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 is a preview of subscription content, access via your institution
Open Access articles citing this article.
Nature Communications Open Access 21 September 2022
Brain Structure and Function Open Access 03 February 2022
Open access resource for cellular-resolution analyses of corticocortical connectivity in the marmoset monkey
Nature Communications Open Access 28 February 2020
Subscribe to Nature+
Get immediate online access to the entire Nature family of 50+ journals
Subscribe to Journal
Get full journal access for 1 year
only $8.25 per issue
All prices are NET prices.
VAT will be added later in the checkout.
Tax calculation will be finalised during checkout.
Get time limited or full article access on ReadCube.
All prices are NET prices.
The resource presented here includes (1) dMRI data with the highest resolution available to date revealing white matter features not previously described, (2) a comprehensive 3D 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 dMRI tractography and neuronal tracing data. The raw data and all other features of the resource can be downloaded in NIFTI format from our website (marmosetbrainmapping.org).
Van Essen, D. C. & Glasser, M. F. Parcellating cerebral cortex: how invasive animal studies inform noninvasive mapmaking in humans. Neuron 99, 640–663 (2018).
Fields, R. D. White matter in learning, cognition and psychiatric disorders. Trends Neurosci. 31, 361–370 (2008).
Schmahmann, J. & Pandya, D. Fiber Pathways of the Brain (Oxford Univ. Press, 2009).
Lehman, J. F., Greenberg, B. D., McIntyre, C. C., Rasmussen, S. A. & Haber, S. N. Rules ventral prefrontal cortical axons use to reach their targets: implications for diffusion tensor imaging tractography and deep brain stimulation for psychiatric illness. J. Neurosci. 31, 10392–10402 (2011).
Safadi, Z. et al. Functional segmentation of the anterior limb of the internal capsule: linking white matter abnormalities to specific connections. J. Neurosci. 38, 2106–2117 (2018).
Calabrese, E. et al. A diffusion tensor MRI atlas of the postmortem rhesus macaque brain. NeuroImage 117, 408–416 (2015).
Zakszewski, E., Adluru, N., Tromp, D. P., Kalin, N. & Alexander, A. L. A diffusion-tensor-based white matter atlas for rhesus macaques. PLoS One 9, e107398 (2014).
Mori, S., Wakana, S., Van Zijl, P. C. & Nagae-Poetscher, L. MRI Atlas of Human White Matter (Elsevier, 2005).
Alexander, A. L., Lee, J. E., Lazar, M. & Field, A. S. Diffusion tensor imaging of the brain. Neurotherapeutics 4, 316–329 (2007).
Basser, P. J., Pajevic, S., Pierpaoli, C., Duda, J. & Aldroubi, A. In vivo fiber tractography using DT‐MRI data. Magn. Reson. Med. 44, 625–632 (2000).
Belcher, A. M. et al. Large-scale brain networks in the awake, truly resting marmoset monkey. J. Neurosci. 33, 16796–16804 (2013).
Liu, C. et al. Anatomical and functional investigation of the marmoset default mode network. Nat. Commun. 10, 1975 (2019).
Ghahremani, M., Hutchison, R. M., Menon, R. S. & Everling, S. Frontoparietal functional connectivity in the common marmoset. Cereb. Cortex 27, 3890–3905 (2016).
Buckner, R. L. & Margulies, D. S. Macroscale cortical organization and a default-like apex transmodal network in the marmoset monkey. Nat. Commun. 10, 1976 (2019).
Silva, A. C. Anatomical and functional neuroimaging in awake, behaving marmosets. Dev. Neurobiol. 77, 373–389 (2017).
Liu, C. et al. A digital 3D atlas of the marmoset brain based on multi-modal MRI. NeuroImage 169, 106–116 (2018).
Majka, P. et al. Towards a comprehensive atlas of cortical connections in a primate brain: mapping tracer injection studies of the common marmoset into a reference digital template. J. Comp. Neurol. 524, 2161–2181 (2016).
Caravan, P. Strategies for increasing the sensitivity of gadolinium based MRI contrast agents. Chem. Soc. Rev. 35, 512–523 (2006).
Thomas, C. et al. Anatomical accuracy of brain connections derived from diffusion MRI tractography is inherently limited. Proc. Natl Acad. Sci. USA 111, 16574–16579 (2014).
Reveley, C. et al. Superficial white matter fiber systems impede detection of long-range cortical connections in diffusion MR tractography. Proc. Natl Acad. Sci. USA 112, E2820–E2828 (2015).
Vu, A. T. et al. High resolution whole brain diffusion imaging at 7T for the human connectome project. NeuroImage 122, 318–331 (2015).
Pajevic, S. & Pierpaoli, C. Color schemes to represent the orientation of anisotropic tissues from diffusion tensor data: application to white matter fiber tract mapping in the human brain. Magn. Reson. Med. 42, 526–540 (1999).
Forkel, S. J., Mahmood, S., Vergani, F. & Catani, M. The white matter of the human cerebrum: part I the occipital lobe by Heinrich Sachs. Cortex 62, 182–202 (2015).
Dejerine, J. & Dejerine-Klumpke, A. Anatomie des Centres Nerveux (Rueff, 1895).
Takemura, H. et al. Occipital white matter tracts in human and macaque. Cereb. Cortex 27, 3346–3359 (2017).
Yeatman, J. D. et al. The vertical occipital fasciculus: a century of controversy resolved by in vivo measurements. Proc. Natl Acad. Sci. USA 111, E5214–E5223 (2014).
Yu, H. H., Chaplin, T. A. & Rosa, M. G. Representation of central and peripheral vision in the primate cerebral cortex: insights from studies of the marmoset brain. Neurosci. Res. 93, 47–61 (2015).
Jeffs, J., Ichida, J. M., Federer, F. & Angelucci, A. Anatomical evidence for classical and extra-classical receptive field completion across the discontinuous horizontal meridian representation of primate area V2. Cereb. Cortex 19, 963–981 (2009).
Lee, N. J. et al. Spatiotemporal distribution of fibrinogen in marmoset and human inflammatory demyelination. Brain 141, 1637–1649 (2018).
de Schotten, M. T., Croxson, P. L. & Mars, R. B. Large-scale comparative neuroimaging: where are we and what do we need? Cortex 118, 188–202 (2018).
Lin, M. K. et al. A high-throughput neurohistological pipeline for brain-wide mesoscale connectivity mapping of the common marmoset. eLife 8, e40042 (2019).
Maier-Hein, K. H. et al. The challenge of mapping the human connectome based on diffusion tractography. Nat. Commun. 8, 1349 (2017).
Jbabdi, S., Sotiropoulos, S. N., Haber, S. N., Van Essen, D. C. & Behrens, T. E. Measuring macroscopic brain connections in vivo. Nat. Neurosci. 18, 1546–1555 (2015).
Petrides, M. & Pandya, D. N. Efferent association pathways from the rostral prefrontal cortex in the macaque monkey. J. Neurosci. 27, 11573–11586 (2007).
Chaplin, T. A., Yu, H. H., Soares, J. G., Gattass, R. & Rosa, M. G. A conserved pattern of differential expansion of cortical areas in simian primates. J. Neurosci. 33, 15120–15125 (2013).
Sneve, M. H. et al. High-expanding regions in primate cortical brain evolution support supramodal cognitive flexibility. Cereb. Cortex 29, 3891–3901 (2018).
Setsompop, K. et al. Improving diffusion MRI using simultaneous multi-slice echo planar imaging. NeuroImage 63, 569–580 (2012).
Wang, N. et al. Whole mouse brain structural connectomics using magnetic resonance histology. Brain Struct. Funct. 223, 4323–4335 (2018).
Seidlitz, J. et al. A population MRI brain template and analysis tools for the macaque. NeuroImage 170, 121–131 (2018).
Fonov, V. et al. Unbiased average age-appropriate atlases for pediatric studies. NeuroImage 54, 313–327 (2011).
Paxinos, G., Watson, C., Petrides, M., Rosa, M. & Tokuno, H. The Marmoset Brain in Stereotaxic Coordinates (Elsevier Academic Press, 2012).
Hardman, C. D. & Ashwell, K. W. Stereotaxic and Chemoarchitectural Atlas of the Brain of the Common Marmoset (Callithrix jacchus) (CRC Press, 2012).
Cheng, J., Shen, D., Yap, P.-T. & Basser, P. J. Single-and multiple-shell uniform sampling schemes for diffusion MRI using spherical codes. IEEE Trans. Med. Imaging 37, 185–199 (2018).
Veraart, J. et al. Denoising of diffusion MRI using random matrix theory. NeuroImage 142, 394–406 (2016).
Jenkinson, M., Beckmann, C. F., Behrens, T. E., Woolrich, M. W. & Smith, S. M. FSL. NeuroImage 62, 782–790 (2012).
Pierpaoli, C. et al. TORTOISE: an integrated software package for processing of diffusion MRI data. In Proc. 18th Scientific Meeting of the International Society for Magnetic Resonance in Medicine (ISMRM) http://archive.ismrm.org/2010/1597.html (2010).
Basser, P. J. & Pierpaoli, C. Microstructural and physiological features of tissues elucidated by quantitative-diffusion-tensor MRI. J. Magn. Reson. B 111, 209–219 (1996).
Basser, P. J., Mattiello, J. & LeBihan, D. MR diffusion tensor spectroscopy and imaging. Biophys. J. 66, 259–267 (1994).
Tournier, J. D., Calamante, F. & Connelly, A. MRtrix: diffusion tractography in crossing fiber regions. Int. J. Imaging Syst. 22, 53–66 (2012).
Jeurissen, B., Tournier, J. D., Dhollander, T., Connelly, A. & Sijbers, J. Multi-tissue constrained spherical deconvolution for improved analysis of multi-shell diffusion MRI data. NeuroImage 103, 411–426 (2014).
Dhollander, T., Smith, R. E., Tournier, J.-D., Jeurissen, B. & Connelly, A. Time to move on: an FOD-based DEC map to replace DTI’s trademark DEC FA. NeuroImage 59, 3976–3994 (2012).
Avants, B. B., Tustison, N. & Song, G. Advanced normalization tools (ANTS). Insight J. 2, 1–35 (2009).
Cox, R. W. AFNI: software for analysis and visualization of functional magnetic resonance neuroimages. Comput. Biomed. Res. 29, 162–173 (1996).
We thank the Scientific and Statistical Computing Core of the NIMH Intramural Research Program for their support of the software AFNI and thank the NIH Fellows Editorial Board and the NIH library for language-editing services. We also thank J. Guy for providing the optimized T2* sequence. This work utilized the computational resources of the NIH High Performing Computation Biowulf cluster (hpc.nih.gov). This research was supported by the Intramural Research Program of the NIH, NINDS (ZIA NS003041), including the Neurophysiology Imaging Facility Core (NIMH, NINDS, NEI, ZIC MH002899). The neuronal tracing data are from the Australian Research Council (DP110101200, DP140101968 and CE140100007) and an International Neuroinformatics Coordinating Facility Seed Funding Grant.
The authors declare no competing interests.
Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
About this article
Cite this article
Liu, C., Ye, F.Q., Newman, J.D. et al. A resource for the detailed 3D mapping of white matter pathways in the marmoset brain. Nat Neurosci 23, 271–280 (2020). https://doi.org/10.1038/s41593-019-0575-0
Nature Communications (2022)
Brain Structure and Function (2022)
Brain Structure and Function (2022)
Nature Biotechnology (2021)
Lab Animal (2020)