Network Redundancy Analysis of Effective Brain Networks; a Comparison of Healthy Controls and Patients with Major Depression

Abstract : This study investigated electroencephalographic correlates in chronically depressed patients compared to healthy controls using intracutaneously applied electrical pain stimulus, to better understand the interaction between pain processing and depression. A close interaction between pain and depression is generally recognized although the precise mechanisms are not yet fully understood. The present study focuses on the hypothesis that effective brain connectivity in major depression patients is altered. Multifunctional interactions between brain regions represent a robust index of effective interactions within the brain, and can be quantified by network redundancy. Thus, structural network differences between 18 normal controls and 18 major depression patients before as well as during the processing of moderately painful intracutaneous electrical stimuli were investigated on the basis of network redundancy differences. In our sample, both patients and control subjects exhibit comparable network redundancies before stimulus application. Caused by the stimulus, there is a global increase of network redundancy in both groups. This increase is diminished in the group of major depression patients. We found clear differences between patients and controls during the stimulus processing, where the network redundancy in normal controls is larger in comparison to patients. The differences might be explained by the fact that major depression patients are more restricted to the affective component of the processing. The well-established biasing to affective processing might suppress the somatosensory processing resulting in a lower number of connections within the considered network. This might then lead to a reduction in network redundancy during stimulus processing.
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PLoS ONE, Public Library of Science, 2013, 8 (4), pp.1-10. 〈10.1371/journal.pone.0060956〉
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https://hal.inria.fr/hal-01443257
Contributeur : Fabrizio De Vico Fallani <>
Soumis le : dimanche 22 janvier 2017 - 22:57:58
Dernière modification le : jeudi 26 avril 2018 - 10:28:53

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Lutz Leistritz, Thomas Weiss, Karl-Jürgen Bär, Fabrizio De Vico Fallani, Fabio Babiloni, et al.. Network Redundancy Analysis of Effective Brain Networks; a Comparison of Healthy Controls and Patients with Major Depression. PLoS ONE, Public Library of Science, 2013, 8 (4), pp.1-10. 〈10.1371/journal.pone.0060956〉. 〈hal-01443257〉

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