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A resource for the detailed 3D mapping of white matter pathways in the marmoset brain

Authors:
Cirong Liu at Institute of Neuroscience Chinese Academy of Sciences
Cirong Liu
  • Institute of Neuroscience Chinese Academy of Sciences
Frank Q. Ye at National Institutes of Health
Frank Q. Ye
John D. Newman
John D. Newman
John D. Newman
  • This person is not on ResearchGate, or hasn't claimed this research yet.
Diego Szczupak at University of Pittsburgh
Diego Szczupak
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Abstract and Figures

While the fundamental importance of the white matter in supporting neuronal communication is well known, existing publications of primate brains do not feature a detailed description of its complex anatomy. The main barrier to achieving this is that existing primate neuroimaging data have insufficient spatial resolution to resolve white matter pathways fully. Here we present a resource that allows detailed descriptions of white matter structures and trajectories of fiber pathways in the marmoset brain. The resource includes: (1) the highest-resolution diffusion-weighted MRI data available to date, which reveal white matter features not previously described; (2) a comprehensive three-dimensional white matter atlas depicting fiber pathways that were either omitted or misidentified in previous atlases; and (3) comprehensive fiber pathway maps of cortical connections combining diffusion-weighted MRI tractography and neuronal tracing data. The resource, which can be downloaded from marmosetbrainmapping.org, will facilitate studies of brain connectivity and the development of tractography algorithms in the primate brain. This resource comprises ultra-high-resolution MRI datasets and corresponding gray and white matter atlases of the marmoset brain to facilitate brain connectivity studies and the development of tractography algorithms in the primate brain.
Comparison of isotropic data resolution, brain volume and fiber volumes between marmosets, macaques and humans a, Compared with our previous 150-µm data¹⁶, the new ultra-high-resolution dataset represents a substantial improvement in spatial resolution, including 80-µm dMRI, 50-µm T2* and 64-µm dMRI. b, Comparison of voxel resolution. The macaque ex vivo dMRI dataset has 250-µm resolution²⁰ whereas the human in vivo dMRI dataset from the 7T human connectome project²¹ has 1,050-µm resolution. In terms of volume (µm³), the resolution of our 64-µm data is 59.6 times and 4,416 times higher in resolution than that of the macaque and human data, respectively. c, Comparison of the brain and fiber volumes (µm³). Brain sample images are from http://brainmuseum.org. All volumes are estimated from three population-based templates, including a marmoset template from 22 adult marmosets, a NMT macaque template³⁹ and a MNI152 adult human template⁴⁰. The five white matter tracts shown are the corpus callosum (blue), the anterior commissure (green), the posterior commissure (red), the fornix (yellow) and the optic white matter (cyan; including the optic nerve, the optic chiasm and the optic tract).
Comparison of isotropic data resolution, brain volume and fiber volumes between marmosets, macaques and humans a, Compared with our previous 150-µm data¹⁶, the new ultra-high-resolution dataset represents a substantial improvement in spatial resolution, including 80-µm dMRI, 50-µm T2* and 64-µm dMRI. b, Comparison of voxel resolution. The macaque ex vivo dMRI dataset has 250-µm resolution²⁰ whereas the human in vivo dMRI dataset from the 7T human connectome project²¹ has 1,050-µm resolution. In terms of volume (µm³), the resolution of our 64-µm data is 59.6 times and 4,416 times higher in resolution than that of the macaque and human data, respectively. c, Comparison of the brain and fiber volumes (µm³). Brain sample images are from http://brainmuseum.org. All volumes are estimated from three population-based templates, including a marmoset template from 22 adult marmosets, a NMT macaque template³⁹ and a MNI152 adult human template⁴⁰. The five white matter tracts shown are the corpus callosum (blue), the anterior commissure (green), the posterior commissure (red), the fornix (yellow) and the optic white matter (cyan; including the optic nerve, the optic chiasm and the optic tract).
… 
The corona radiata imaged at different spatial resolutions a, Coronal slices of the corona radiata (white dashed rectangle) of an ex vivo macaque brain (at 250 µm) and an in vivo human brain (at 1,050 µm). Note that the corona radiata is mostly dominated by projection fibers from the internal capsule (gray arrow). b, Coronal slices showing the corona radiata (white dashed rectangle) of a marmoset brain acquired at increasing spatial resolution. Colored arrows highlight areas that benefit from the use of higher spatial resolution (see the main text for details; a zoomed-in view is provided in Supplementary Fig. 1).
The corona radiata imaged at different spatial resolutions a, Coronal slices of the corona radiata (white dashed rectangle) of an ex vivo macaque brain (at 250 µm) and an in vivo human brain (at 1,050 µm). Note that the corona radiata is mostly dominated by projection fibers from the internal capsule (gray arrow). b, Coronal slices showing the corona radiata (white dashed rectangle) of a marmoset brain acquired at increasing spatial resolution. Colored arrows highlight areas that benefit from the use of higher spatial resolution (see the main text for details; a zoomed-in view is provided in Supplementary Fig. 1).
… 
The FOF and the Muratoff bundle a, Coronal slice (64 µm) through the corona radiata (left) of the marmoset, with the FOF and the Muratoff bundle highlighted (right). b, Sagittal slice (80 µm) showing the FOF and Muratoff bundle. Two white matter fiber pathways run in a similar direction (green: anterior–posterior) and are separated by a small fiber running left to right (red). c, Non-phosphorylated neurofilament staining of coronal slices from the Paxinos atlas⁴¹ and the Hardman atlas⁴² shows that previous histological marmoset atlases cannot distinguish the two fiber bundles due to the lack of fiber-orientation contrasts. Modified from refs. 41,42 with permission (Elsevier Academic Press and CRC Press, respectively). d, Similarly, coronal images of the macaque (250 µm) and human dMRI data (1,050 µm) cannot distinguish the two fiber bundles due to their insufficient spatial resolution.
The FOF and the Muratoff bundle a, Coronal slice (64 µm) through the corona radiata (left) of the marmoset, with the FOF and the Muratoff bundle highlighted (right). b, Sagittal slice (80 µm) showing the FOF and Muratoff bundle. Two white matter fiber pathways run in a similar direction (green: anterior–posterior) and are separated by a small fiber running left to right (red). c, Non-phosphorylated neurofilament staining of coronal slices from the Paxinos atlas⁴¹ and the Hardman atlas⁴² shows that previous histological marmoset atlases cannot distinguish the two fiber bundles due to the lack of fiber-orientation contrasts. Modified from refs. 41,42 with permission (Elsevier Academic Press and CRC Press, respectively). d, Similarly, coronal images of the macaque (250 µm) and human dMRI data (1,050 µm) cannot distinguish the two fiber bundles due to their insufficient spatial resolution.
… 
White matter fiber pathways in the marmoset occipital lobe a–c, White matter structures in the marmoset occipital lobe. Three different coronal slices are presented with the color-coded tract density maps generated from the 64-µm dataset. Colored boxes and arrows highlight local fibers. d–f, Cross-species comparison of the occipital white matter, which shows highly homologous structures across marmosets (64 µm) (d), macaques (250 µm) (e) and humans (1,050 µm) (f). Small fiber branches and local U fibers formed by sulci are not shown. Hp, hippocampus.
White matter fiber pathways in the marmoset occipital lobe a–c, White matter structures in the marmoset occipital lobe. Three different coronal slices are presented with the color-coded tract density maps generated from the 64-µm dataset. Colored boxes and arrows highlight local fibers. d–f, Cross-species comparison of the occipital white matter, which shows highly homologous structures across marmosets (64 µm) (d), macaques (250 µm) (e) and humans (1,050 µm) (f). Small fiber branches and local U fibers formed by sulci are not shown. Hp, hippocampus.
… 
The VHC of primates a, Left: middle sagittal slice of a FA-weighted DEC image of the marmoset brain (80 µm). Right: white arrows highlight the VHC and the area mistakenly labeled as the VHC in most atlases. b, A coronal slice of the marmoset that shows dominant left–right fiber orientation in the VHC. The bottom right shows the fiber orientation distribution image for each voxel and overlaid on the FA image, and the fiber orientation of the voxel highlighted by the white circle is presented. c, A coronal slice of the marmoset brain showing the non-VHC region (fornix area), in which fiber orientation is dominated by the anterior–posterior (DEC-green) direction. d,e, The VHC (d) and non-VHC (e) white matter in the macaque brain, which shows a relatively smaller VHC. f,g, The VHC of the human brain is too small to be identified by the in vivo connectome data (1,050 µm). A coronal image is shown in f, and a middle sagittal image is shown in g.
+3
The VHC of primates a, Left: middle sagittal slice of a FA-weighted DEC image of the marmoset brain (80 µm). Right: white arrows highlight the VHC and the area mistakenly labeled as the VHC in most atlases. b, A coronal slice of the marmoset that shows dominant left–right fiber orientation in the VHC. The bottom right shows the fiber orientation distribution image for each voxel and overlaid on the FA image, and the fiber orientation of the voxel highlighted by the white circle is presented. c, A coronal slice of the marmoset brain showing the non-VHC region (fornix area), in which fiber orientation is dominated by the anterior–posterior (DEC-green) direction. d,e, The VHC (d) and non-VHC (e) white matter in the macaque brain, which shows a relatively smaller VHC. f,g, The VHC of the human brain is too small to be identified by the in vivo connectome data (1,050 µm). A coronal image is shown in f, and a middle sagittal image is shown in g.
… 
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ResouRce
https://doi.org/10.1038/s41593-019-0575-0
1Cerebral Microcirculation Section, Laboratory of Functional and Molecular Imaging, National Institute of Neurological Disorders and Stroke, National
Institutes of Health, Bethesda, MD, USA. 2Neurophysiology Imaging Facility, National Institute of Mental Health, National Institute of Neurological
Disorders and Stroke, and National Eye Institute, National Institutes of Health, Bethesda, MD, USA. 3Laboratory of Neuroinformatics, Nencki Institute
of Experimental Biology of Polish Academy of Sciences, Warsaw, Poland. 4ARC Centre of Excellence for Integrative Brain Function, Clayton, Melbourne,
Victoria, Australia. 5Scientific and Statistical Computing Core, National Institute of Mental Health, National Institutes of Health (NIMH/NIH),
Bethesda, MD, USA. 6Neuroscience Program, Monash Biomedicine Discovery Institute, Clayton, Melbourne, Victoria, Australia. 7Section on Cognitive
Neurophysiology and Imaging, Laboratory of Neuropsychology, National Institute of Mental Health, National Institutes of Health, Bethesda, MD, USA.
8Present address: Department of Neurobiology, University of Pittsburgh Brain Institute, Pittsburgh, PA, USA. 9Present address: Section on Quantitative
Imaging and Tissue Sciences, National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, MD, USA.
*e-mail: cirongliu@gmail.com; afonso@pitt.edu
The primate brain is evolutionarily adapted to support visual
and social cognition through a large number of cortical
regions1 interconnected through axonal bundles that form
the white matter. Recent studies have demonstrated that the white
matter is not a passive passageway of neuronal communication, but
a vital component of brain plasticity and connectivity that actively
affects learning, memory and cognitive function2. Although not tra-
ditionally emphasized in brain atlases, charting these white matter
bundles is of keen interest to researchers attempting to understand
the connectional principles of the primate brain and to explain
symptoms in neurological diseases, such as stroke and multiple scle-
rosis, and in psychiatric disorders, including depression and schizo-
phrenia2. Anterograde tracing is a traditional approach used to trace
discrete axonal projections3, which can be rendered in three dimen-
sions to chart specific fiber pathways4,5, but the method cannot be
applied to create a complete, whole-brain white matter atlas. Recent
progress in diffusion-weighted MRI (dMRI) has paved a new way
to map fiber pathways and contributed to whole-brain white matter
atlases of humans and nonhuman primates6–9. Compared to tradi-
tional tracing methods, the dMRI-based atlases have the advantage
of preserving the three-dimensional (3D) fiber orientation infor-
mation across the entire brain. As digital atlases, they also provide
versatile tools to facilitate fiber reconstruction and tract-based anal-
yses10 for human and animal studies.
However, to date, dMRI atlases have a relatively coarse spatial
resolution, which limits their capacity to resolve small but essen-
tial fiber pathways known from anatomical studies. This problem
stems from the fact that dMRI data acquisition on large primate
brains faces inherent technical challenges that limit the signal-to-
noise ratio required to acquire very small voxels. For example, larger
brains require a longer scanning time, cannot fit into ultra-high-
field magnets that usually have small bores, and pose difficulties for
designing high-performance radiofrequency (RF) coils with whole-
brain coverage. An essential resolution measure is the absolute voxel
size, as opposed to the relative voxel size in proportion to overall
brain size, as many white matter structures do not scale in propor-
tion to overall brain size but remain very small even in large brains
(Fig. 1). Thus, there is much to be gained by increasing the absolute
dMRI resolution in a primate brain.
The primary aim of this study was to map white matter path-
ways in the primate brain with a higher level of precision than has
previously been possible. For this, we turned to one of the smallest
primates, the common marmoset, whose brain shares basic organi-
zational features with larger primates11–14. The small marmoset brain
allows the use of high-field MRI and stronger gradients, which is
a necessity for high-resolution dMRI15,16. Together with improve-
ments in RF coil selection and proper design of scanning protocols,
we collected dMRI data of the marmoset brain with unprecedented
spatial resolution. The data allowed us to build a fine-grained 3D
white matter atlas of the marmoset brain, which depicts many fiber
pathways that were either omitted or incorrectly described in previ-
ous MRI datasets or atlases of the primate brain. We also provide
examples of the high similarity of white matter structures across
primate species. To further extend the functionality of this atlas,
A resource for the detailed 3D mapping of white
matter pathways in the marmoset brain
Cirong Liu 1,8*, Frank Q. Ye 2, John D. Newman1,9, Diego Szczupak1,8, Xiaoguang Tian1,8,
Cecil Chern-Chyi Yen1, Piotr Majka3,4, Daniel Glen5, Marcello G. P. Rosa 4,6, David A. Leopold2,7
and Afonso C. Silva 1,8*
While the fundamental importance of the white matter in supporting neuronal communication is well known, existing publications
of primate brains do not feature a detailed description of its complex anatomy. The main barrier to achieving this is that existing
primate neuroimaging data have insufficient spatial resolution to resolve white matter pathways fully. Here we present a resource
that allows detailed descriptions of white matter structures and trajectories of fiber pathways in the marmoset brain. The resource
includes: (1) the highest-resolution diffusion-weighted MRI data available to date, which reveal white matter features not previ-
ously described; (2) a comprehensive three-dimensional white matter atlas depicting fiber pathways that were either omitted
or misidentified in previous atlases; and (3) comprehensive fiber pathway maps of cortical connections combining diffusion-
weighted MRI tractography and neuronal tracing data. The resource, which can be downloaded from marmosetbrainmapping.org,
will facilitate studies of brain connectivity and the development of tractography algorithms in the primate brain.
NATURE NEUROSCIENCE | VOL 23 | FEBRUARY 2020 | 271–280 | www.nature.com/natureneuroscience 271
Content courtesy of Springer Nature, terms of use apply. Rights reserved
... Much less is known about how dMRI parameters behave in gray matter, which is primarily composed of neuropil, a conglomeration of neurites, glial processes, cell bodies, vasculature, and other unmyelinated structures whose influence on diffusion has yet to be fully established ( Jelescu et al., 2020;Novikov et al., 2019). Gray matter also contains a proportion of thin myelinated axons that are enmeshed within the neuropil, and whose structural organization varies by anatomical region and cortical layer ( Bock et al., 2011;Braitenberg, 1962;Lewis & Van Essen, 2000;Vogt & Vogt, 1919). These diverse axon arrangements tend to be more diffuse than fiber bundles in the white matter ( Lewis & Van Essen, 2000;Vogt & Vogt, 1919), and they may affect the dynamics of diffusing water molecules differently. ...
... Gray matter also contains a proportion of thin myelinated axons that are enmeshed within the neuropil, and whose structural organization varies by anatomical region and cortical layer ( Bock et al., 2011;Braitenberg, 1962;Lewis & Van Essen, 2000;Vogt & Vogt, 1919). These diverse axon arrangements tend to be more diffuse than fiber bundles in the white matter ( Lewis & Van Essen, 2000;Vogt & Vogt, 1919), and they may affect the dynamics of diffusing water molecules differently. Moreover, the aggregate dMRI signal in a cortical voxel simultaneously reflects the influence of both neuropil and myelinated axons. ...
... The postmortem brains of two adult marmosets "case M" and "case P", both used in previous studies ( Liu et al., 2018( Liu et al., , 2020Reveley et al., 2022), were employed in this work. Both animals were scanned for multi-shelled diffusion MRI (dMRI) and for Magnetization Transfer Ratio (MTR) MRI on the same 7T Bruker preclinical scanner with a 30 cm bore and 450 mT/m gradients. ...
Diffusion kurtosis imaging, MAP-MRI and NODDI selectively track gray matter myelin density in the primate cerebral cortex
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Diffusion magnetic resonance imaging (dMRI) has been widely used to model the trajectory of myelinated fiber bundles in the white matter. Increasingly, it is also used to evaluate the microstructure of the cerebral cortex gray matter. For example, in diffusion tensor imaging (DTI) of the cortex, fractional anisotropy (FA) correlates strongly with the anisotropy of cellular anatomy, while radial diffusivity (RD) tracks the anisotropy of myelinated fibers. However, no DTI parameter shows specificity to gray matter myelin density. Here, we show that three higher-order diffusion parameters—the mean diffusion kurtosis (MK), the Neurite Density Index (NDI) from neurite orientation dispersion and density imaging (NODDI), and the Non-Gaussian (NG) parameter from mean apparent propagator (MAP)-MRI—each track the laminar and regional myelin density of the primate cerebral cortex in fine detail. We carried out ultra-high-resolution, multi-shelled dMRI in ex-vivo marmoset monkey brains. We compared the spatial mapping of the MK, NDI, and ND diffusion parameters to the cortical myelin distribution of these brains, with the latter obtained in two ways: First, using histological sections finely co-registered to the MRI, and second using magnetization transfer ratio MRI scans (MTR), an established non-diffusion method for imaging myelin density. We found that, in contrast to DTI parameters, each of these higher-order diffusion measures captured the spatial variation of myelin density in the cortex. The demonstration that diffusion parameters exhibit both sensitivity and specificity for gray matter myelin density will allow dMRI to more effectively track human disease, in which myelinated and non-myelinated tissue compartments are affected differentially.
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... Resources to support the use of the common marmoset (Callithrix jacchus) for neuroscientific inquiry have developed rapidly [1][2][3][4][5][6][7][8][9][10][11][12] , with this small New World primate species poised to inform translational gaps between rodents and humans [13][14][15][16] . One of the many practical advantages of the marmoset model is that preclinical instruments originally designed for rodent models can be ported for use in marmosets, such as small-bore MRI or PET systems, electrodes, and optical imaging setups [17][18][19][20] . ...
... One area of our collective focus has been developing radiofrequency coils for ultra-high field preclinical MRI systems, offering exquisite signal-to-noise ratio and resolution 1, [29][30][31][32] . These developments have enabled the generation of structural and functional marmoset brain atlases [3][4][5][6][9][10][11][12] and allowed for insights into where marmoset brain structure and function fit with reference to other preclinical modeling species 20,27,[33][34][35] . With clear effects of anesthesia on functional signals in the marmoset 36,37 and the advent of conducting task-based fMRI in awake-behaving marmosets, there has been prodigious bias toward engineering apparatus to support comfortable -yet motionfree -imaging in the marmoset. ...
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The use of the common marmoset (Callithrix jacchus) for neuroscientific inquiry has grown precipitously over the past two decades. Despite windfalls of grant support from funding initiatives in North America, Europe, and Asia to model human brain diseases in the marmoset, marmoset-specific apparatus are of sparse availability from commercial vendors and thus are often developed and reside within individual laboratories. Through our collective research efforts, we have designed and vetted myriad designs for awake or anesthetized magnetic resonance imaging (MRI), positron emission tomography (PET), computed tomography (CT), as well as focused ultrasound (FUS), electrophysiology, optical imaging, surgery, and behavior in marmosets across the age-span. This resource makes these designs openly available, reducing the burden of de novo development across the marmoset field. The computer-aided-design (CAD) files are publicly available through the Marmoset Brain Connectome (MBC) resource (marmosetbrainconnectome.org/apparatus) and include dozens of downloadable CAD assemblies, software and online calculators for marmoset neuroscience. In addition, we make available a variety of vetted touchscreen and task-based fMRI code and stimuli. Here, we highlight the online interface and the development and validation of a few yet unpublished resources: Software to automatically extract the head morphology of a marmoset from a CT and produce a 3D printable helmet for awake neuroimaging, and the design and validation of 8-channel and 14-channel receive arrays for imaging deep structures during anatomical and functional MRI.
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... These developments have enabled the generation of structural and functional marmoset brain atlases (C. Liu et al., 2018Liu et al., , 2020Liu et al., , 2021Majka et al., 2020;Schaeffer et al., 2022;Shimogori et al., 2018;Tian et al., 2022;Zhu et al., 2023) and allowed for insights into where marmoset brain structure and function fit with reference to other preclinical modeling species Hori, Schaeffer, Yoshida, et al., 2020;Schaeffer, Gilbert, Hori, Hayrynen, et al., 2019;Schaeffer, Hori, et al., 2020;Schaeffer, Selvanayagam, et al., 2020). With clear effects of anesthesia on functional signals in the marmoset J. V. Liu et al., 2013) and the advent of conducting task-based fMRI in awake-behaving marmosets, there has been prodigious bias toward engineering apparatus to support comfortable -yet motion-free -imaging in the marmoset. ...
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... There is growing recognition of the common marmoset's (Callithrix jacchus) potential as an invaluable animal model in neuroscience research (Miller et al., 2016;Burkart and Finkenwirth, 2015) as evidenced by efforts to create marmoset brain databases at multiple biological levels (Lin et al., 2019;Liu et al., 2020;Woodward et al., 2018;Okano et al., 2016). Marmosets provide notable advantages as research models, including their immediate relevance to humans given their genetic relatedness and shared dominant sensory modalities (Miller et al., 2016;Mitchell and Leopold, 2015), and their small size which facilitates naturalistic, freely moving studies of primate social behaviors that can be challenging with larger species like macaques. ...
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Potentiation of cortico-spinal output via targeted electrical stimulation of the motor thalamus
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  • Oct 2024
Cerebral white matter lesions prevent cortico-spinal descending inputs from effectively activating spinal motoneurons, leading to loss of motor control. However, in most cases, the damage to cortico-spinal axons is incomplete offering a potential target for therapies aimed at improving volitional muscle activation. Here we hypothesize that, by engaging direct excitatory connections to cortico-spinal motoneurons, stimulation of the motor thalamus could facilitate activation of surviving cortico-spinal fibers thereby immediately potentiating motor output. To test this hypothesis, we identify optimal thalamic targets and stimulation parameters that enhance upper-limb motor-evoked potentials and grip forces in anesthetized monkeys. This potentiation persists after white matter lesions. We replicate these results in humans during intra-operative testing. We then design a stimulation protocol that immediately improves strength and force control in a patient with a chronic white matter lesion. Our results show that electrical stimulation targeting surviving neural pathways can improve motor control after white matter lesions.
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PDF of The Marmoset Brain in Stereotaxic Coordinates
Book
Full-text available
  • Jan 2012
This is the full pdf of the Paxinos et al. 2012 atlas of the marmoset brain. This book has gone out of print, and the copyright reverted to the authors. For more resources related to the marmoset brain, visit www.marmosetbrain.org
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Anatomical and functional investigation of the marmoset default mode network
Article
Full-text available
  • Apr 2019
The default mode network (DMN) is associated with a wide range of brain functions. In humans, the DMN is marked by strong functional connectivity among three core regions: medial prefrontal cortex (mPFC), posterior parietal cortex (PPC), and the medial parietal and posterior cingulate cortex (PCC). Neuroimaging studies have shown that the DMN also exists in non-human primates, suggesting that it may be a conserved feature of the primate brain. Here, we found that, in common marmosets, the dorsolateral prefrontal cortex (dlPFC; peak at A8aD) has robust fMRI functional connectivity and reciprocal anatomical connections with the posterior DMN core regions (PPC and PCC), while the mPFC has weak connections with the posterior DMN core regions. This strong dlPFC but weak mPFC connectivity in marmoset differs markedly from the stereotypical DMN in humans. The mPFC may be involved in brain functions that are further developed in humans than in other primates.
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Macroscale cortical organization and a default-like apex transmodal network in the marmoset monkey
Article
Full-text available
  • Apr 2019
Networks of widely distributed regions populate human association cortex. One network, often called the default network, is positioned at the apex of a gradient of sequential networks that radiate outward from primary cortex. Here, extensive anatomical data made available through the Marmoset Brain Architecture Project are explored to show a homologue exists in marmoset. Results reveal that a gradient of networks extend outward from primary cortex to progressively higher-order transmodal association cortex in both frontal and temporal cortex. The apex transmodal network comprises frontopolar and rostral temporal association cortex, parahippocampal areas TH / TF, the ventral posterior midline, and lateral parietal association cortex. The positioning of this network in the gradient and its composition of areas make it a candidate homologue to the human default network. That the marmoset, a physiologically- and genetically-accessible primate, might possess a default-network-like candidate creates opportunities for study of higher cognitive and social functions.
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A high-throughput neurohistological pipeline for brain-wide mesoscale connectivity mapping of the common marmoset
Article
Full-text available
  • Feb 2019
  • eLife
Understanding the connectivity architecture of entire vertebrate brains is a fundamental but difficult task. Here we present an integrated neuro-histological pipeline as well as a grid-based tracer injection strategy for systematic mesoscale connectivity mapping in the common Marmoset (Callithrix jacchus). Individual brains are sectioned into ~1700 20µm sections using the tape transfer technique, permitting high quality 3D reconstruction of a series of histochemical stains (Nissl, myelin) interleaved with tracer labelled sections. Systematic in-vivo MRI of the individual animals facilitates injection placement into reference-atlas defined anatomical compartments. Further, combining the resulting 3D volumes, containing informative cytoarchitectonic markers, with in-vivo and ex-vivo MRI, and using an integrated computational pipeline, we are able to accurately map individual brains into a common reference atlas despite the significant individual variation. This approach will facilitate the systematic assembly of a mesoscale connectivity matrix together with unprecedented 3D reconstructions of brain-wide projection patterns in a primate brain.
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Large-scale comparative neuroimaging: Where are we and what do we need?
Article
Full-text available
  • Dec 2018
  • CORTEX
Neuroimaging has a lot to offer comparative neuroscience. Although invasive “gold standard” techniques have a better spatial resolution, neuroimaging allows fast, whole-brain, repeatable, and multi-modal measurements of structure and function in living animals and post-mortem tissue. In the past years, comparative neuroimaging has increased in popularity. However, we argue that its most significant potential lies in its ability to collect large-scale datasets of many species to investigate principles of variability in brain organisation across whole orders of species—an ambition that is presently unfulfilled but achievable. We briefly review the current state of the field and explore what the current obstacles to such an approach are. We propose some calls to action.
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Whole mouse brain structural connectomics using magnetic resonance histology
Article
Full-text available
  • Dec 2018
  • BRAIN STRUCT FUNCT
Diffusion tensor histology holds great promise for quantitative characterization of structural connectivity in mouse models of neurological and psychiatric conditions. There has been extensive study in both the clinical and preclinical domains on the complex tradeoffs between the spatial resolution, the number of samples in diffusion q-space, scan time, and the reliability of the resultant data. We describe here a method for accelerating the acquisition of diffusion MRI data to support quantitative connectivity measurements in the whole mouse brain using compressed sensing (CS). The use of CS allows substantial increase in spatial resolution and/or reduction in scan time. Compared to the fully sampled results at the same scan time, the subtle anatomical details of the brain, such as cortical layers, dentate gyrus, and cerebellum, were better visualized using CS due to the higher spatial resolution. Compared to the fully sampled results at the same spatial resolution, the scalar diffusion metrics, including fractional anisotropy (FA) and mean diffusivity (MD), showed consistently low error across the whole brain (< 6.0%) even with 8.0 times acceleration. The node properties of connectivity (strength, cluster coefficient, eigenvector centrality, and local efficiency) demonstrated correlation of better than 95.0% between accelerated and fully sampled connectomes. The acceleration will enable routine application of this technology to a wide range of mouse models of neurologic diseases.
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Spatiotemporal distribution of fibrinogen in marmoset and human inflammatory demyelination
Article
Full-text available
  • Apr 2018
  • BRAIN
Multiple sclerosis is an inflammatory demyelinating disease of the central nervous system. Although it has been extensively studied, the proximate trigger of the immune response remains uncertain. Experimental autoimmune encephalomyelitis in the common marmoset recapitulates many radiological and pathological features of focal multiple sclerosis lesions in the cerebral white matter, unlike traditional experimental autoimmune encephalomyelitis in rodents. This provides an opportunity to investigate how lesions form as well as the relative timing of factors involved in lesion pathogenesis, especially during early stages of the disease. We used MRI to track experimental autoimmune encephalomyelitis lesions in vivo to determine their age, stage of development, and location, and we assessed the corresponding histopathology post-mortem. We focused on the plasma protein fibrinogen-a marker for blood-brain barrier leakage that has also been linked to a pathogenic role in inflammatory demyelinating lesion development. We show that fibrinogen has a specific spatiotemporal deposition pattern, apparently deriving from the central vein in early experimental autoimmune encephalomyelitis lesions <6 weeks old, and preceding both demyelination and visible gadolinium enhancement on MRI. Thus, fibrinogen leakage is one of the earliest detectable events in lesion pathogenesis. In slightly older lesions, fibrinogen is found inside microglia/macrophages, suggesting rapid phagocytosis. Quantification demonstrates positive correlation of fibrinogen deposition with accumulation of inflammatory cells, including microglia/macrophages and T cells. The peak of fibrinogen deposition coincides with the onset of demyelination and axonal loss. In samples from chronic multiple sclerosis cases, fibrinogen was found at the edge of chronic active lesions, which have ongoing demyelination and inflammation, but not in inactive lesions, suggesting that fibrinogen may play a role in sustained inflammation even in the chronic setting. In summary, our data support the notion that fibrinogen is a key player in the early pathogenesis, as well as sustained inflammation, of inflammatory demyelinating lesions.
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Functional Segmentation of the Anterior Limb of the Internal Capsule: Linking White Matter Abnormalities to Specific Connections
Article
Full-text available
  • Jan 2018
The anterior limb of the internal capsule (ALIC) carries thalamic and brainstem fibers from prefrontal cortical regions that are associated with different aspects of emotion, motivation, cognition processing, and decision-making. This large fiber bundle is abnormal in several psychiatric illnesses and a major target for deep brain stimulation. Yet, we have very little information about where specific prefrontal fibers travel within the bundle. Using a combination of tracing studies and diffusionMRIin malenonhumanprimates, as well as diffusion MRI in male and female human subjects, we segmented the human ALIC into five regions based on the positions of axons from different cortical regions within the capsule. Fractional anisotropy (FA) abnormalities in patients with bipolar disorder were detected whenFAwas averaged in the ALIC segment that carries ventrolateral prefrontal cortical connections. Together, the results set the stage for linking abnormalities within the ALIC to specific connections and demonstrate the utility of applying connectivity profiles of large white matter bundles based on animal anatomic studies to human connections and associating disease abnormalities in those pathways with specific connections. The ability to functionally segment large white matter bundles into their components begins a new era of refining how we think about white matter organization and use that information in understanding abnormalities.
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High-Expanding Regions in Primate Cortical Brain Evolution Support Supramodal Cognitive Flexibility
Article
  • Oct 2018
  • CEREB CORTEX
Primate cortical evolution has been characterized by massive and disproportionate expansion of a set of specific regions in the neocortex. The associated increase in neocortical neurons comes with a high metabolic cost, thus the functions served by these regions must have conferred significant evolutionary advantage. In the present series of analyses, we show that evolutionary high-expanding cortex - as estimated from patterns of surface growth from several primate species - shares functional connections with different brain networks in a context-dependent manner. Specifically, we demonstrate that high-expanding cortex is characterized by high internetwork functional connectivity; is recruited flexibly over many different cognitive tasks; and changes its functional coupling pattern between rest and a multimodal task-state. The capacity of high-expanding cortex to connect flexibly with various specialized brain networks depending on particular cognitive requirements suggests that its selective growth and sustainment in evolution may have been linked to an involvement in supramodal cognition. In accordance with an evolutionary-developmental view, we find that this observed ability of high-expanding regions - to flexibly modulate functional connections as a function of cognitive state - emerges gradually through childhood, with a prolonged developmental trajectory plateauing in young adulthood.
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Parcellating Cerebral Cortex: How Invasive Animal Studies Inform Noninvasive Mapmaking in Humans
Article
  • Aug 2018
The cerebral cortex in mammals contains a mosaic of cortical areas that differ in function, architecture, connectivity, and/or topographic organization. A combination of local connectivity (within-area microcircuitry) and long-distance (between-area) connectivity enables each area to perform a unique set of computations. Some areas also have characteristic within-area mesoscale organization, reflecting specialized representations of distinct types of information. Cortical areas interact with one another to form functional networks that mediate behavior, and each area may be a part of multiple, partially overlapping networks. Given their importance to the understanding of brain organization, mapping cortical areas across species is a major objective of systems neuroscience and has been a century-long challenge. Here, we review recent progress in multi-modal mapping of mouse and nonhuman primate cortex, mainly using invasive experimental methods. These studies also provide a neuroanatomical foundation for mapping human cerebral cortex using noninvasive neuroimaging, including a new map of human cortical areas that we generated using a semiautomated analysis of high-quality, multimodal neuroimaging data. We contrast our semiautomated approach to human multimodal cortical mapping with various extant fully automated human brain parcellations that are based on only a single imaging modality and offer suggestions on how to best advance the noninvasive brain parcellation field. We discuss the limitations as well as the strengths of current noninvasive methods of mapping brain function, architecture, connectivity, and topography and of current approaches to mapping the brain's functional networks.
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