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Time-dependent degree-degree correlations in epileptic brain networks: from assortative to dissortative mixing.

Geier C, Lehnertz K, Bialonski S - Front Hum Neurosci (2015)

Bottom Line: Functional networks are derived from continuous multi-day, multi-channel electroencephalographic data, which capture a wide range of physiological and pathophysiological activities.Our findings suggest that physiological and pathophysiological activity may modify functional brain networks in a different and process-specific way.We evaluate factors that possibly influence the long-term evolution of degree-degree correlations.

View Article: PubMed Central - PubMed

Affiliation: Department of Epileptology, University of Bonn Bonn, Germany ; Helmholtz Institute for Radiation and Nuclear Physics, University of Bonn Bonn, Germany.

ABSTRACT
We investigate the long-term evolution of degree-degree correlations (assortativity) in functional brain networks from epilepsy patients. Functional networks are derived from continuous multi-day, multi-channel electroencephalographic data, which capture a wide range of physiological and pathophysiological activities. In contrast to previous studies which all reported functional brain networks to be assortative on average, even in case of various neurological and neurodegenerative disorders, we observe large fluctuations in time-resolved degree-degree correlations ranging from assortative to dissortative mixing. Moreover, in some patients these fluctuations exhibit some periodic temporal structure which can be attributed, to a large extent, to daily rhythms. Relevant aspects of the epileptic process, particularly possible pre-seizure alterations, contribute marginally to the observed long-term fluctuations. Our findings suggest that physiological and pathophysiological activity may modify functional brain networks in a different and process-specific way. We evaluate factors that possibly influence the long-term evolution of degree-degree correlations.

No MeSH data available.


Related in: MedlinePlus

Sketch of how functional brain networks may explore the space of accessible network topologies (here parametrized by the clustering coefficient C, average shortest path length L, and assortativity coefficient a) in a process-dependent way: Daily rhythms may be reflected in periodic reorganizations of functional brain networks. Superimposed on that may be a reorganization in functional network connectivity reflecting pathophysiological activity.
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Figure 6: Sketch of how functional brain networks may explore the space of accessible network topologies (here parametrized by the clustering coefficient C, average shortest path length L, and assortativity coefficient a) in a process-dependent way: Daily rhythms may be reflected in periodic reorganizations of functional brain networks. Superimposed on that may be a reorganization in functional network connectivity reflecting pathophysiological activity.

Mentions: In the light of results reported in previous studies (Ponten et al., 2007; Schindler et al., 2008; Kramer et al., 2010, 2011; Kuhnert et al., 2010; Bialonski et al., 2011; Bialonski and Lehnertz, 2013), our findings might point toward the following: We speculate that daily rhythms may be reflected in periodic reorganizations of functional brain networks. Superimposed on that may be a reorganization in functional network connectivity reflecting pathophysiological activity. The space of accessible network topologies, however, may be explored in a different and process-dependent way (cf. Figure 6).


Time-dependent degree-degree correlations in epileptic brain networks: from assortative to dissortative mixing.

Geier C, Lehnertz K, Bialonski S - Front Hum Neurosci (2015)

Sketch of how functional brain networks may explore the space of accessible network topologies (here parametrized by the clustering coefficient C, average shortest path length L, and assortativity coefficient a) in a process-dependent way: Daily rhythms may be reflected in periodic reorganizations of functional brain networks. Superimposed on that may be a reorganization in functional network connectivity reflecting pathophysiological activity.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4542502&req=5

Figure 6: Sketch of how functional brain networks may explore the space of accessible network topologies (here parametrized by the clustering coefficient C, average shortest path length L, and assortativity coefficient a) in a process-dependent way: Daily rhythms may be reflected in periodic reorganizations of functional brain networks. Superimposed on that may be a reorganization in functional network connectivity reflecting pathophysiological activity.
Mentions: In the light of results reported in previous studies (Ponten et al., 2007; Schindler et al., 2008; Kramer et al., 2010, 2011; Kuhnert et al., 2010; Bialonski et al., 2011; Bialonski and Lehnertz, 2013), our findings might point toward the following: We speculate that daily rhythms may be reflected in periodic reorganizations of functional brain networks. Superimposed on that may be a reorganization in functional network connectivity reflecting pathophysiological activity. The space of accessible network topologies, however, may be explored in a different and process-dependent way (cf. Figure 6).

Bottom Line: Functional networks are derived from continuous multi-day, multi-channel electroencephalographic data, which capture a wide range of physiological and pathophysiological activities.Our findings suggest that physiological and pathophysiological activity may modify functional brain networks in a different and process-specific way.We evaluate factors that possibly influence the long-term evolution of degree-degree correlations.

View Article: PubMed Central - PubMed

Affiliation: Department of Epileptology, University of Bonn Bonn, Germany ; Helmholtz Institute for Radiation and Nuclear Physics, University of Bonn Bonn, Germany.

ABSTRACT
We investigate the long-term evolution of degree-degree correlations (assortativity) in functional brain networks from epilepsy patients. Functional networks are derived from continuous multi-day, multi-channel electroencephalographic data, which capture a wide range of physiological and pathophysiological activities. In contrast to previous studies which all reported functional brain networks to be assortative on average, even in case of various neurological and neurodegenerative disorders, we observe large fluctuations in time-resolved degree-degree correlations ranging from assortative to dissortative mixing. Moreover, in some patients these fluctuations exhibit some periodic temporal structure which can be attributed, to a large extent, to daily rhythms. Relevant aspects of the epileptic process, particularly possible pre-seizure alterations, contribute marginally to the observed long-term fluctuations. Our findings suggest that physiological and pathophysiological activity may modify functional brain networks in a different and process-specific way. We evaluate factors that possibly influence the long-term evolution of degree-degree correlations.

No MeSH data available.


Related in: MedlinePlus