Volume 12 Supplement 1

Twentieth Annual Computational Neuroscience Meeting: CNS*2011

Open Access

Simulated functional networks in health and schizophrenia: a graph theoretical approach

BMC Neuroscience201112(Suppl 1):P63

DOI: 10.1186/1471-2202-12-S1-P63

Published: 18 July 2011

In the last decade, particular attention has been paid to the graph theoretical aspects of the brain’s network and its implications in brain function. Small-worldness, path length, efficiency and several other graph theoretical metrics have allowed characterizing anatomical and functional network organization.

In a recent study [1], an analysis of resting-state functional networks of healthy volunteers and people with schizophrenia revealed a number of significant topological differences across groups, namely improved global efficiency, reduced small-worldness, lower clustering, increased hierarchy and greater robustness in patients with schizophrenia compared to healthy subjects. Moreover, these parameters were found correlate with the verbal fluency score, an indicator of disease severity. These results suggest a subtle functional network randomization in schizophrenia. Actually, schizophrenia, characterized by a dysfunctional integration of cognitive processes, is often classified as a disconnection syndrome. This can be understood in terms of abnormal functional connectivity between cortical areas as observed in EEG and fMRI experiments. A disruption of such interactions may therefore underlie the cognitive and behavioral disturbances described in schizophrenia.

In addition, a recent diffusion tensor imaging study [2] reports an overall lower anatomical connectivity in patients than control subjects. This suggests that the functional network alterations underlying schizophrenia could be originated by a widespread deficit in anatomical coupling.

In the present work we investigated the effect of decreasing the neurodynamical coupling strength in the topological properties of simulated functional networks. We used a large-scale dynamical model of local neural ensembles coupled through anatomical white matter fibers. Spontaneous neuronal activity was obtained from simulations and transformed into blood oxygenation level dependent (BOLD) signal. Functional networks were obtained by computing and thresholding the BOLD signals’ correlation matrix. Graph theoretical measures were then calculated for all the simulated graphs.

Results show that the networks’ topological properties vary with coupling strength. In more detail, when the neurodynamical coupling strength is decreased in the model, resulting networks exhibit an increase in global efficiency, hierarchy and robustness and a decrease in small-worldness and clustering, as reported for functional networks of people with schizophrenia. In addition, the shape of the degree distribution also changed accordingly. Moreover, the metrics are in the range of the ones reported experimentally in health and when the coupling strength is decreased by 6%, the measures are closer to the ones reported for schizophrenia (see Table 1).
Table 1

Graph theoretical metrics of functional networks in health and schizophrenia

  

Global Efficiency

Average Clustering

Hierarchy

Small-Worldness

Robustness to Random Attack

Robustness to Targeted Attack

Degree Distribution

        

Variance

Power exponent

Degree cut-off

Health

Exp.

0.744

0.743

0.037

1.61

0.991

0.960

183

3.25

9.45

 

Sim.

0.688

0.803

0.076

1.72

0.979

0.888

168

3.79

8.17

Schizo.

Exp.

0.746

0.692

0.101

1.53

0.995

0.970

120

6.11

5.37

 

Sim.

0.697

0.709

0.109

1.51

0.989

0.912

115

4.34

6.40

Exp.: mean experimental value reported in [1]. Sim.: value obtained from simulations. Schizo.: Schizophrenia.

Conclusions

Graph theoretical alterations of functional networks reported in schizophrenia can be accounted for by a decrease in the neurodynamical coupling strength, in agreement with theories of schizophrenia as a disconnectivity syndrome.

Authors’ Affiliations

(1)
Center for Brain and Cognition, Universitat Pompeu Fabra
(2)
Institut Català de Recerca i Estudis Avançats (ICREA)

References

  1. Lynall ME, Bassett DS, Kerwin R, McKenna PJ, Kitzbichler M, Muller U, Bullmore Ed: Functional connectivity and brain networks in schizophrenia. J Neurosci. 2010, 30 (28): 9477-9487.PubMed CentralView ArticlePubMedGoogle Scholar
  2. Skudlarski P, Jagannathan K, Anderson K, Stevens MC, Calhoun VD, Skudlarska BA, Pearlson G: Brain connectivity is not only lower but different in schizophrenia: a combined anatomical and functional approach. Biological psychiatry. 2010, 68 (1): 61-69. 10.1016/j.biopsych.2010.03.035.PubMed CentralView ArticlePubMedGoogle Scholar

Copyright

© Cabral et al; licensee BioMed Central Ltd. 2011

This article is published under license to BioMed Central Ltd. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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