Localizing epileptic brain activity using non-invasive EEG functional neuroimaging​

Start date 01/01/2009
End date The project is closed: 31/12/2013

This project aims to improve currently inadequate diagnostics for correct and anatomically precise localization of the epileptic focus, in order to enable surgical therapy. The reason is that anti-epileptic drugs frequently fail to successfully control epileptic seizures. An alternative, which requires knowledge of the epileptic focus, is to remove affected brain tissue.

The current diagnostics tools have limited accuracy and are therefore associated with significant risks. Underestimating the extent of the affected region can result in the re-occurrence of seizures following surgery, while overestimation holds an increased risk of functional deficits.

The overall goal of the project is to develop a non-invasive, clinically-viable, time-efficient method for localization of epileptic brain activity based on electroencephalograph (EEG) source localization. EEG is the most important diagnosis tool 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.
When the drugs don’t work

Epilepsy is one of the most common neurologic diseases in the world, with many patients never receiving the treatment which make them seizure free. Surgical therapy has become an important therapeutic alternative for patients with medically intractable epilepsy, in order to localize epileptic activity and remove affected brain tissue.

The risks of intracranial surgery do not equal the risks of uncontrolled seizures, which involve accidental injury, cognitive decline and memory loss and sudden unexplained death. In addition, the benefits of removing affected brain tissue outweigh the benefits of anti-epileptic drugs (AED’s), resulting in a better quality of life for the patient.

Localizing epileptic activity
Before intracranial surgery can be carried out, the epileptic brain activity needs to be accurately localized. Underestimating the extent of the affected region can result in the re-occurrence of seizures following surgery, while overestimation holds an increased risk of functional deficits. Localization is currently done via three methods; electroencephalography (EEG), structural MRI (sMRI) and nuclear imaging techniques. These techniques have limited accuracy and are therefore associated with significant risks. Hence, there is a need for improved, complementary, time-efficient, non-invasive methods to define the seizure-generating focus.
Benefits and challenges of EEG diagnostics
​The EEG is the most important diagnostics tool used at epilepsy surgery centers. This method localizes epileptic electrical activity, called spike waveforms. Spikes occur between seizure times and are closely linked to the site of seizure focus. In contrast to seizures, spikes do not cause patient movement artifact in an MRI scanner, which is advantageous to data acquisition.
 
A major limitation in EEG based source reconstruction has been the poor spatial accuracy, which is attributed to low resolution of previous EEG systems and to the use of simplified spherical head models for solving the inverse problem.
 
The procedure of the EEG source localization deals with two problems. One is the forward problem to find the scalp potentials for the given current dipole(s) inside the brain. The second one is the inverse problem to estimate the source(s) that fits with the given potential distribution at the scalp electrodes.
More information
​Chalmers researchers propose a new global optimization method based on a computational method called 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.
​The work has been supported in part by Chalmers University of Technology and Islamic Development Bank. The project has been performed in collaboration with industry, namely FCC. The data was recorded by the Neurophysiology Department, Sahlgrenska University Hospital, Göteborg, Sweden.

Published: Tue 07 Mar 2017.