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Brain Source Imaging in Preclinical Rat Models of Focal Epilepsy using High-Resolution EEG Recordings
08:20

Brain Source Imaging in Preclinical Rat Models of Focal Epilepsy using High-Resolution EEG Recordings

Published on: June 6, 2015

15.7K

State-space models of evoked potentials to localize the seizure onset zone

Rachel J Smith, Golnoosh Kamali, Mark Hays

    Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
    |October 6, 2020
    PubMed

    Abstract:

    Surgical removal of the seizure onset zone (SOZ) in epilepsy patients is a potentially curative treatment, but the process heavily relies on accurate localization of the SOZ via visual inspection. SPES (Single-pulse electrical stimulation) is a method recently used to explore inter-areal connectivity in vivo to probe functional brain networks such as language and motor networks, and to a much lesser degree, seizure networks. We hypothesized that a dynamical quantification of the connectivity networks derived from the evoked responses induced by SPES could also be used to localize the SOZ. To test our hypothesis, we used an intracranial EEG (iEEG) data set in which five epilepsy patients underwent extensive SPES evaluation. For each patient, and for each dataset that stimulated a different pair of electrodes, we constructed a state-space model from the patient's data. Specifically, we simultaneously estimated model parameters under an exogenous pulse input to a dynamical system whose state vector consisted of the response iEEG signals. Then, the size of the reachable state space, as quantified by the maximum singular value of the reachability matrix, σmax(R), was computed and denoted as the "largest" network response possible when stimulating the given pair. Our results suggest high agreement between σmax(R) and clinically annotated SOZ for patients with localizable SOZs.Clinical Relevance- Our study applies dynamical systems theory to identify epileptogenic brain regions, creating a novel tool that clinicians may use in surgical planning for medically-refractory epilepsy patients.

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