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Increased segregation of brain networks in focal epilepsy: An fMRI graph theory finding.

Pedersen M, Omidvarnia AH, Walz JM, Jackson GD - Neuroimage Clin (2015)

Bottom Line: Graph theory represents a powerful quantitative framework for investigation of brain networks.We postulate that network regularity, or segregation of the nodes of the networks, may be an adaptation that inhibits the conversion of the interictal state to seizures.It remains possible that this may be part of the epileptogenic process or an effect of medications.

View Article: PubMed Central - PubMed

Affiliation: The Florey Institute of Neuroscience and Mental Health, Austin Campus, Melbourne, VIC, Australia ; Florey Department of Neuroscience and Mental Health, The University of Melbourne, Melbourne, VIC, Australia.

ABSTRACT
Focal epilepsy is conceived of as activating local areas of the brain as well as engaging regional brain networks. Graph theory represents a powerful quantitative framework for investigation of brain networks. Here we investigate whether functional network changes are present in extratemporal focal epilepsy. Task-free functional magnetic resonance imaging data from 15 subjects with extratemporal epilepsy and 26 age and gender matched healthy controls were used for analysis. Local network properties were calculated using local efficiency, clustering coefficient and modularity metrics. Global network properties were assessed with global efficiency and betweenness centrality metrics. Cost-efficiency of the networks at both local and global levels was evaluated by estimating the physical distance between functionally connected nodes, in addition to the overall numbers of connections in the network. Clustering coefficient, local efficiency and modularity were significantly higher in individuals with focal epilepsy than healthy control subjects, while global efficiency and betweenness centrality were not significantly different between the two groups. Local network properties were also highly efficient, at low cost, in focal epilepsy subjects compared to healthy controls. Our results show that functional networks in focal epilepsy are altered in a way that the nodes of the network are more isolated. We postulate that network regularity, or segregation of the nodes of the networks, may be an adaptation that inhibits the conversion of the interictal state to seizures. It remains possible that this may be part of the epileptogenic process or an effect of medications.

No MeSH data available.


Related in: MedlinePlus

Whole-brain local and global network differences between extratemporal focal epilepsy subjects (red line) and healthy controls (blue line). Regular and random networks are displayed with black dotted and solid line respectively. A)LE. B)CCnorm. Note that the random networks for CCnorm have a value of 1 for all 26 thresholds as CCnorm incorporates random networks (see Section2.5). C)MOD. D)GE. E)BC.
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f0015: Whole-brain local and global network differences between extratemporal focal epilepsy subjects (red line) and healthy controls (blue line). Regular and random networks are displayed with black dotted and solid line respectively. A)LE. B)CCnorm. Note that the random networks for CCnorm have a value of 1 for all 26 thresholds as CCnorm incorporates random networks (see Section2.5). C)MOD. D)GE. E)BC.

Mentions: An increase of LE was seen in the extratemporal focal epilepsy group compared to healthy controls (Fig.3A) with 10 of 26 network densities statistically significant after FDR correction (median effect size = 0.90, CI 95% of 0.16–1.65). CCnorm was significantly higher in focal epilepsy subjects compared to controls for 23 of 26 network density thresholds (FDR-corrected). Median effect size for CCnorm was 1.21 with CI 95% of 0.41–2.01. Focal epilepsy subjects also displayed increased network MOD versus controls (Fig.3B) in 4 of 26 density thresholds (FDR-corrected) with a median effect size of 0.76 and CI 95% of 0.05–1.48. No statistically significant differences were seen between focal epilepsy subjects and healthy controls for GE (median effect size = −0.53, CI 95% of 0.15 to −1.23— Fig.3C) and BC (median effect size = 0.56, CI 95% of −0.12–1.25— Fig.3D).


Increased segregation of brain networks in focal epilepsy: An fMRI graph theory finding.

Pedersen M, Omidvarnia AH, Walz JM, Jackson GD - Neuroimage Clin (2015)

Whole-brain local and global network differences between extratemporal focal epilepsy subjects (red line) and healthy controls (blue line). Regular and random networks are displayed with black dotted and solid line respectively. A)LE. B)CCnorm. Note that the random networks for CCnorm have a value of 1 for all 26 thresholds as CCnorm incorporates random networks (see Section2.5). C)MOD. D)GE. E)BC.
© Copyright Policy - CC BY-NC-ND
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4477107&req=5

f0015: Whole-brain local and global network differences between extratemporal focal epilepsy subjects (red line) and healthy controls (blue line). Regular and random networks are displayed with black dotted and solid line respectively. A)LE. B)CCnorm. Note that the random networks for CCnorm have a value of 1 for all 26 thresholds as CCnorm incorporates random networks (see Section2.5). C)MOD. D)GE. E)BC.
Mentions: An increase of LE was seen in the extratemporal focal epilepsy group compared to healthy controls (Fig.3A) with 10 of 26 network densities statistically significant after FDR correction (median effect size = 0.90, CI 95% of 0.16–1.65). CCnorm was significantly higher in focal epilepsy subjects compared to controls for 23 of 26 network density thresholds (FDR-corrected). Median effect size for CCnorm was 1.21 with CI 95% of 0.41–2.01. Focal epilepsy subjects also displayed increased network MOD versus controls (Fig.3B) in 4 of 26 density thresholds (FDR-corrected) with a median effect size of 0.76 and CI 95% of 0.05–1.48. No statistically significant differences were seen between focal epilepsy subjects and healthy controls for GE (median effect size = −0.53, CI 95% of 0.15 to −1.23— Fig.3C) and BC (median effect size = 0.56, CI 95% of −0.12–1.25— Fig.3D).

Bottom Line: Graph theory represents a powerful quantitative framework for investigation of brain networks.We postulate that network regularity, or segregation of the nodes of the networks, may be an adaptation that inhibits the conversion of the interictal state to seizures.It remains possible that this may be part of the epileptogenic process or an effect of medications.

View Article: PubMed Central - PubMed

Affiliation: The Florey Institute of Neuroscience and Mental Health, Austin Campus, Melbourne, VIC, Australia ; Florey Department of Neuroscience and Mental Health, The University of Melbourne, Melbourne, VIC, Australia.

ABSTRACT
Focal epilepsy is conceived of as activating local areas of the brain as well as engaging regional brain networks. Graph theory represents a powerful quantitative framework for investigation of brain networks. Here we investigate whether functional network changes are present in extratemporal focal epilepsy. Task-free functional magnetic resonance imaging data from 15 subjects with extratemporal epilepsy and 26 age and gender matched healthy controls were used for analysis. Local network properties were calculated using local efficiency, clustering coefficient and modularity metrics. Global network properties were assessed with global efficiency and betweenness centrality metrics. Cost-efficiency of the networks at both local and global levels was evaluated by estimating the physical distance between functionally connected nodes, in addition to the overall numbers of connections in the network. Clustering coefficient, local efficiency and modularity were significantly higher in individuals with focal epilepsy than healthy control subjects, while global efficiency and betweenness centrality were not significantly different between the two groups. Local network properties were also highly efficient, at low cost, in focal epilepsy subjects compared to healthy controls. Our results show that functional networks in focal epilepsy are altered in a way that the nodes of the network are more isolated. We postulate that network regularity, or segregation of the nodes of the networks, may be an adaptation that inhibits the conversion of the interictal state to seizures. It remains possible that this may be part of the epileptogenic process or an effect of medications.

No MeSH data available.


Related in: MedlinePlus