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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.
Significance
An increased regularity and a diminished modulation capability appear characteristic of epileptic brain networks.
Epilepsy
(2010)
Hybrid control for autonomous systems — Integrating learning, deliberation and reactive control
(2010)
We consider recent reports on small-world topologies of interaction networks derived from the dynamics of spatially extended systems that are investigated in diverse scientific fields such as neurosciences, geophysics, or meteorology. With numerical simulations that mimic typical experimental situations, we have identified an important constraint when characterizing such networks: indications of a small-world topology can be expected solely due to the spatial sampling of the system along with the commonly used time series analysis based approaches to network characterization.
Ein viel versprechender erneuerbarer Rohstoff für die Produktion von Chemikalien und Treibstoffen ist Lignocellulose aus pflanzlicher Biomasse. Die darin enthaltenen Zucker können mittels enzymatischer Hydrolyse freigesetzt und fermentativ zu Ethanol umgesetzt werden. Ein interessanter Ansatz ist dabei die simultane Verzuckerung und Fermentation. Hefen und Enzyme haben mit 30 °C bzw. 50 °C zwar unterschiedliche Temperaturoptima, es konnte aber gezeigt werden, dass auch bei den niedrigeren Temperaturen eine Umsetzung der Cellulose zu Glucose erfolgt, wenn auch langsamer als bei optimalen Bedingungen. Außerdem konnte in Vorversuchen gezeigt werden, dass Ethanol in den zu erwartenden Konzentrationen keinen Einfluss auf die enzymatische Umsetzung hat.