Authors:
L. Négyessy Hungarian Academy of Sciences — Péter Pázmány Catholic University — Semmelweis University Neurobionics Research Group Budapest Hungary

Search for other papers by L. Négyessy in
Current site
Google Scholar
PubMed
Close
,
M. Bányai

Search for other papers by M. Bányai in
Current site
Google Scholar
PubMed
Close
,
T. Nepusz

Search for other papers by T. Nepusz in
Current site
Google Scholar
PubMed
Close
, and
F. Bazsó

Search for other papers by F. Bazsó in
Current site
Google Scholar
PubMed
Close
Restricted access

It is thought that the prefrontal cortex (PFC) subserves cognitive control processes by coordinating the flow of information in the cerebral cortex. In the network of cortical areas the central position of the PFC makes difficult to dissociate processing and the cognitive function mapped to this region, especially when using whole brain imaging techniques, which can detect frequently activated regions. Accordingly, the present study showed particularly high rate of increase of published studies citing the PFC and imaging as compared to other fields of the neurosciences on the PubMed. Network measures used to characterize the role of the areas in signal flow indicated specialization of the different regions of the PFC in cortical processing. Notably, areas of the dorsolateral PFC and the anterior cingulate cortex, which received the highest number of citations, were identified as global convergence points in the network. These prefrontal regions also had central position in the dominant cluster consisted exclusively by the associational areas of the cortex. We also present findings relevant to models suggesting that control processes of the PFC are depended on serial processing, which results in bottleneck effects. The findings suggest that PFC is best understood via its role in cortical information processing.

  • 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.

    Bullmore E. , 'A resilient, low-frequency, small-world human brain functional network with highly connected association cortical hubs ' (2006 ) 26 J. Neurosci. : 63 -72 .

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

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

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

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

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

  • 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

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

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

    • Search Google Scholar
  • Constantinidis, C., Procyk, E. (2004) The primate working memory networks. Cogn. Affect Behav. Neurosci. 4, 444–465.

    Procyk E. , 'The primate working memory networks ' (2004 ) 4 Cogn. Affect Behav. Neurosci. : 444 -465 .

    • Search Google Scholar
  • Csárdi G. Nepusz T. 2006 The igraph software package for complex network research. Inter. Journal Complex Systems1695

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

    Changeux J. P. , 'Experimental and theoretical approaches to conscious processing ' (2011 ) 70 Neuron. : 200 -227 .

    • Search Google Scholar
  • Fortunato, S. (2009) Community detection in graphs Physics Reports 486, 75–174.

    Fortunato S. , 'Community detection in graphs ' (2009 ) 486 Physics Reports : 75 -174 .

    • Search Google Scholar
  • Fruchterman, T. M. J., Reingold, E. M. (1991) Graph Drawing by Force-Directed Placement. Software — Practice & Experience 21, 1129–1164.

    Reingold E. M. , 'Graph Drawing by Force-Directed Placement ' (1991 ) 21 Software — Practice & Experience : 1129 -1164 .

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

    Fuster J. M. , '', in The prefrontal cortex. Anatomy, physiology and neuropsychology of the frontal lobe , (1997 ) -.

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

    Mangun G. R. , '', in Cognitive Neuroscience: The biology of the mind , (2009 ) -.

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

    Changeux J. P. , 'Computational models of association cortex ' (2000 ) 10 Curr. Opin. Neurobiol. : 250 -259 .

    • Search Google Scholar
  • Honey, C. J., Kötter, 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.

    Sporns O. , 'Network structure of cerebral cortex shapes functional connectivity on multiple time scales ' (2007 ) 104 Proc. Natl. Acad. Sci. USA. : 10240 -10245 .

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

    Sporns O. , 'Can structure predict function in the human brain? ' (2010 ) 52 Neuroimage : 766 -776 .

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

    Ivanoff J. , 'Capacity limits of information processing in the brain ' (2005 ) 9 Trends Cogn. Sci. : 296 -305 .

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

    Damasio A. , 'Convergence and divergence in a neural architecture for recognition and memory ' (2009 ) 32 Trends Neurosci. : 376 -382 .

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

    Cohen J. D. , 'An integrative theory of prefrontal cortex function ' (2001 ) 24 Annu. Rev. Neurosci. : 167 -202 .

    • Search Google Scholar
  • 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.

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

    Bazsó F. , 'Fuzzy communities and the concept of bridgeness in complex networks ' (2008 ) 77 Phys. Rev. E Stat. Nonlin. Soft Matter Phys. : 016107 -.

    • Search Google Scholar
  • 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.

    Bazsó F. , 'Prediction of the main cortical areas and connections involved in the tactile function of the visual cortex by network analysis ' (2006 ) 23 Eur. J. Neurosci. : 1919 -1930 .

    • Search Google Scholar
  • 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.

    Bazsó F. , 'Convergence and divergence are mostly reciprocated properties of the connections in the network of cortical areas ' (2008 ) 275 Proc. Biol. Sci. : 2403 -2410 .

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

    Sporns O. , '', in Neuroscience Databases. A Practical Guide , (2002 ) -.

  • Sporns, O., Kötter, R. (2004) Motifs in brain networks. PLoS Biol. 2, e369.

    Kötter R. , 'Motifs in brain networks ' (2004 ) 2 PLoS Biol. : e369 -.

  • 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.

    Marois R. , 'A unified attentional bottleneck in the human brain ' (2011 ) 108 Proc. Natl. Acad. Sci. USA. : 13426 -13431 .

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

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

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

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

    • Search Google Scholar
  • Strogatz, S. H. (2001) Exploring complex networks. Nature 410, 268–276.

    Strogatz S. H. , 'Exploring complex networks ' (2001 ) 410 Nature : 268 -276 .

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

    Watts D. J. , 'The “New” Science of Networks ' (2004 ) 30 Annual Review of Sociology : 243 -270 .

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

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

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

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

    • Search Google Scholar
  • Zylberberg, A., Fernández 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.

    Sigman M. , 'The brain’s router: a cortical network model of serial processing in the primate brain ' (2010 ) 6 PLoS Comput. Biol. : e1000765 -.

    • Search Google Scholar
  • Collapse
  • Expand

Editorial Board

    1. Csányi, Vilmos (Göd)
    1. Dudits, Dénes (Szeged)
    1. Falus, András (Budapest)
    1. Fischer, Ernő (Pécs)
    1. Gábriel, Róbert (Pécs)
    1. Gulya, Károly (Szeged)
    1. Gulyás, Balázs (Stockholm)
    1. Hajós, Ferenc (Budapest)
    1. Hámori, József (Budapest)
    1. Heszky, László (Gödöllő)
    1. Hideg, Éva (Szeged)
    1. E. Ito (Sanuki)
    1. Janda, Tibor (Martonvásár)
    1. Kavanaugh, Michael P. (Missoula)
    1. Kása, Péter (Szeged)
    1. Klein, Éva (Stockholm)
    1. Kovács, János (Budapest)
    1. Brigitte Mauch-Mani (Neuchâtel)
    1. Nässel, Dick R. (Stockholm)
    1. Nemcsók, János (Szeged)
    1. Péczely, Péter (Gödöllő)
    1. Roberts, D. F. (Newcastle-upon-Tyne)
    1. Sakharov, Dimitri A. (Moscow)
    1. Singh, Meharvan (Fort Worth)
    1. Sipiczky, Mátyás (Debrecen)
    1. Szeberényi, József (Pécs)
    1. Székely, György (Debrecen)
    1. Tari, Irma (Szeged)
    1. Vágvölgyi, Csaba (Szeged),
    1. L. Zaborszky (Newark)

 

Acta Biologica Hungarica
P.O. Box 35
H-8237 Tihany, Hungary
Phone: (36 87) 448 244 ext. 103
Fax: (36 87) 448 006
E-mail: elekes@tres.blki.hu

Indexing and Abstracting Services:

  • Biological Abstracts
  • BIOSIS Previews
  • CAB Abstracts
  • Chemical Abstracts
  • Current Contents: Agriculture
  • Biology and Environmental Sciences
  • Elsevier BIOBASE
  • Global Health
  • Index Medicus
  • Index Veterinarius
  • Medline
  • Referativnyi Zhurnal
  • Science Citation Index
  • Science Citation Index Expanded (SciSearch)
  • SCOPUS
  • The ISI Alerting Services
  • Zoological Abstracts

 

Acta Biologica Hungarica
Language English
Size  
Year of
Foundation
1950
Publication
Programme
changed title
Volumes
per Year
 
Issues
per Year
 
Founder Magyar Tudományos Akadémia
Founder's
Address
H-1051 Budapest, Hungary, Széchenyi István tér 9.
Publisher Akadémiai Kiadó
Publisher's
Address
H-1117 Budapest, Hungary 1516 Budapest, PO Box 245.
Responsible
Publisher
Chief Executive Officer, Akadémiai Kiadó
ISSN 0236-5383 (Print)
ISSN 1588-256X (Online)