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A Predictive Structural Model of the Primate Connectome

Sarah F. Beul, Helen Barbas, Claus C. Hilgetag

Scientific Reports · 2017 · CC BY

doi:10.1038/srep43176

Abstract

Anatomical connectivity imposes strong constraints on brain function, but there is no general agreement about principles that govern its organization. Based on extensive quantitative data, we tested the power of three factors to predict connections of the primate cerebral cortex: architectonic similarity (structural model), spatial proximity (distance model) and thickness similarity (thickness model). Architectonic similarity showed the strongest and most consistent influence on connection features. This parameter was strongly associated with the presence or absence of inter-areal connections and when integrated with spatial distance, the factor allowed predicting the existence of projections with very high accuracy. Moreover, architectonic similarity was strongly related to the laminar pattern of projection origins, and the absolute number of cortical connections of an area. By contrast, cortical thickness similarity and distance were not systematically related to connection features. These findings suggest that cortical architecture provides a general organizing principle for connections in the primate brain, providing further support for the well-corroborated structural model.

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References 89

  1. 1.

    Park H.-J. & Friston K. J. Structural and Functional Brain Networks: From Connections to Cognition. Science 342, 1238411 (2013 ).

    Not in our library10.1126/science.1238411

  2. 2.

    Rockland K. S. & Pandya D. N. Laminar origins and terminations of cortical connections of the occipital lobe in the rhesus monkey. Brain Res. 179, 3–20 (1979 ).

    Not in our library10.1016/0006-8993(79)90485-2

  3. 3.

    Pandya D. N. & Yeterian E. H. In Association and auditory cortices (eds Peters A. & Jones E. G. ) 4, 3–61 (Plenum Press, 1985 ).

    Not in our library

  4. 4.

    Felleman D. J. & Van Essen D. C. Distributed hierarchical processing in the primate cerebral cortex. Cereb. Cortex 1, 1–47 (1991 ).

    Not in our library10.1093/cercor/1.1.1-a

  5. 5.

    Hilgetag C. C., O’Neill M. A. & Young M. P. Indeterminate organization of the visual system. Science 271, 776–777 (1996 ).

    Not in our library10.1126/science.271.5250.776

  6. 6.

    Bullmore E. T. & Sporns O. Complex brain networks: graph theoretical analysis of structural and functional systems. Nat. Rev. Neurosci. 10, 186–198 (2009 ).

    Not in our library10.1038/nrn2575

  7. 7.

    Colizza V., Flammini A., Serrano M. A. & Vespignani A. Detecting rich-club ordering in complex networks. Nat. Phys. 2, 110–115 (2006 ).

    Not in our library

  8. 8.

    Barbas H. Pattern in the laminar origin of corticocortical connections. J. Comp. Neurol. 252, 415–422 (1986 ).

    Not in our library10.1002/cne.902520310

  9. 9.

    Barbas H. & Rempel-Clower N. L. Cortical structure predicts the pattern of corticocortical connections. Cereb. Cortex 7, 635–646 (1997 ).

    Not in our library10.1093/cercor/7.7.635

  10. 10.

    Sanides F. In The Primate Brain (eds Noback C. R. & Montagna W. ) 137–208 (Appleton-Century-Crofts, 1970 ).

    Not in our library

  11. 11.

    Pandya D. N., Seltzer B. & Barbas H. In Comparative Primate Biology, Vol.4, Neurosciences (eds Steklis H. & Erwin J. ) 39–80 (Alan R. Liss, 1988 ).

    Not in our library

  12. 12.

    Barbas H. General Cortical and Special Prefrontal Connections: Principles from Structure to Function. Annu. Rev. Neurosci. 38, 269–289 (2015 ).

    Not in our library10.1146/annurev-neuro-071714-033936

  13. 13.

    Barbas H. & Pandya D. N. Architecture and intrinsic connections of the prefrontal cortex in the rhesus monkey. J. Comp. Neurol. 286, 353–375 (1989 ).

    Not in our library10.1002/cne.902860306

  14. 14.

    Dombrowski S. M., Hilgetag C. C. & Barbas H. Quantitative Architecture Distinguishes Prefrontal Cortical Systems in the Rhesus Monkey. Cereb. Cortex 11, 975–988 (2001 ).

    Not in our library10.1093/cercor/11.10.975

  15. 15.

    von Economo C. Zellaufbau der Grosshirnrinde des Menschen. (Springer, 1927 ).

    Not in our library

  16. 16.

    von Economo C. Cellular Structure of the Human Cerebral Cortex. (Karger Medical and Scientific Publishers, 2009 ).

    Not in our library

  17. 17.

    Zilles K. & Amunts K. Segregation and Wiring in the Brain. Science 335, 1582–1584 (2012 ).

    Not in our library10.1126/science.1221366

  18. 18.

    Barbas H., Hilgetag C. C., Saha S., Dermon C. R. & Suski J. L. Parallel organization of contralateral and ipsilateral prefrontal cortical projections in the rhesus monkey. BMC Neurosci. 6, 32 (2005 ).

    Not in our library10.1186/1471-2202-6-32

  19. 19.

    Hilgetag C. C. & Grant S. Cytoarchitectural differences are a key determinant of laminar projection origins in the visual cortex. NeuroImage 51, 1006–1017 (2010 ).

    Not in our library10.1016/j.neuroimage.2010.03.006

  20. 20.

    Beul S. F., Grant S. & Hilgetag C. C. A predictive model of the cat cortical connectome based on cytoarchitecture and distance. Brain Struct. Funct. 220, 3167–3184 (2015 ).

    Not in our library10.1007/s00429-014-0849-y

  21. 21.

    Young M. P. Objective analysis of the topological organization of the primate cortical visual system. Nature 358, 152–155 (1992 ).

    Not in our library10.1038/358152a0

  22. 22.

    Klyachko V. A. & Stevens C. F. Connectivity optimization and the positioning of cortical areas. Proc. Natl. Acad. Sci. 100, 7937–7941 (2003 ).

    Not in our library10.1073/pnas.0932745100

  23. 23.

    Markov N. T.. The role of long-range connections on the specificity of the macaque interareal cortical network. Proc. Natl. Acad. Sci. 110, 5187–5192 (2013 ).

    Not in our library10.1073/pnas.1218972110

  24. 24.

    Douglas R. J. & Martin K. A. C. Mapping the Matrix: The Ways of Neocortex. Neuron 56, 226–238 (2007 ).

    Not in our library10.1016/j.neuron.2007.10.017

  25. 25.

    Ercsey-Ravasz M.. A Predictive Network Model of Cerebral Cortical Connectivity Based on a Distance Rule. Neuron 80, 184–197 (2013 ).

    Not in our library10.1016/j.neuron.2013.07.036

  26. 26.

    Salin P. A. & Bullier J. Corticocortical connections in the visual system: structure and function. Physiol. Rev. 75, 107–154 (1995 ).

    Not in our library10.1152/physrev.1995.75.1.107

  27. 27.

    Cullen T. J.. Anomalies of asymmetry of pyramidal cell density and structure in dorsolateral prefrontal cortex in schizophrenia. Br. J. Psychiatry 188, 26–31 (2006 ).

    Not in our library10.1192/bjp.bp.104.008169

  28. 28.

    la Fougère C.. Where in-vivo imaging meets cytoarchitectonics: The relationship between cortical thickness and neuronal density measured with high-resolution [18F]flumazenil-PET. NeuroImage 56, 951–960 (2011 ).

    Not in our library10.1016/j.neuroimage.2010.11.015

  29. 29.

    Narr K. L.. Mapping Cortical Thickness and Gray Matter Concentration in First Episode Schizophrenia. Cereb. Cortex 15, 708–719 (2005 ).

    Not in our library10.1093/cercor/bhh172

  30. 30.

    Lerch J. P.. Mapping anatomical correlations across cerebral cortex (MACACC) using cortical thickness from MRI. NeuroImage 31, 993–1003 (2006 ).

    Not in our library10.1016/j.neuroimage.2006.01.042

  31. 31.

    He Y., Chen Z. J. & Evans A. C. Small-World Anatomical Networks in the Human Brain Revealed by Cortical Thickness from MRI. Cereb. Cortex 17, 2407–2419 (2007 ).

    Not in our library10.1093/cercor/bhl149

  32. 32.

    Gong G., He Y., Chen Z. J. & Evans A. C. Convergence and divergence of thickness correlations with diffusion connections across the human cerebral cortex. NeuroImage 59, 1239–1248 (2012 ).

    Not in our library10.1016/j.neuroimage.2011.08.017

  33. 33.

    Chen Z. J., He Y., Rosa-Neto P., Germann J. & Evans A. C. Revealing Modular Architecture of Human Brain Structural Networks by Using Cortical Thickness from MRI. Cereb. Cortex 18, 2374–2381 (2008 ).

    Not in our library10.1093/cercor/bhn003

  34. 34.

    Chen Z. J., He Y., Rosa-Neto P., Gong G. & Evans A. C. Age-related alterations in the modular organization of structural cortical network by using cortical thickness from MRI. NeuroImage 56, 235–245 (2011 ).

    Not in our library10.1016/j.neuroimage.2011.01.010

  35. 35.

    Bernhardt B. C., Klimecki O. M., Leiberg S. & Singer T. Structural Covariance Networks of the Dorsal Anterior Insula Predict Females’ Individual Differences in Empathic Responding. Cereb. Cortex 24, 2189–2198 (2014 ).

    Not in our library10.1093/cercor/bht072

  36. 36.

    Tewarie P.. Disruption of structural and functional networks in long-standing multiple sclerosis. Hum. Brain Mapp. doi: (2014 ).

    Not in our library10.1002/hbm.22596

  37. 37.

    Evans A. C. Networks of anatomical covariance. NeuroImage 80, 489–504 (2013 ).

    Not in our library10.1016/j.neuroimage.2013.05.054

  38. 38.

    Markov N. T.. A Weighted and Directed Interareal Connectivity Matrix for Macaque Cerebral Cortex. Cereb. Cortex 24, 17–36 (2014 ).

    Not in our library10.1093/cercor/bhs270

  39. 39.
  40. 40.

    Hilgetag C. C., Burns G. A. P. C., O’Neill M. A., Scannell J. W. & Young M. P. Anatomical connectivity defines the organization of clusters of cortical areas in the macaque monkey and the cat. Philos. Trans. R. Soc. B Biol. Sci. 355, 91–110 (2000 ).

    Not in our library10.1098/rstb.2000.0551

All 89 references

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