EEG and epilepsy

Authors: Francois Tadel, Elizabeth Bock, John C. Mosher.

This tutorial introduces some concepts that are specific to the management of EEG recordings in the Brainstorm environment. It also describes a standard pipeline for analyzing epilepsy recordings. It is based on a clinical case from the Epilepsy Center at the University Hospital of Freiburg, Germany. The anonymized dataset can be downloaded directly from the Brainstorm download page.

License

This tutorial dataset (EEG and MRI data) remains proprietary of the Epilepsy Centre, University Hospital Freiburg, Germany. Its use and transfer outside the Brainstorm tutorial, e.g. for research purposes, is prohibited without written consent from the Epilepsy Center in Freiburg. For questions please contact A. Schulze-Bonhage, MD, PhD: andreas.schulze-bonhage@uniklinik-freiburg.de

Presentation of the clinical case

This tutorial dataset was acquired in a patient who suffered from focal epilepsy with focal sensory, dyscognitive and secondarily generalized seizures since the age of eight years. He does not have any typical risk factors for epilepsy. The high resolution 3T epilepsy MRI including postprocessing was found to be normal. FDG-PET of the brain did not show any pathological changes in the glucose metabolism. Non-invasive telemetry revealed left fronto-central sharp waves, polyspikes and bursts of beta band activity (max. amplitude FC1, Cz) especially during sleep. The tutorial dataset was acquired during one night of the non-invasive telemetry recording at the Epilepsy Center Freiburg, Germany.

Afterwards the patient underwent invasive EEG to identify the epileptogenic area and to map functionally important cortex. Details about invasive EEG and source localization from invasive EEG in this patient are reported in Dümpelmann, et al. (2011). Subsequently a left frontal tailored resection was performed. The histological analysis revealed a focal cortical dysplasia type IIB according to the classification of Palmini, et al. (2004). The postsurgical outcome is Engel 1A with a follow-up of 5 years.

The EEG data distributed here was recorded at 1024Hz, using a Neurofile NT digital video-EEG system with 128 channels and a 16-bit A/D converter. The signal was filtered in the recording system with a high-pass filter with a time constant of 1 second and a low-pass filter with a cutoff frequency of 344 Hz. The spikes were marked with Brainstorm by the epileptologists at the Epilepsy Center in Freiburg.

Overview of the data processing

The proper identification of epileptiform discharges ("spikes") is a complicated topic beyond the scope of this tutorial. Neurology students train intensively on how to identify true interictal and ictal discharges, particularly as distinct from so-called "normal variants" that can be abundant. Sleep and drowsy states of the brain can generate "vertex waves," "K-complexes," "positive occipital sharp transients of sleep" (POSTS), and "wickets," to name a few variants, none of which are epileptic. A good overview of terminology and application can be found, for example, on the Medscape website, Epileptiform Discharges.

With this caveat, we nonetheless give an overview of the processing approach. Although automation has been proposed for decades, "spike hunting" is often done by manual inspection of the recorded EEG waveforms (whether scalp, subdural, or depths). The classic scalp sensor arrangement is the International 10-20 System (Wikipedia Site, Bioelectromagnetism Book, Chapter 13.3) arranged at 10 percent and 20 percent distances about the circumference of the head. Each of these 21 electrodes is acquired with respect to some reference (as all potentials must be). In reviewing the recordings, however, several "montages" are traditionally recommended that digitally "re-reference" the original recordings into new linear combinations of electrodes.

A classic montage is the "double banana" (Google Search) which emphasizes local changes in the scalp EEG by forming sequential bipolar pairs, such as "Fp1-F3", "F3-C3." Because F3 is found twice in this montage and of opposite sign, then an epileptic spike centered under F3 will appear as a reversed polarity in these two channels, a visual cue the trained epileptologist seeks when rapidly scanning through hours of recordings. This montage is more formally known as "LB-18.3" or "Longitudinal Bipolar 3" in the nomenclature of the American Clinical Neurophysiology Society (ACNS) Guidelines (see References Below).

ACNS guidelines suggest using both "longitudinal" and "transversal" bipolar montages to survey your data. For temporal epilepsy cases, you may also add a "temporal ring" montage. European neurologists often prefer to review the recordings using an average reference montage. Brainstorm provides several variations of all these montages, allows the users full flexibility in creating their own, and can run different montages simultaneously in multiple windows.

The user has to step along through the data, look for abnormal brain activity, then use Brainstorm's event markers to tag suspect intervals.With the suspected events marked and saved, the user can return later to perform source analyses on these intervals. With this brief overview, we detail below an exercise with the sample epilepsy data.

Note that the aim of this tutorial is not to not train you to the spike recognition itself, but rather to illustrate how to manipulate the Brainstorm interface to build a an environment adapted to this task. The data reviewing should be done by clinical neurophysiologists or experienced persons with special training.

References

Dümpelmann M, Ball T, Schulze-Bonhage A (2011)
sLORETA allows reliable distributed source reconstruction based on subdural strip and grid recordings. Human Brain Mapping.

Palmini A, Najm I, Avanzini G, Babb T, Guerrini R, Foldvary-Schaefer N, Jackson G, Luders HO, Prayson R, Spreafico R, Vinters HV (2004) Terminology and classification of the cortical dysplasias.
Neurology, 62:S2-8.

Standard montages recommended by the American Clinical Neurophysiology Society:

Download and installation

Import the anatomy

Without the individual MRI

If you do not have access to an individual MR scan of the subject (or if its quality is too low to be processed with FreeSurfer), but if you have digitized the head shape of the subject using a tracking system, you have an alternative: deform one of the Brainstorm templates (Colin27 or ICBM152) to match the shape of the subject's head.
For more information, read the following tutorial: Warping default anatomy

Access the recordings

Prepare the channel file

Register electrodes with MRI

Review EEG recordings

Import the spike markers

Some spikes were marked by the epileptologists at the Epilepsy Center in Freiburg with Brainstorm and saved in an external text file. We are going to import this file manually.

Display the recordings in one montage

reviewall.gif

Frequency filters

Go to the Filter tab to enable some display frequency filters. General recommendations are:

Time and amplitude resolution

The resolutions of the time and amplitude axes has a lot of importance for the visual detection of epileptic spikes. The shapes we are looking for are altered by the horizontal and vertical scaling. The distance unit on a screen is the pixel, we can set how much time is represented by one pixel horizontally and how much amplitude is represented by one pixel vertically.

In the Brainstorm interface, this resolution is usually set implicitly: you can set the size of the window, the duration or recordings reviewed at once (text box "duration" in tab Record) and the maximum amplitude to show in the figure (buttons [...] and [AS] on the right of the time series figure). From there, you can also zoom in time ([<], [>], mouse wheel) or amplitude ([^], [v], Shift+mouse wheel). Those parameters are convenient to explore the recordings interactively but don't allow us to have reproducible displays with constant time and amplitude resolutions.

To set the figure resolution explicitly: right-click on the figure > Figure > Set axes resolution. Note that this interface does not store the input values, it just modifies the other parameters (figure size, time window, max amplitude) to fit the resolution objectives. Then if you modify those parameters (resize the figure, leave the button [AS] selected and scroll in time, etc) the resolution is lost, you have to set it again manually.

Recommendations for this dataset are:

User setups

This preparation of the reviewing environment requires a large number of operations, and would become quickly annoying if you have to repeat it every time you open a file. This is a good time to use the menu "User setups" to save this window configuration, to reload it in one click later. In the menu "Window layout", at the top-right of the Brainstorm window, select User setup > New setup. Enter a name of your choice for this particular window arrangement.

This operation will also disable the automatic window arrangement (Window layout > None). To reload it later, open one figure on the dataset you want to review and then select your new entry in the User setup menu.

Multiple montages

It may be interesting for some cases to display different groups of sensors in multiple windows (eg. with an MEG system with 300 sensors), or some complicated epilepsy cases where you would like to review at the same time multiple montages (eg. longitudinal and transversal bipolar montages). Brainstorm offers a flexible way of doing this.

reviewall2.gif

Mark spikes

In this dataset, some single spikes have already been identified by experts at the University Hospital of Freiburg. You can see that 58 SPIKE events are available in the Record tab. Click on a few of them and try to identify the shape of the spike.

The procedure if you are marking the events by yourself is the following:

Pre-process recordings

Evaluation

Two of the typical pre-processing steps consist in get rid of the contamination due to the power lines (50 Hz or 60Hz) and of the frequencies we are not interested in (a low-pass filter to remove the high-frequencies and a high-pass filter to remove the very slow components of the signals). Let's start with the spectral evaluation of this file.

High-pass filter

We would like to apply a 0.5Hz high-pass filter to the entire file in order to get rid of the long amplitude fluctuations (longer than 2s). With some MEG file formats, Brainstorm supports the creation of new filtered files in native formats, which means that you can drag and grop directly the "Link to raw file" to the Process1 tab and run the band-pass filter process. Unfortunately, this is currently not supported for the file format we are currently working on (Deltamed Coherence-Neurofile). There is an alternative option which consists in importing the entire continuous file in the database in one single block, then run the filter on it. This approach works is possible only on rather small files (4 * file size < memory on the computer). Here the file size is less than 80 Mb, so it can be easily processed this way.

Epoching and averaging

Import recordings

Average spikes

Source analysis: Cortically constrained

Head model

Noise covariance matrix

Inverse model

Regions of interest

Z-score normalization

A good way to reveal better the source activity at the cortex level, we can calculate a Z-score of the source maps with respect with a quiet baseline. We can use the same baseline as for the calculation of the noise covariance matrix.

=> SCREEN CAPTURES

Source analysis: Full head volume

If the results you obtain are not satisfying with the surface-based source estimation, you can run again the same analysis with a different source space, sampling the entire head volume instead of being contrained to the surface. More information about this method in the Volume source estimation tutorial.

Head model

Inverse model

Moving dipoles

See tutorial: Computing and displaying dipoles

Note: you can also load dipoles calculated with other programs.

MEM inverse solution

Coming soon...

Discussion

Distributed source models vs. ECD (equivalent current dipole)

Kobayashi K, Yoshinaga H, Ohtsuka Y, Gotman J (2005)
Dipole modeling of epileptic spikes can be accurate or misleading
Epilepsia, 2005 Mar;46(3):397-408.

Distributed source models vs. BOLD

Heers M, Hedrich T, An D, Dubeau F, Gotman J, Grova C, Kobayashi E (2014)
Spatial correlation of hemodynamic changes related to interictal epileptic discharges with electric and magnetic source imaging. Human Brain Mapping [in press].

ECD vs. BOLD

Benar CG, Grova C, Kobayashi E, Bagshaw AP, Aghakhani Y, Dubeau F, Gotman J (2006)
EEG–fMRI of epileptic spikes: Concordance with EEG source localization and intracranial EEG
NeuroImage, 30:1161-1170.

Scripting

To reproduce this entire analysis with a script, use the following processes:

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Tutorials/EpilepsyOld (last edited 2014-02-26 16:48:35 by agrippa)