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Localizing the seizure onset zone from single pulse electrical stimulation responses using transfer function models.

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    Summary
    This summary is machine-generated.

    This study introduces a novel method using single pulse electrical stimulation (SPES) to precisely locate the seizure onset zone (SOZ) in epilepsy patients. Quantitative analysis of evoked responses aids in identifying the SOZ, improving surgical outcomes.

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    Area of Science:

    • Neuroscience
    • Biomedical Engineering
    • Epileptology

    Background:

    • Surgical resection of the seizure onset zone (SOZ) offers seizure freedom for medically refractory epilepsy.
    • Current SOZ localization relies on time-consuming visual inspection of intracranial electroencephalographic (iEEG) recordings.
    • Single pulse electrical stimulation (SPES) is used for functional brain network mapping during iEEG monitoring.

    Purpose of the Study:

    • To investigate the potential of using SPES-evoked responses to quantitatively localize the SOZ.
    • To develop patient-specific models to analyze iEEG network characteristics from SPES data.
    • To correlate SPES-derived metrics with clinically identified SOZ in epilepsy patients.

    Main Methods:

    • Constructed patient-specific single-input multi-output transfer function models.
    • Analyzed evoked responses from SPES in five epilepsy patients undergoing iEEG monitoring.
    • Quantified transfer function gain using the H-infinity norm.

    Main Results:

    • Preliminary results indicate that stimulation electrodes with the highest H-infinity norm gain correspond to the clinically defined SOZ.
    • This suggests SPES-evoked responses reflect the underlying iEEG network properties relevant to seizure origin.
    • The quantitative metrics derived from SPES show promise in identifying the SOZ.

    Conclusions:

    • SPES-evoked responses can be quantitatively analyzed to identify the SOZ in epilepsy patients.
    • This innovative tool offers a more objective and potentially faster method for SOZ localization.
    • Improved SOZ identification can enhance surgical success rates, reduce patient risks, and lower healthcare costs.