@inproceedings{8cd57637f9b945b7962e052f1cdb97de,
title = "Prediction of seizure spread network via sparse representations of overcomplete dictionaries",
abstract = "Epilepsy is one of the most common brain disorders and affect people of all ages. Resective surgery is currently the most effective overall treatment for patients whose seizures cannot be controlled by medications. Seizure spread network with secondary epileptogenesis are thought to be responsible for a substantial portion of surgical failures. However, there is still considerable risk of surgical failures for lacking of priori knowledge. Cortico-cortical evoked potentials (CCEP) offer the possibility of understanding connectivity within seizure spread networks to know how seizure evolves in the brain as it measures directly the intracranial electric signals. This study is one of the first works to investigate effective seizure spread network modeling using CCEP signals. The previous unsupervised brain network connectivity problem was converted into a classical supervised sparse representation problem for the first time. In particular, we developed an effective network modeling framework using sparse representation of over-determined features extracted from extensively designed experiments to predict real seizure spread network for each individual patient. The experimental results on five patients achieved prediction accuracy of about 70%, which indicates that it is possible to predict seizure spread network from stimulated CCEP networks. The developed CCEP signal analysis and network modeling approaches are promising to understand network mechanisms of epileptogenesis and have a potential to render clinicians better epilepsy surgical decisions in the future.",
keywords = "Brain connectivity, CCEP, Feature selection, Seizure spread network, Sparse representation",
author = "Feng Liu and Wei Xiang and Shouyi Wang and Bradley Lega",
note = "Publisher Copyright: {\textcopyright} Springer International Publishing AG 2016.; International Conference on Brain Informatics and Health, BIH 2016 ; Conference date: 13-10-2016 Through 16-10-2016",
year = "2016",
doi = "10.1007/978-3-319-47103-7_26",
language = "English (US)",
isbn = "9783319471020",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "262--273",
editor = "Hesham Ali and Yong Shi and Ascoli, {Giorgio A.} and Deepak Khazanchi and Michael Hawrylycz",
booktitle = "Brain Informatics and Health - International Conference, BIH 2016, Proceedings",
}