 2H). The target was
also a large coronal mask in the territory of the SLFc at the level
of the anterior commissure. The exclusion mask was made of
an axial exclusion below the corpus callosum to avoid invading
temporal tracts, and three coronal masks in the cingulate gyrus,
two of them at the same coronal level as the seed and target and
one in between, in the region of midpoint of the central sulcus,
to avoid invading the cingulum bundle. Three additional coronal
exclude masks were placed at the same level in the external and
internal capsule to avoid invading these fibers. Finally the seeds
and targets from the MdLF recipe were added to the exclusion
to make sure the SLFc did not invade ventral pathways.
Optic radiation (OR): We reconstructed the OR by placing a
seed in the lateral geniculate nucleus and a target as a coronal
plane just anterior to the lunate sulcus (Fig. 2I). The exclusion
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(Reveley et al. 2015). This approach is to multiply the tractograms
obtained with a whole brain connectivity matrix (Mars et al.
2018). For each species, we obtained an average matrix across
subjects representing the connectivity between all the vertices
of the cortical surface and all the voxels in the brain volume.
We used the brain extracted template image and the template
surface generated above for each species. Each of the tracts from
the tractography (not log normalized or thresholded) was multiplied to this average matrix, to obtain a map representing their
connectivity with the cortical surface. The result was smoothed
using a Gaussian surface smoothing kernel of 1 mm using the
cifti-smoothing command from Connectome Workbench (Marcus
et al. 2011) and log transformed and thresholded at 0.8 as per the
tractography result.
Data Availability Statement
Raw data of the lemur and squirrel monkey will be made
available on the Digital Brain Bank of the Wellcome Centre
for Integrative Neuroimaging (https://open.win.ox.ac.uk/Digita
lBrainBank/#/) upon acceptance of the paper. Macaque data are
already available within PRIME-DE (Milham et al. 2018); http://
fcon_1000.projects.nitrc.org/indi/indiPRIME.html). The scripts
used for preprocessing are available in MrCat (www.neuroeco
logylab.org, https://github.com/neuroecology/MrCat). MMORF
is available as a Singularity image online (https://git.fmrib.o
x.ac.uk/flange/mmorf_beta). The surface pipeline is available
online (https://github.com/neurabenn/precon_all). Template
and surface images, tractography recipes and results, template
and analysis code are available online (https://git.fmrib.ox.ac.u
k/rlea/small_primate_brains).
Results
In this study, we acquired diffusion MRI data from three primate
species representing three distinct lineages: strepsirrhines (ringtailed lemur), platyrrhines (black-capped squirrel monkey), and
cercopithecids (rhesus macaque). The dataset is of high quality
and three individual brains were used for each of the species,
allowing us to establish templates using a recently presented
multimodal registration method (Lange et al. 2020b), and surfaces using a modified version of previous tools (Benn et al.
2020). In turn, these allowed us to investigate and compare the
cortical, sulcal, and white matter anatomy of the three species.
Cortical Surface
Cortical surface reconstructions reveal that all three species
show some degree of cortical folding (Fig. 4A), but this is most
apparent in the macaque, with the squirrel monkey showing
the least evidence for deep sulci in the occipital, and to a
lesser extent, frontal cortex. Due to the lack of consensus in the
literature, we adapted the macaque terminology and added a
“l” prefix for the ring-tailed lemur sulci. The squirrel monkey
cortical surface shows a very lissencephalic anatomy with only
two very pronounced sulci, the lateral sulcus (LaS, also called
Sylvian fissure), and the superior temporal sulcus (STS) (Fig. 4B).
We could also observe three other sulci in all three species: the
principal sulcus (PS), the central sulcus (CeS), and the intraparietal sulcus (IPS). However, we are cautious in labeling these
sulci in lemurs as previous reports have disagreed in their labeling. It is evident from the surface reconstruction that the PS
extends more posteriorly in lemurs than in the other species,
even merging with the IPS. This had been previously interpreted
as a unique sulcus called the coronal sulcus, similar to what
is observed in non-primate mammals (Radinsky 1975), while
others have kept them separated (Mott and Kelley 1908). Others
have argued that the lemur CeS is actually formed by both
the CeS (as indicated here) and the posterior portion of the
PS (Connolly 1936). Posteriorly, the IPS is substantially more
extensive in lemurs and macaques than in squirrel monkeys.
The border between occipital and parietal cortex (marked with
an arrow in Fig. 4A) suggests that much more of the dorsocaudal surface of the occipital lobe is occupied by visual cortex
in squirrel monkeys than in the other species studied.
To put this cortical labeling in context, it is helpful to compare
the sulcal anatomy to known cytoarchitectonic subdivisions in
the three species. We labeled primary visual cortex (V1), primary
motor cortex (M1), prefrontal cortex (PF), and the granular part
of prefrontal cortex (Gr) in the three species (Fig. 4C) based on
existing anatomical atlases (Mott and Kelley 1908; von Bonin
and Bailey 1947; Paxinos et al. 2000; Schilling et al. 2017), and
found that the morphology and cortical territory of V1 differs
substantially across species. V1 shows a very different folding
pattern in lemurs compared to the two other species, apparent
in the dorsally rotated orientation of the calcarine sulcus. Furthermore, V1 occupies proportionally more cortical surface area
in the squirrel monkey (30% of total surface in squirrel monkeys,
against 21% and 15%, respectively, for lemurs and macaques).
The expansion of PF in squirrel monkeys and rhesus macaques
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Figure 3. Additional tractography recipes for lemurs, squirrel monkeys, and macaques. (A) The seed mask (red), (B) the target mask for ILF (yellow), (C) MdLF (blue),
and the exclusion mask (white) are represented for the left hemisphere protocols on the template image for each species in radiological convention.
Cortical Morphology and White Matter Tractography of Three Phylogenetically Distant Primates
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can be illustrated by comparing on the medial surface the
locations and sizes of M1 and PF, which appear further apart and
PF covers more areas in squirrel monkeys and rhesus macaques
than in ring-tailed lemurs. The large arcuate sulcus in rhesus
macaques also increases the cortical territory of PF on the lateral
surface. PF contains more granular territory in squirrel monkeys
and rhesus macaques compared to that of ring-tailed lemurs,
as is confirmed by the ratios of granular surface to prefrontal
surface: 15% in lemurs compared to 30% and 43%, respectively,
in squirrel monkeys and rhesus macaques.
White Matter Anatomy
We reconstructed several white matter tracts using probabilistic
tractography. We employed similar recipes in the three species
based on common anatomical features and principal direction
images identifying landmarks for white matter tract definition
(Fig. 5). All the tracts are displayed as a 3D reconstruction and as
a projection to the cortical surface.
From the limbic tracts, we reconstructed the cingulum bundle (CB). This is a tract extending from the para hippocampal
gyrus, through medial posterior temporal lobe, coursing rostrocaudally superior to the corpus callosum and terminating in
medial prefrontal cortex. Because of the sharp curvature of
this tract, we reconstructed it in three different sections: perigenual (CBp), dorsal (CBd), and temporal (CBt). We were able
to obtain the whole CB with a very similar anatomy showing
prefrontal projections in the three species, while also showing
some posterior parietal projections in squirrel monkeys and
rhesus macaques (Fig. 6). It also appears that the posterior end of
the dorsal segment is located relatively more rostral in squirrel
monkeys compared to rhesus macaques, possibly because of the
difference in the anatomy of the visual cortex described above.
From the temporal lobe tracts, we reconstructed the uncinate
fasciculus (UNC), the middle longitudinal fasciculus (MdLF), the
inferior longitudinal fasciculus (ILF), and the inferior frontooccipital fasciculus (IFOF).
The UNC is a tract that connects the temporal pole to the
medial and orbital prefrontal cortex via the extreme/external
capsule. The UNC is also considered a limbic tract (Alves et al.
2019). The anatomy of the uncinate is quite similar in the three
species studied. Although it has been shown previously that few
fibers reach the frontal pole in macaques as well (Schmahmann
et al. 2007), we observe more streamlines reaching the rostral
prefrontal cortex in the ring-tailed lemur compared to both the
rhesus macaque and squirrel monkey, possibly because of the
reduced granular prefrontal cortex in the lemur (Fig. 6). These
observations suggest that similar cortical areas are innervated
by this tract. The difference observed highlights the expansion
of granular prefrontal cortex in the lineage to which squirrel
monkeys and rhesus macaques belong and the relative position
of prefrontal cortex areas in the three species (Passingham and
Wise 2012).
The MdLF is a longitudinal tract spanning the length of the
superior temporal gyrus and projecting to the occipital and posterior parietal cortex. It has been shown to exhibit a conserved
and similar anatomy in rhesus macaques, great apes such as
chimpanzees and humans (Bryant et al. 2020; Roumazeilles et al.
2020). The anatomy of the MdLF is also very similar in ring-tailed
lemurs, squirrel monkeys, and rhesus macaques studied herein,
with the only difference occurring in the somewhat broader
projections to the occipital cortex in squirrel monkeys compared
to the other species (Fig. 7A–B).
The ILF is a longitudinal tract running parallel to the MdLF
and it has been described in macaques as spanning the length
of the inferior temporal gyrus from the temporal pole to occipital
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Figure 4. Cortical surface labeling. (A) Pial cortical surfaces of ring-tailed lemurs, black-capped squirrel monkeys, and rhesus macaques obtained from the template.
The arrows indicate the dorsal most location of the occipito-parietal cortex in the three species. (B) Labeling of the sulci on the lateral mid-thickness surfaces. AS:
arcuate sulcus; CeS: central sulcus; IOS: inferior occipital sulcus; IPS: intra-parietal sulcus; LaS: lateral sulcus; LuS: lunate sulcus; PS: principal sulcus; STS: superior
temporal sulcus. (C) Labeling of the primary visual cortex (V1), primary motor cortex (M1), prefrontal cortex (PF) and its granular areas (Gr) on the right hemisphere
mid-thickness cortical surfaces.
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and posterior parietal regions (Schmahmann et al. 2007). However, our tractography protocol, although similar in all species,
could not identify a parietal projection in ring-tailed lemurs
even though it was present in both squirrel monkeys and rhesus macaques (Fig. 7A–B). To verify this result was not due to
issues in the tractography protocols, we performed an additional
tractography analysis, using a large seed encompassing the
parietal cortex and targets either in the territory of the anterior
MdLF or the anterior ILF. We calculated the number of surviving streamlines with these two tractography protocols for each
individual and each hemisphere, to investigate the plausibility
of a tract running from the parietal cortex to these two anterior
temporal locations. We then calculated the ratio between these
surviving streamlines for MdLF and ILF protocols. The results
confirmed the observation from the initial tractography. Seeding in ring-tailed lemur parietal cortex showed only minimal
fibers reaching the ILF running through the inferior temporal
gyrus compared to fibers reaching the MdLF running through
the superior temporal gyrus (log ratio around 10) (Fig. 7C). In
contrast, from the parietal cortex of the squirrel monkey, the
MdLF was less likely to be reached than the ILF (log ratio close
to 0), and the rhesus macaque showed similar connectivity of
parietal with MdLF and ILF (log ratio close to 1). This result
suggests parietal connectivity of the ILF in squirrel monkeys and
rhesus macaques, not present in ring-tailed lemurs.
The presence of an inferior fronto-occipital fasciculus (IFOF),
also called the longitudinal fronto-temporal tract or extreme
capsule complex, has been established in several species of
cercopithecids using both tractography and blunt dissection
(Mars et al. 2016; Schaeffer et al. 2017; Decramer et al. 2018;
Barrett et al. 2020; Bryant et al. 2020; Roumazeilles et al. 2020).
This multisynaptic tract has been described as connecting
the occipital lobe and the frontal lobe via the temporal lobe
and the extreme/external capsule. Its overall shape appears
very similar in all three species studied herein, although its
frontal projections appear more robust toward the PF in squirrel
monkeys and rhesus macaques than in ring-tailed lemurs,
and its occipital projections appear more restricted in squirrel
monkeys, particularly compared with the OR projections in that
region of the brain (Fig. 8A–B). Sagittal, coronal, and axial brain
sections of the three species showing the OR, MdLF, and IFOF
reinforce the argument that IFOF is a tract that is distinct from
other tracts occupying the same region (Fig. 8C).
In the dorsal portion of the telencephalon, we reconstructed
a superior longitudinal fasciculus complex (SLFc) encompassing
the three branches of the SLF usually defined in macaques, as
a complex of dorsal longitudinal fibers connecting the frontal
lobe with parietal and posterior temporal cortices. We observed
that in all three species the SLFc terminates posteriorly in the
posterior parietal cortex, but in rhesus macaques and squirrel
monkeys the SLFc projects further rostrally than in ring-tailed
lemurs (Fig. 9A,B). This can also be seen when comparing the
location of the prefrontal cortex and the SLFc projection on the
cortical surface (Fig. 10). Indeed, it would appear that the SLFc in
ring-tailed lemurs shows weaker frontal connectivity, possibly
due to the reduced size of their PF.
The optic radiation (OR) was reconstructed as a tract that
connects the lateral geniculate nucleus of the thalamus and
the primary visual cortex. Its anatomy in the different species
confirms the previous observation made on cortical labeling of
V1, as this tract’s posterior projections highlight the extent of
V1. The relative enlargement of V1 in the calcarine fissure in
the squirrel monkey is evident also from the OR projections.
The lateral position of macaque V1 is also accompanied by weak
lateral projections of OR in this species (Figs 9A,B and 10).
To confirm the differences observed in SLFc and OR, namely
that SLFc connectivity is reduced in ring-tailed lemurs frontal
cortex, and OR is disproportionately expanded in squirrel monkeys, we performed a ratio analysis with tracts that are similar
between the different species and running in similar areas
(dorsal and temporo-occipital). The CB runs in both dorsal and
temporal areas and is a tract usually considered to be conserved
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Figure 5. Anatomical landmarks for white matter tract definition. Sulcal landmarks on the template image (left) and the principal diffusion directions modulated by
the fractional anisotropy (right) are shown for ring-tailed lemurs, squirrel monkeys, and rhesus macaques in radiological convention. The lemur sulci correspond to
the sulci with the “l” prefix as in Fig. 4. Colors of the principal diffusion images indicate the directions: red left–right, green anterior–posterior, and blue dorsal-ventral.
CB: cingulum bundle; CeS: central sulcus; ILF: inferior longitudinal fasciculus; LaS: lateral sulcus; LuS: lunate sulcus; MdLF: middle longitudinal fasciculus; PS: principal
sulcus; STS: superior temporal sulcus; WM: white matter.
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Roumazeilles et al.
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across species (Bubb et al. 2018). Therefore, we performed the
ratio of our two tracts of interest with the CB section that runs
in a similar territory. These analyses confirmed our observation
that the SLFc is proportionately smaller in ring-tailed lemurs,
and it also revealed that the macaque SLFc seems proportionately smaller than that of the squirrel monkey SLFc (Fig. 9C). The
OR was demonstrated to be proportionately larger in squirrel
monkeys, while a very similar ratio with CBt was obtained for
ring-tailed lemurs and rhesus macaques.
Discussion
In the current study, we investigated cortical morphology
and white matter architecture in three species of primates,
representing three distinct lineages within the order, ring-tailed
lemurs (which belong to the suborder Strepsirrhini, family
Lemuroidae, also referred to as a prosimian primate), blackcapped squirrel monkeys (which belong to the suborder Haplorrhini, parvorder Platyrrhini, family Cebidae, also referred to as
New World monkey, simian primate or anthropoid primate), and
rhesus macaques (which belong to the suborder Haplorrhini,
parvorder Catarrhini, family Cercopithecidae, also referred to
as Old World monkey, simian primate or anthropoid primate).
To our knowledge, we present the first reconstructions of white
matter tracts in the ring-tailed lemur, as well as expanding our
knowledge of these tracts in the squirrel monkey. The white
matter tracts show a generalized similarity across the primate
species studied here and those studied previously. Our results
identified an elaboration of prefrontal and parietal connectivity
in squirrel monkeys and rhesus macaques (simians) compared
to ring-tailed lemurs (prosimians), among a range of variations
that might be considered to represent a simian versus prosimian
divergence in cortical organization. We also observed a very
specific occipito-parietal anatomy in the squirrel monkey that
distinguishes the squirrel monkey from the other species
studied.
Despite these variations, the white matter tracts show a
generalized similarity across the primate species studied here
and other primates. Mammals have been shown to share fundamental principles of brain connectivity such as wiring costs
and speed of conduction, and more recently, a conserved relationship in which fewer interhemispheric connections are associated with better intrahemispheric connectivity and vice versa,
maintaining the overall efficiency of communication across a
large range of species (Assaf et al. 2020). The addition of new
cortical association fields in the different lineages of primates
contributes to our knowledge of the evolutionary specializations
of this order (Krubitzer 2009). However, the overall principles of
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Figure 6. Tractography results for the CB and UNC. (A) We represented the averaged log transformed, thresholded tractogram with a 3D reconstruction showing from
left to right: left hemisphere, ventral view, right hemisphere. (B) The projections to the mid-thickness cortical surface show left and right hemispheres from both lateral
and medial views.
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Figure 7. Tractography results for the MdLF and ILF. (A) We represented the averaged log transformed, thresholded tractogram with a 3D reconstruction showing from
left to right: left hemisphere, ventral view, right hemisphere. (B) The projections to the mid-thickness cortical surface show left and right hemispheres from both lateral
and medial views. (C) The boxplot shows the log ratio of surviving streamlines between control protocols using the MdLF or the ILF target. On each box, the central
mark indicates the median, and the bottom and top edges of the box indicate the 25th and 75th percentiles, respectively. The whiskers extend to the most extreme
data points not considered outliers. Each gray dot represents the ratio for one hemisphere from one individual.
white matter organization appear conserved across the primate
order (Rilling et al. 2008; Barrett et al. 2020; Eichert et al. 2020;
Roumazeilles et al. 2020) despite differences in brain size and
sulcal pattern, representing what might be an order-specific
organization of the white matter (Manger 2005). The seven white
matter tracts studied here are consistent with this pattern,
showing a conserved organization in terms of topological relationship and connectivity of comparable brain regions, across
three primate species that represent three distinct lineages
within the order. Despite this overall similarity, interspecific
variations were observed, particularly in the connectivity of
association areas.
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Roumazeilles et al.
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The identified differences between prosimian and simian
primates were mainly associated with the frontal and parietal
cortical areas. Prefrontal cortex has been previously reported to
be proportionately larger in simians than prosimians, with several granular prefrontal cortical areas reported to be present only
in simians (Preuss and Goldman-Rakic 1991). We have illustrated
these findings here on the surface brains we created for the
prosimian and the two simians. The comparative neuroimaging analysis undertaken in the current study provided further
supportive evidence for these suggestions in terms of white
matter organization. Particularly, although we could reconstruct
the SLF in all species studied, there were less extensive frontal
projections in the prosimian, possibly reflecting a weaker frontal
connectivity, which is consistent with the limited size of the
prefrontal cortex reported in prosimians. Similarly, the frontal
projections of the IFOF appear less robust in the prosimian.
In contrast, the UNC, which projects to the granular prefrontal
areas that are present in all three species studied, appeared to
reach the frontal pole more in the prosimian. This illustrates
the reduced size of frontal granular areas observed in prosimians, confined only to the frontal extremity while extending
more posteriorly in simians. We also noticed differences in
the anatomy of the white matter associated with the parietal
cortex when comparing between prosimians and simians. The
ILF showed more limited posterior projections in the prosimian
as it did not reach the parietal cortex, whereas it did in the
two simians studied. In addition, the CB showed projections
to the posterior parietal region in the two simians but not in
the prosimian. These frontal and parietal variations between
prosimians and simians support previous findings showing that
the connectivity between frontal, parietal, and temporal areas
is more complex in simian primates compared to prosimian
primates, giving rise to what has been termed the “anthropoid
elaboration” (Krubitzer 2009).
The additional granular prefrontal cortical areas in simian
primates have been postulated to be associated with certain
ecological and social factors and their abilities to forage in
a more complex niche than prosimian primates. It has been
further argued that these prefrontal networks have increased
access to posterior parietal cortex information related to
relational metrics, using them for more general decision making
processes (Genovesio et al. 2014). The findings of the reduced
parietal ILF projections in prosimians raise similar questions.
Based on tracer work in the macaque monkey, Schmahmann
and Pandya (2006) identified the ILF as a long association fiber
tract of the ventral visual pathway in the occipitotemporal
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Figure 8. Tractography results for the IFOF. (A) We represented the averaged log transformed, thresholded tractogram with a 3D reconstruction showing from left to
right: left hemisphere, ventral view, right hemisphere. (B) The projections to the mid-thickness cortical surface show left and right hemispheres from both lateral and
medial views. (C) The arrows on the sagittal, coronal, and axial slices point to locations where the IFOF (purple) path is clearly separated from the MdLF (blue) and OR
(green). The tracts are shown on the template in radiological convention.
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cortices. Importantly, they also highlighted its connectivity with
parietal cortex, suggesting the importance of integrating the
attentional functions of these areas into the visual processing
of the ventral stream. Although the current state of knowledge
and methods does not allow us to link white matter tracts
and functions with certainty, it is interesting to discuss this
observation in light of the known functions of areas associated
with the ILF. Kaas (2017) highlights an expansion of the ventral
visual stream in simians, presumably to enhance the ability
to recognize individual faces and objects. The ILF has been
specifically associated with providing visual input to this system
for facial recognition (Herbet et al. 2018) and it is therefore
striking that a species such as the lemur, usually living in smaller
groups and relying on audition and olfaction in addition to
vision to recognize individuals, would possess a reduced ILF
(Kulahci et al. 2014). Furthermore, we have previously showed
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Figure 9. Tractography results for the SLFc and OR. (A) We represented the averaged log transformed, thresholded tractogram with a 3D reconstruction showing from
left to right: left hemisphere, ventral view, right hemisphere. (B) The projections to the mid-thickness cortical surface show left and right hemispheres from both lateral
and medial views. (C) Tract ratios with the CBd and CBt for the tracts of interest: SLFc and OR, as well as the rest of the tracts. Both left and right hemisphere ratios
are represented. L: lemurs; S: squirrel monkeys; M: macaques.
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Roumazeilles et al.
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that the ILF is even more complex in great apes, where it is
divisible into two subcomponents, the most ventral of which is
homologous to macaque ILF and reaches face-responsive areas
in all of the anthropoids species studied (Roumazeilles et al.
2020).
Our study also highlights specific features of the occipital
region for the squirrel monkey. The size of the primary visual
cortex, and more generally occipital cortex, is particularly large
in the squirrel monkey compared to the two other species studied. This is associated with the posterior projections of the OR
projecting more broadly than in the two other species. We also
note other subtler differences in tract projections to occipital
regions in squirrel monkeys compared to the two other species,
including broader MdLF projections and more restricted IFOF
projections. In this context, it is also interesting to note that
the ILF appears more dominant in the posterior parietal area in
squirrel monkeys than in macaques. These anatomical details in
the relative size of different cortical regions and the projections
of the associated tracts suggest a potential specialization of the
occipital cortex in squirrel monkeys that has not been observed
in other primates studied to date. Although all three species
examined in this study are diurnal, squirrel monkeys have a
lifestyle that is more arboreal-dependent than the two other
species. Squirrel monkeys rarely come to the ground, and live
and travel through small branches of trees, implying a challenge
for neuronal information processing in both visual and locomotor systems. Interestingly, it has been previously noted that
arboreal rodents devote more cortical territory to visual processing when compared to their terrestrial counterparts (Campi and
Krubitzer 2010).
Limitations and Future Studies
It should be noted that changes in proportion of white matter
across the brains of different species may be due to allometric
scaling (Ventura-Antunes et al. 2013). Inferring departures from
allometric scaling rules generally requires analyses that take
phylogenetic relationships into account and that include many
more species than examined in the present study (Barton and
Venditti 2013). However, the differences reported here are not
differences in the relative quantity of cortical white matter, but
rather qualitative variances between the cortical territories of
a certain white matter tract. We have previously shown that
qualitative variations, such as invasion of new cortical territories
by a particular white matter tract, can be distinguished from
cortical reorganization due solely to the expansion of the brain
(Eichert et al. 2018, 2020). Our results are in line with such
reorganizations of the intracortical white matter, showing that
there are changes in the relative proportion of tracts in the same
cortical areas, such as in the case of the SLFc and the dorsal
cingulum, and that these tracts may project to novel parts of the
cortex, such as in the case of the parietal connections of ILF in
simians.
Tractography is a suitable tool to compare connectivity in
different brains, as it allows for standardized protocols that
are readily comparable across species; however, tractography
is not without its caveats. First, probabilistic tractography
applied to diffusion MRI data has been criticized recently
for generating false positives and false negatives if not used
with proper anatomical constraints (Maier-Hein et al. 2017).
Here, we used previously validated protocols in macaques that
have been shown to reconstruct tracts accurately (Warrington
et al. 2020). Importantly, we were able to use three subjects
per species and thus average the individual tractograms and
threshold the result, which reduces the probability for false
positives and negatives to be conserved in the final tract. Second,
finding anatomical landmarks corresponding across species
can sometimes be difficult, due to their very different overall
anatomy. Taking several points of reference, both cortically
and subcortically, which are known to have only limited
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Figure 10. Cortical surface labeling and tractography. (A) Right hemisphere mid-thickness cortical surface showing M1 (blue), PF and granular areas (light and dark
yellow, respectively), and SLFc projections (pink). (B) Right hemisphere mid-thickness cortical surface showing V1 (orange) and (C) showing OR projections (green).
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Conclusion
In summary, our study provides evidence in the form of white
matter anatomy that supports the concept of the elaboration of
prefrontal and posterior parietal systems in simians compared
to prosimians. This study provides a baseline from which further
studies, using similar standardized methods, can accurately
compare brains across different species. This is of interest to
allow us to understand the various evolutionary trajectories
that influenced the structure of the brain within the different
primate lineages and species.
Funding
L.R. is supported by funding from the Biotechnology and Biological Sciences Research Council (BBSRC) UK [BB/M011224/1].
R.A.B. is supported by a fellowship from the FP7-PEOPLE-2013ITN “Cardionext”. J.S. is supported by a Sir Henry Dale Wellcome
Trust Fellowship [105651/Z/14/Z], IDEXLYON “IMPULSION 2020
grant (IDEX/IMP/2020/14) and the Labex CORTEX ANR-11-LABX0042 of Université de Lyon. The work of R.B.M. is supported
by the Biotechnology and Biological Sciences Research Council
(BBSRC) UK [BB/N019814/1]. The Wellcome Centre for Integrative
Neuroimaging is supported by core funding from the Wellcome
Trust [203139/Z/16/Z].
Notes
We thank Prof. Nicola R. Sibson for her support of the MRI scans.
This research was funded in whole, or in part, by the Wellcome
Trust [203139/Z/16/Z]. For the purpose of open access, the author
has applied a CC BY public copyright license to any Author
Accepted Manuscript version arising from this submission. Conflict of Interest: None declared.
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