Prediction of seizure spread network via sparse representations of overcomplete dictionaries

Feng Liu, Wei Xiang, Shouyi Wang, Bradley Lega

    Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

    6 Scopus citations

    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.

    Original languageEnglish
    Title of host publicationBrain Informatics and Health - International Conference, BIH 2016, Proceedings
    EditorsHesham Ali, Yong Shi, Giorgio A. Ascoli, Deepak Khazanchi, Michael Hawrylycz
    Pages262-273
    Number of pages12
    DOIs
    StatePublished - 2016
    EventInternational Conference on Brain Informatics and Health, BIH 2016 - Omaha, United States
    Duration: 13 Oct 201616 Oct 2016

    Publication series

    NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
    Volume9919 LNAI
    ISSN (Print)0302-9743
    ISSN (Electronic)1611-3349

    Conference

    ConferenceInternational Conference on Brain Informatics and Health, BIH 2016
    Country/TerritoryUnited States
    CityOmaha
    Period13/10/1616/10/16

    Keywords

    • Brain connectivity
    • CCEP
    • Feature selection
    • Seizure spread network
    • Sparse representation

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