Epileptic source localization through EEG
Non-invasive EEG Functional Neuroimaging for Localizing Epileptic Brain Activity
Surgical therapy has become an important therapeutic alternative for patients with medically intractable epilepsy. Correct and anatomically precise localization of the epileptic focus, preferably with non-invasive methods, is the main goal of the pre-surgical epilepsy diagnosis to decide if resection of brain tissue is possible.
The most important diagnosis tool used at epilepsy surgery centers is electroencephalography (EEG), which is used to find the source of activities inside the brain by measuring the voltage potential on the scalp with the EEG electrodes at different locations. The overall goal is to develop a non-invasive, clinically-viable, time-efficient method for localization of epileptic brain activity based on EEG source localization.
We propose a new global optimization method based on particle swarm optimization (PSO) to solve the epileptic spike EEG source localization inverse problem. In the forward problem a modified subtraction method is used for modeling the dipole source to reduce the computational time. The new proposed inverse method is tested for synthetic and real EEG data and the results are compared with other existing methods. The results for synthetic data showed that the new PSO algorithm can find the optimal solution significantly faster and more accurate than the other methods and also reduce the probability of trapping in local minima.
In the clinical test, somatosensory evoked potentials (SEPs) were measured for a healthy subject and used for source localization. A realistic 1 mm patient-specific, isotropic finite element model of the subject’s head with special consideration of precise modeling the two compartments, skull and cerebrospinal fluid (CSF), was generated using T1-weighted magnetic resonance imaging data. We have applied MPSO to median (N20) and tibial (P40) nerve stimulations as well as their late cortical activities, (P60) and (N80), respectively. Comparison between the recorded EEG and estimated scalp potential topographies showed a good agreement in all cases. Moreover, based on clinical expertise the estimated sources are located in correct region. The EEG source localization results obtained from MPSO gave the same results as exhaustive search method but with significantly lower computational complexity.
The overall goal is to develop a non-invasive, clinically-viable, time-efficient method for localization of epileptic brain activity based on EEG source localization.
The work has been performed in the Biomedical Electromagnetics Group, Department of Signals and Systems at Chalmers from Jan. 2009 to present under the supervision of Professor Mikael Persson, Associate Professor Fredrik Edelvik (Fraunhofer-Chalmers Research Center, FCC) and Medical Doctor Anders Hedström (Sahlgrenska University Hospital).
This work has been supported in part by Chalmers University of Technology. The project has been performed in collaboration with industry, namely FCC. The data for this thesis was recorded by the Neurophysiology Department, Sahlgrenska University Hospital, Göteborg, Sweden.
MedTech West partner
Yazdan Shirvany, PhD Student, Department of Signal Processing and Biomedical Engineering, S2, Chalmers University of Technology.
Technical research partners
Prof. Mikael Persson, Department of Signal Processing and Biomedical Engineering, S2, Chalmers University of Technology.
Dr. Fredrik Edelvik, Department of Computational Engineering and Design, FCC, Chalmers University of Technology.
Dr. Anders Hedström, MD, Institute of Neuroscience and Physiology, Clinical Neurophysiology, Sahlgrenska University Hospital
Ass. Prof. Magnus Thordstein, Institute of Neuroscience and Physiology, Clinical Neurophysiology, Sahlgrenska University Hospital
For more information about this project contact Henrik Mindedal, MedTech West, email@example.com
Shirvany, Y., Non-invasive EEG Functional Neuroimaging for Localizing Epileptic Brain Activity, Licentiate of Engineering, Chalmers University of Technology, Report No. R002/2012, ISSN 1403-266X.
Shirvany, Y., Mahmood, Q., Edelvik, F., Jakobsson, S., Hedström A., and Persson, M., Particle Swarm Optimization applied to EEG Source Localization of Somatosensory Evoked Potentials, Submitted to IEEE Transaction on Neural System and Rehabilitation.
Shirvany, Y., Porras, A.R., Kowkabzadeh, K., Mahmood, Q., Lui, H., and Persson, H., Investigation of Brain Tissue Segmentation Error and its Effect on EEG Source Localization, Accepted to 34th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC12).
Shirvany, Y., Edelvik, F., Jakobsson, S., Hedström, A., Mahmood, Q., Chodorowski, A., and Persson, M., Non-invasive EEG Source Localization using Particle Swarm Optimization: A Clinical Experiment, Accepted to 34th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC12).
Shirvany, Y., Edelvik, F., Jakobsson, S., Hedström, A., and Persson, M., Application of Particle Swarm Optimization in Epileptic Spike EEG Source Localization, Summited on J. of Applied Soft Computing.
Persson, M., McKelvey, T., Fhager, A., Lui, H., Shirvany, Y., Chodorowski, A., Mahmood, Q., Edelvik, F., Thordstein, M., Hedström, A., and Elam, M., Advances in Neuro Diagnostic based on Microwave Technology, Transcranial Magnetic Stimulation and EEG source localization, Asia Pacific Microwave Conference.
Edelvik, F., Andersson, B., Jakobsson, S., Larsson, S., Persson, M., and Shirvany, Y., An improved method for dipole modeling in EEG-based source localization, World Congress of Medical Physics and Biomedical Engineering.