Spatio-temporal patient-individual assessment of synchronization changes for epileptic seizure prediction.
OBJECTIVE
Abnormal synchronization of neurons plays a central role for the generation of epileptic seizures. Therefore, multivariate time series analysis techniques investigating relationships between the dynamics of different neural populations may offer advantages in predicting epileptic seizures.


METHODS
We applied a phase and a lag synchronization measure to a selected subset of multicontact intracranial EEG recordings and assessed changes in synchronization with respect to seizure prediction.


RESULTS
Patient individual results, group results, spatial aspects using focal and extra-focal electrode contacts as well as two evaluation schemes analyzing decreases and increases in synchronization were examined. Averaged sensitivity values of 60% are observed for a false prediction rate of 0.15 false predictions per hour, a seizure occurrence period of half an hour, and a prediction horizon of 10 min. For approximately half of all 21 patients, a statistically significant prediction performance is observed for at least one synchronization measure and evaluation scheme.


CONCLUSIONS
The results indicate that synchronization changes in the EEG dynamics preceding seizures can be used for seizure prediction. Nevertheless, the underlying pathogenic mechanisms differ and both decreases and increases in synchronization may precede epileptic seizures depending on the structures investigated.


CONCLUSIONS
The prediction method, optimized values of intervention times, as well as preferred brain structures for the EEG recordings have to be determined for each patient individually offering the chance of a better patient-individual prediction performance.
Winterhalder
Matthias
M
Freiburg Center for Data Analysis and Modeling, University of Freiburg, Eckerstr. 1, 79104 Freiburg, Germany. matthias.winterhalder@fdm.uni-freiburg.de
Schelter
Björn
B
Maiwald
Thomas
T
Brandt
Armin
A
Schad
Ariane
A
Schulze-Bonhage
Andreas
A
Timmer
Jens
J
D000293:Adolescent; D000328:Adult; D000465:Algorithms; D016477:Artifacts; D002648:Child; D003627:Data Interpretation, Statistical; D004566:Electrodes; D004569:Electroencephalography; D004827:Epilepsy / Q000503:physiopathology*; D005189:False Positive Reactions; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D009474:Neurons / Q000502:physiology*; D011237:Predictive Value of Tests; D015203:Reproducibility of Results; D012640:Seizures / Q000503:physiopathology*