Simultaneous Electroencephalography and Magnetoencephalography to Identify Seizure-Prone Brain Regions

Begin with a human participant wearing electroencephalography or EEG electrodes and additional electrodes, lying in the magnetoencephalography or MEG chamber.

The EEG records the electrical signals from neurons and generates the EEG data. 

Simultaneously, MEG detects magnetic signals generated by neuronal electrical activity and produces the MEG data. 

With the additional electrodes, record peripheral signals from the body movements.

Remove the participant and record the background signal to remove noise from the data.

Compare EEG and MEG data to identify segments with interictal epileptiform discharges or IEDs.

IEDs are linked to recurrent abnormal brain activity associated with seizures.

Apply algorithms and detect high-frequency oscillations, or HFOs, representing rapid neuronal activity near or within IEDs, and compare them with peripheral signals to exclude body movement signals.

This ensures accurate localization of HFOs to seizure-prone regions.

Using an algorithm, EEG and MEG data generate a 3D brain map highlighting HFO regions linked to seizure-prone areas.

In the MEG acquisition software, click the Record button to record MEG, EEG, and obtain peripheral recordings for 60 minutes. After the recording is complete, open the MSR and take out the patient from the MSR room. Gently remove all the tapes, electrodes, HPI coils, and the EEG cap. Finally, after escorting the patient out of the testing space, record the magnetic signals of the empty MSR for two minutes without the patient present.

Begin by opening the data in the analysis software. Display EEG and MEG data with two vertically aligned windows of 10 seconds per page. Go to the Filter tab and set the high pass filter to 1 Hertz, the low pass filter to Hertz, and the notch filter at 50 or 60 Hertz.

Inspect the data and identify portions with Interictal Epileptic Discharges Or IEDs. Mark the peak of each IED occurring in both the EEG and MEG data. Run the algorithm for the automatic detection of HFOs on the portions of EEG data with IEDs and import the detected HFOs into the software for data visualization. To review the detected HFO events, Display EEG, MEG, and peripheral recordings with vertically aligned windows of 2 seconds per page. Go to the Filter tab and set the low pass filter to 250 Hertz and the high pass filter to 80 Hertz.

To ensure that the detected HFOs are not due to artifacts, verify that there is not concurrent activity in the peripheral recordings. Furthermore, consider only the HFO events that occur in both EEG and MEG signals and disregard HFOs that do not overlap with the marked IEDs. Next, segment the patient's MRI, and obtain the cortical surface using brain imaging analysis software, and estimate the forward model with the boundary element method.

For each HFO event, perform the source localization on both EEG and MEG data using the Wavelet Maximum Entropy on the Mean or wMEM method. Average the localization results along the event duration to obtain a source localization map. Finally, visualize the HFO zone over the cortical surface, applying a threshold of 60% of the maximum activation amplitude using both EEG and MEG data.