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Mapping putative hubs in human, chimpanzee and rhesus macaque connectomes via diffusion tractography
Open accessAbstract
Mapping anatomical brain networks with graph-theoretic analysis of diffusion tractography has recently gained popularity, because of its presumed value in understanding brain function. However, this approach has seldom been used to compare brain connectomes across species, which may provide insights into brain evolution. Here, we employed a data-driven approach to compare interregional brain connections across three primate species: 1) the intensively studied rhesus macaque, 2) our closest living primate relative, the chimpanzee, and 3) humans. Specifically, we first used random parcellations and surface-based probabilistic diffusion tractography to derive the brain networks of the three species under various network densities and resolutions. We then compared the characteristics of the networks using graph-theoretic measures. In rhesus macaques, our tractography-defined hubs showed reasonable overlap with hubs previously identified using anterograde and retrograde tracer data. Across all three species, hubs were largely symmetric in the two hemispheres and were consistently identified in medial parietal, insular, retrosplenial cingulate and ventrolateral prefrontal cortices, suggesting a conserved structural architecture within these regions. However, species differences were observed in the inferior parietal cortex, polar and medial prefrontal cortices. The potential significance of these interspecies differences is discussed.
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A default mode of brain function
Raichle, M. E., MacLeod, A. M., Snyder, A. Z., Powers, W. J., Gusnard, D. A., & Shulman, G. L. (2001) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.98.2.676 · Cited by 12,190
Complex brain networks: graph theoretical analysis of structural and functional systems
Bullmore, E., & Sporns, O. (2009) · Nature Reviews Neuroscience · doi:10.1038/nrn2575 · Cited by 11,820
Complex network measures of brain connectivity: Uses and interpretations
Rubinov, M., & Sporns, O. (2010) · NeuroImage · doi:10.1016/j.neuroimage.2009.10.003 · Cited by 11,522
Fast robust automated brain extraction
Smith, S. M. (2002) · Human Brain Mapping · doi:10.1002/hbm.10062 · Cited by 10,496
Distributed hierarchical processing in the primate cerebral cortex
Felleman, D. J., & Van Essen, D. C. (1991) · Cerebral Cortex · doi:10.1093/cercor/1.1.1 · Cited by 7,783
Zhang, Y., Brady, M., & Smith, S. M. (2001) · IEEE Transactions on Medical Imaging · doi:10.1109/42.906424 · Cited by 7,628
Dissociable intrinsic connectivity networks for salience processing and executive control
Seeley, W. W., Menon, V., Schatzberg, A. F., Keller, J., Glover, G. H., Kenna, H., Reiss, A. L., & Greicius, M. D. (2007) · The Journal of Neuroscience · doi:10.1523/jneurosci.5587-06.2007 · Cited by 7,426
Functional connectivity in the resting brain: a network analysis of the default mode hypothesis
Greicius, M. D., Krasnow, B., Reiss, A. L., & Menon, V. (2003) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0135058100 · Cited by 6,358
How do you feel? Interoception: The sense of the physiological condition of the body
Craig, A. D. (2002) · Nature Reviews Neuroscience · doi:10.1038/nrn894 · Cited by 6,006
Saliency, switching, attention and control: a network model of insula function
Menon, V., & Uddin, L. Q. (2010) · Brain Structure and Function · doi:10.1007/s00429-010-0262-0 · Cited by 5,592
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Research works printed but not linked: 2
- Brodmann, 1913, Neue Forchungsergebnisse der Grosshirnrindeanatomische mit besonderer Berucksichtung anthropologischer Fragen, Gesselch. Deuts. Naturf. Artze., 85, 200
- Li, 2011, The effects of connection reconstruction method on the interregional connectivity of brain networks via diffusion tractography, Hum. Brain Mapp.
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Ardesch, D. J. (2023) · doi:10.5463/thesis.22
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Cohen, D., & Johnstone, B. (2024) · Journal of Cognition and Culture · doi:10.1163/15685373-12340180
Tura, A. (2024) · eDiss (Georg-August-Universität Göttingen) · doi:10.53846/goediss-10519
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Karimi, D., Li, B., Taymourtash, A., Jaimes, C. E., Grant, P. E., & Warfield, S. K. (2026) · Human Brain Mapping · doi:10.1002/hbm.70609
The primate brain connectivity bauplan and human-specific variations
Mars, R. B., Bryant, K., Karadachka, K., Tang, W., Zhou, J., Bijanki, K. R., Palomero‐Gallagher, N., & Heibronner, S. R. (2025) · Evolution of Nervous Systems · doi:10.1016/b978-0-443-27380-3.00036-1
Chauvel, M. (2023) · theses.fr (ABES) · doi:10.70675/243d3998zd318z4ce4z8d5cz99f877a66861 · Cited by 1
Hecht, E. E., & Barton, S. A. (2026) · Springer eBooks · doi:10.1007/978-3-032-31515-1_9
Kokubun, K., Nemoto, K., & Yamakawa, Y. (2026) · Brain Structure and Function · doi:10.1007/s00429-026-03205-6
Metadata
- Authors
- Li, L., Hu, X., Preuss, T. M., Glasser, M. F., Damen, F. W., Qiu, Y., & Rilling, J.
- Affiliations
- Georgia Institute of Technology (US)
- Emory University (US)
- Washington University in St. Louis (US)
- Corresponding author
- Rilling, James
- ORCID
- Venue
- NeuroImage
- Publisher
- Elsevier BV
- Published
- 2013-10
- Volume
- 80
- Pages
- 462-474
- ISSN
- 1053-8119 (ISSN-L)
- PMC
- PMC3720835
- OpenAlex
- W1979383653
- Cited by
- 109
- References
- 96
- Citations by year
- 2026: 3 · 2025: 4 · 2024: 9 · 2023: 6 · 2022: 4 · 2021: 6 · 2020: 10 · 2019: 11 · 2018: 13 · 2017: 11 · 2016: 10 · 2015: 6 · 2014: 12 · 2013: 4
- FWCI
- 8.28
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- NeuroImage (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- Funders
- NIH (5P01 AG026423-03, P50-MH100029)
- National Center for Research Resources (P51RR165)
- Office of Research Infrastructure Programs (P51OD11132)
- Topics
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced Neuroimaging Techniques and Applications
- Life Sciences › Neuroscience › Cognitive Neuroscience › Functional Brain Connectivity Studies
- Physical Sciences › Physics and Astronomy › Statistical and Nonlinear Physics › Complex Network Analysis Techniques
- Keywords
- brain connectome, diffusion tractography, primate brain evolution, human-brain comparison, chimpanzees, rhesus monkeys, probabilistic tractography, hemispheric symmetry, prefrontal cortex, parietal cortex, insula, retrosplenial cortex
- MeSH terms
- Animals, Brain, Pan troglodytes, Humans, Macaca mulatta, Models, Anatomic, Models, Neurological, Nerve Fibers, Myelinated, Nerve Net, Species Specificity, Diffusion Tensor Imaging, Connectome
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