State dependent properties of epileptic brain networks: comparative graph-theoretical analyses of simultaneously recorded EEG and MEG.
OBJECTIVE
To investigate whether functional brain networks of epilepsy patients treated with antiepileptic medication differ from networks of healthy controls even during the seizure-free interval.


METHODS
We applied different rules to construct binary and weighted networks from EEG and MEG data recorded under a resting-state eyes-open and eyes-closed condition from 21 epilepsy patients and 23 healthy controls. The average shortest path length and the clustering coefficient served as global statistical network characteristics.


RESULTS
Independent on the behavioral condition, epileptic brains exhibited a more regular functional network structure. Similarly, the eyes-closed condition was characterized by a more regular functional network structure in both groups. The amount of network reorganization due to behavioral state changes was similar in both groups. Consistent findings could be achieved for networks derived from EEG but hardly from MEG recordings, and network construction rules had a rather strong impact on our findings.


CONCLUSIONS
Despite the locality of the investigated processes epileptic brain networks differ in their global characteristics from non-epileptic brain networks. Further methodological developments are necessary to improve the characterization of disturbed and normal functional networks.


CONCLUSIONS
An increased regularity and a diminished modulation capability appear characteristic of epileptic brain networks.
Horstmann
Marie-Therese
MT
Department of Epileptology, University of Bonn, Sigmund-Freud-Str 25, 53105 Bonn, Germany. mhorstma@uni-bonn.de
Bialonski
Stephan
S
Noennig
Nina
N
Mai
Heinke
H
Prusseit
Jens
J
Wellmer
Jörg
J
Hinrichs
Hermann
H
Lehnertz
Klaus
K
D000328:Adult; D002540:Cerebral Cortex / Q000503:physiopathology*; D003072:Cognition Disorders / Q000503:physiopathology; D004569:Electroencephalography / Q000379:methods*; D004827:Epilepsy / Q000175:diagnosis / Q000503:physiopathology*; D005260:Female; D007839:Functional Laterality / Q000502:physiology; D006801:Humans; D015225:Magnetoencephalography / Q000379:methods*; D008297:Male; D008432:Mathematical Computing; D055641:Mathematical Concepts; D008875:Middle Aged; D009415:Nerve Net / Q000503:physiopathology*; D016571:Neural Networks, Computer; D009473:Neuronal Plasticity / Q000502:physiology; D012815:Signal Processing, Computer-Assisted