What Makes The Prefrontal Cortex So Appealing in the Era of Brain Imaging? A Network Analytical Perspective


  1. 1.

    Achard, S., Salvador, R., Whitcher, B., Suckling, J., Bullmore, E. (2006) A resilient, low-frequency, small-world human brain functional network with highly connected association cortical hubs. J. Neurosci. 26, 63–72.

    CAS  Article  Google Scholar 

  2. 2.

    Averbeck, B.B., Seo, M. (2008) The statistical neuroanatomy of frontal networks in the macaque. PLoS Comput. Biol. 4, e1000050.

    Article  Google Scholar 

  3. 3.

    Baddeley, A. (2012) Working memory: Theories, models, and controversies. Annu Rev. Psychol. 63, 12.1–12.29.

    Article  Google Scholar 

  4. 4.

    Banich, M.T., Compton, R. J. (2011) Cognitive Neuroscience (3rd ed.). Wadsworth Publishing.

    Google Scholar 

  5. 5.

    Bányai, M., Négyessy, L., Bazsó, F. (2011) Organisation of signal flow in directed networks. Journal of Statistical Mechanics: theory and experiment. P06001. doi: 10.1088/1742-5468/2011/06/P06001

    Google Scholar 

  6. 6.

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

    CAS  Article  Google Scholar 

  7. 7.

    Constantinidis, C., Procyk, E. (2004) The primate working memory networks. Cogn. Affect Behav. Neurosci. 4, 444 165.

    Google Scholar 

  8. 8.

    Csárdi, G., Nepusz, T. (2006) The igraph software package for complex network research. Inter. Journal, Complex Systems 1695.

    Google Scholar 

  9. 9.

    Dehaene, S., Changeux, J. P. (2011) Experimental and theoretical approaches to conscious processing. Neuron. 70, 200–227.

    CAS  Article  Google Scholar 

  10. 10.

    Fortunato, S. (2009) Community detection in graphs Physics Report. 486, 75–174.

    Google Scholar 

  11. 11.

    Fruchterman, T. M. J., Reingold, E. M. (1991) Graph Drawing by Force-Directed Placement. Software -Practice & Experienc. 21, 1129–1164.

    Article  Google Scholar 

  12. 12.

    Fuster, J. M. (1997) The prefrontal cortex. Anatomy, physiology and neuropsychology of the frontal lobe. Lippincott-Raven. Philadelphia, New York.

    Google Scholar 

  13. 13.

    Gazzaniga, M.S., Ivry, R.B., Mangun, G. R. (2009) Cognitive Neuroscience: The biology of the mind (3rd ed.). New York: W. W. Norton.

    Google Scholar 

  14. 14.

    Gisiger, T., Dehaene, S., Changeux, J. P. (2000) Computational models of association cortex. Curr Opin. Neurobiol. 10, 250–259.

    CAS  Article  Google Scholar 

  15. 15.

    Honey, C.J., Kõtter, R., Breakspear, M., Sporns, O. (2007) Network structure of cerebral cortex shapes functional connectivity on multiple time scales. Proc. Natl. Acad. Sci. USA. 104, 10240–10245.

    CAS  Article  Google Scholar 

  16. 16.

    Honey, C.J., Thivierge, J.P., Sporns, O. (2010) Can structure predict function in the human brain? Neuroimag. 52, 766–776.

    Article  Google Scholar 

  17. 17.

    Marois, R., Ivanoff J. (2005) Capacity limits of information processing in the brain. Trends Cogn. Sci. 9, 296–305.

    Article  Google Scholar 

  18. 18.

    Meyer, K., Damásio, A. (2009) Convergence and divergence in a neural architecture for recognition and memory. Trends Neurosci. 32, 376–382.

    CAS  Article  Google Scholar 

  19. 19.

    Miller, E.K., Cohen, J. D. (2001) An integrative theory of prefrontal cortex function. Annu. Rev. Neurosci. 24, 167–202.

    CAS  Article  Google Scholar 

  20. 20.

    Nepusz, T., Négyessy, L., Tusnády, G., Bazsó, F. (2009) Reconstructing cortical networks: case of directed graphs with high level of reciprocity. In: Bollobás, B., Kozma, R., Miklós D. (ed.) Handbook of Large-scale Random Networks. Springer, pp. 325–368.

    Google Scholar 

  21. 21.

    Nepusz, T., Petróczi, A., Négyessy, L., Bazsó, F. (2008) Fuzzy communities and the concept of brid-geness in complex networks. Phys. Rev. E Stat. Nonlin. Soft Matter Phys. 77, 016107.

    Article  Google Scholar 

  22. 22.

    Négyessy, L., Nepusz, T., Kocsis, L., Bazsó, F. (2006) Prediction of the main cortical areas and connections involved in the tactile function of the visual cortex by network analysis. Eur. J. Neurosci. 23, 1919–1930.

    Article  Google Scholar 

  23. 23.

    Négyessy, L., Nepusz, T., Zalányi, L., Bazsó, F. (2008) Convergence and divergence are mostly reciprocated properties of the connections in the network of cortical areas. Proc. Biol. Sci. 275, 2403–2410.

    Article  Google Scholar 

  24. 24.

    Sporns, O. (2002) Graph theory methods for the analysis of neural connectivity patterns. In: Kõtter, R. (ed.) Neuroscience Databases. A Practical Guide. Klüwer, Boston, MA. pp. 171–186.

    Google Scholar 

  25. 25.

    Sporns, O., Kõtter, R. (2004) Motifs in brain networks. PLoSBiol. 2, e369.

    Article  Google Scholar 

  26. 26.

    Tombu, M.N., Asplund, C.L., Dux, P.E., Godwin, D., Martin, J.W., Marois, R. (2011) A unified attentional bottleneck in the human brain. Proc. Natl. Acad. Sci. USA. 108, 13426–13431.

    CAS  Article  Google Scholar 

  27. 27.

    Sigman, M., Dehaene, S. (2008) Brain mechanisms of serial and parallel processing during dual-task performance. J. Neurosci. 28, 7585–7598.

    CAS  Article  Google Scholar 

  28. 28.

    Sporns, O. (2011) The non-random brain: efficiency, economy, and complex dynamics. Front Comput. Neurosci. 5, 5.

    Article  Google Scholar 

  29. 29.

    Strogatz, S. H. (2001) Exploring complex networks. Natur. 410, 268–276.

    CAS  Article  Google Scholar 

  30. 30.

    Watts, D. J. (2004) The “New” Science of Networks. Annual Review of Sociolog. 30, 243–270.

    Article  Google Scholar 

  31. 31.

    Wood, J.N., Grafman, J. (2003) Human prefrontal cortex: processing and representational perspectives. Nat. Rev. Neurosci. 4, 139–147.

    CAS  Article  Google Scholar 

  32. 32.

    Yan, C., He, Y (2011) Driving and driven architectures of directed small-world human brain functional networks. PLoS One. 6, e23460.

    Google Scholar 

  33. 33.

    Zylberberg, A., Fernandez Slezak, D., Roelfsema, P.R., Dehaene, S., Sigman, M. (2010) The brain’s router: a cortical network model of serial processing in the primate brain. PLoS Comput. Biol. 6, e1000765.

    Article  Google Scholar 

Download references

Author information



Corresponding author

Correspondence to L. Négyessy.

Additional information

Dedicated to Professor József Hámori on the occasion of his 80th birthday.

Rights and permissions

This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

Reprints and Permissions

About this article

Cite this article

Négyessy, L., Bányai, M., Nepusz, T. et al. What Makes The Prefrontal Cortex So Appealing in the Era of Brain Imaging? A Network Analytical Perspective. BIOLOGIA FUTURA 63, 38–53 (2012). https://doi.org/10.1556/ABiol.63.2012.Suppl.1.5

Download citation