TY - JOUR
T1 - Modeling of intracerebral interictal epileptic discharges
T2 - evidence for network interactions
AU - Meesters, S.
AU - Ossenblok, P.
AU - Colon, A.
AU - Wagner, L.
AU - Schijns, O.
AU - Boon, P.
AU - Florack, L.
AU - Fuster, A.
PY - 2018/6/1
Y1 - 2018/6/1
N2 - Objective: The interictal epileptic discharges (IEDs) occurring in stereotactic EEG (SEEG) recordings are in general abundant compared to ictal discharges, but difficult to interpret due to complex underlying network interactions. A framework is developed to model these network interactions. Methods: To identify the synchronized neuronal activity underlying the IEDs, the variation in correlation over time of the SEEG signals is related to the occurrence of IEDs using the general linear model. The interdependency is assessed of the brain areas that reflect highly synchronized neural activity by applying independent component analysis, followed by cluster analysis of the spatial distributions of the independent components. The spatiotemporal interactions of the spike clusters reveal the leading or lagging of brain areas. Results: The analysis framework was evaluated for five successfully operated patients, showing that the spike cluster that was related to the MRI-visible brain lesions coincided with the seizure onset zone. The additional value of the framework was demonstrated for two more patients, who were MRI-negative and for whom surgery was not successful. Conclusions: A network approach is promising in case of complex epilepsies. Significance: Analysis of IEDs is considered a valuable addition to routine review of SEEG recordings, with the potential to increase the success rate of epilepsy surgery.
AB - Objective: The interictal epileptic discharges (IEDs) occurring in stereotactic EEG (SEEG) recordings are in general abundant compared to ictal discharges, but difficult to interpret due to complex underlying network interactions. A framework is developed to model these network interactions. Methods: To identify the synchronized neuronal activity underlying the IEDs, the variation in correlation over time of the SEEG signals is related to the occurrence of IEDs using the general linear model. The interdependency is assessed of the brain areas that reflect highly synchronized neural activity by applying independent component analysis, followed by cluster analysis of the spatial distributions of the independent components. The spatiotemporal interactions of the spike clusters reveal the leading or lagging of brain areas. Results: The analysis framework was evaluated for five successfully operated patients, showing that the spike cluster that was related to the MRI-visible brain lesions coincided with the seizure onset zone. The additional value of the framework was demonstrated for two more patients, who were MRI-negative and for whom surgery was not successful. Conclusions: A network approach is promising in case of complex epilepsies. Significance: Analysis of IEDs is considered a valuable addition to routine review of SEEG recordings, with the potential to increase the success rate of epilepsy surgery.
KW - Analysis framework
KW - Epilepsy surgery
KW - Interictal epileptic discharges
KW - Spatiotemporal network interaction
KW - Stereo-electroencephalography
KW - Epilepsy/physiopathology
KW - Seizures/physiopathology
KW - Humans
KW - Middle Aged
KW - Male
KW - Electroencephalography
KW - Nerve Net/physiopathology
KW - Young Adult
KW - Adolescent
KW - Brain Mapping
KW - Signal Processing, Computer-Assisted
KW - Adult
KW - Female
KW - Models, Neurological
UR - http://www.scopus.com/inward/record.url?scp=85045716863&partnerID=8YFLogxK
U2 - 10.1016/j.clinph.2018.03.021
DO - 10.1016/j.clinph.2018.03.021
M3 - Article
C2 - 29679878
AN - SCOPUS:85045716863
SN - 1388-2457
VL - 129
SP - 1276
EP - 1290
JO - Clinical Neurophysiology
JF - Clinical Neurophysiology
IS - 6
ER -