A Review of Electrical Source Imaging

Techniques for source localization
EEG is the most central diagnostic tool for presurgical evaluation of medically intractable focal epilepsy. Typically, multichannel EEG synchronized with video monitoring is performed continuously for several days. The resulting EEG traces (or waveforms) are then analyzed for patterns typical for the patient’s seizures. These patterns are assessed by the examination of the EEG traces during interictal discharges, as well as before, during, and after seizures. In the hands of an experienced epileptologist, this kind of trace analysis has a considerable value in localizing the epileptogenic area of the brain for surgery. However, there are some important limitations to the technique as it has been practiced in the past, and it can result in crude or even incorrect localization.

To obtain sufficient precision for surgery, it is important to use several complementary techniques to more accurately localize the epileptogenic foci. Modern presurgical evaluation centers generally include neurological and neuropsychological exams, high-resolution MRI, PET, and/or interictal and ictal SPECT, and sometimes MRI-based volumetry and spectroscopy in the battery of exams that aim to precisely determine the epileptogenic focus. In cases of unclear or nonconcordant results through these exams, invasive recordings from surgically implanted electrodes are usually needed as well.

Improved source-imaging algorithms greatly increase accuracy of source localization
It has been argued that traditional trace analysis of the EEG only provides a fraction of the information that is available in the signal. With the advent of digitally recorded EEG, advanced analysis of the signals with modern signal processing tools is possible, allowing for much higher accuracy in focus localization. One such approach to electrical source imaging, sometimes called ESI, is the reconstruction of the electrically active areas in the brain based on the surface recordings. Since the introduction of electromagnetic source localization methods, many groups have demonstrated the usefulness of source imaging for localizing the epileptic foci based on EEG or MEG data (Binnie and Stefan, 1999; Ebersole, 1997, 2000b; Fuchs, Wagner, Köhler, and Wischmann, 1999; Hämäläinen, Hari, Ilmoniemi, Knuutila, and Lounesmaa, 1993; Mosher, Baillet, and Leahy, 1999; Patt et al., 2000).

Electrical source imaging has dramatically advanced in recent years. Different source localization algorithms have been used, both dipole localization methods (Boon et al., 2000; Ebersole, 2000a, 2000b; Krings, Chiappa, Cuffin, Buchbinder, and Cosgrove, 1998; Lantz, Ryding, Holub, and Rosén, 1996; Lantz, Ryding, and Rosén, 1997; Merlet et al., 1998; Merlet and Gotman, 1999; Nayak et al., 2004; Oliva et al., 2010; Plummer, Litewka, Farish, Harvey, and Cook, 2007; Plummer, Wagner, Fuchs, Harvey, and Cook, 2010), and distributed inverse solution techniques (Fuchs et al., 1999; Huppertz, Hoegg et al., 2001; Lantz, Grave de Peralta, Gonzalez, and Michel, 2001; Lantz, Michel et al., 1997; Michel et al., 1999; Plummer, Wagner, Fuchs, Harvey et al., 2010; Plummer, Wagner, Fuchs, Vogrin et al., 2010; Seri et al., 1998; Waberski et al., 2000; Zumsteg, Friedman, Wennberg, and Wieser, 2005; Zumsteg, Friedman, Wieser, and Wennberg, 2006). These studies, which were normally performed using a standard clinical electrode setup with up to 30 electrodes, have confirmed that inverse solutions can provide an adequate definition of the epileptogenic zone. In addition, some recent studies have demonstrated the usefulness of simultaneous recording of EEG and fMRI (with subsequent source imaging of the epileptiform activity in EEG) for localizing the epileptic focus (Groening et al., 2009; Siniatchkin et al., 2010; Vulliemoz, Rodionov et al., 2010; Vulliemoz et al., 2009).

Accuracy is improved still further by upgrading to dense array EEG
Even though it has been demonstrated that correct source localization results can be obtained with as few as 30 electrodes in certain simple situations, a more dense sampling of the spatial frequencies of the scalp electric fields leads to a better resolution of the topographic features. This has also been demonstrated, in simulations as well as in real data, and these studies indicate that inter-electrode distances of around 2-3 cm (corresponding to at least 100 electrodes on an adult head) are needed to avoid distortions of the scalp potential distribution (A Gevins, 1990; Spitzer, Cohen, Fabrikant, and Hallett, 1989; Srinivasan, Nunez, Tucker, Silberstein, and Cadusch, 1996; Srinivasan, Tucker, and Murias, 1998). More recent investigations, assuming a different relative conductivity between skull and brain, suggest that even higher channel counts are necessary to adequately sample brain electric fields (Gonçalves, et al, 2003; Gonçalves et al., 2003; Lai et al., 2005; Ryynänen, Hyttinen, and Malmivuo, 2004;Ryynänen, Hyttinen, and Malmivuo, 2006)

In a more clinically oriented study (Lantz, et al., 2003), it was demonstrated that the localization accuracy of interictal epileptiform activity significantly improves when increasing from 32 to 64 recording channels. Increasing from 64 to 128 channels further improved the localization precision, but less significantly. This study has recently been repeated using a more accurate head model (Finite Difference Model), and with more realistic values for brain/skull conductivity differences (Lantz et al, 2009). The results of this study indicate that improvement in localization accuracy will occur up to at least 256 electrodes.

This number of electrodes has previously been difficult to reach in normal clinical practice due to the considerable work of gluing the electrodes to the patient’s scalp. Magnetoencephalographic (MEG) recordings are easier in this respect, since whole head systems with more than 100 sensors are available. Therefore, several groups have proposed to include whole head MEG recordings as a tool in presurgical epilepsy evaluation either alone (Baumgartner, et al., 2000; Paetau et al., 1992; Stefan et al., 2000; Wheless et al., 1999) or in combination with EEG source imaging (Ebersole and Ebersole, 2010; Tanaka et al., 2010; Wennberg, Valiante, and Cheyne, 2011). However, since the difference between EEG and MEG in localization precision is probably negligible if the same number of channels is recorded (Anogianakis et al., 1992; Cohen et al., 1990; Malmivuo, Suihko, and Eskola, 1997), it is technically, as well as economically, more practical to use the new high-resolution EEG systems, which allow the application of 128- to 256-EEG electrodes in less than 10 minutes. Several studies with 64 channel (Herrendorf et al., 2000; Huppertz, Hof et al., 2001; Waberski et al., 2000; Wang, Worrell, Yang, Wilke, and He, 2010) or 128- and 256-channel EEG systems (Brodbeck, Lascano, Spinelli, Seeck, and Michel, 2009; Brodbeck et al., 2010; Lantz, Grave de Peralta et al., 2003; Lantz, Spinelli et al., 2003; Michel, Lantz et al., 2004; Sperli et al., 2006), demonstrate the high spatial precision of epileptic focus localization that can be reached with these techniques.

Dense array EEG can also be used to localize ictal patterns
Source imaging of ictal patterns is a complicated task. Only a few studies have been published using surface EEG to quantitatively localize ictal foci. In two related studies, using dipole modelling on 25-channel ictal data, Assaf and Ebersole (1997) were able to demonstrate a clear relationship between dipole orientations and intracranial ictal onset in temporal lobe patients (Assaf and Ebersole, 1997), as well as between dipole orientations and postoperative outcome in the same patient category (Assaf and Ebersole, 1999). In these two ictal studies individual waves in the time domain EEG were used for the source-imaging analysis. More quantitative approaches, such as principle component analysis (Stern et al., 2009), full-scalp frequency analysis (Blanke et al., 2000; Lantz et al., 1999; Lee et al., 2009; Michel et al., 1999) or temporal segmentation (Lantz, Michel et al., 2001) have also been used in combination with different source-imaging algorithms.

In all the aforementioned studies, a standard clinical electrode setup with 20-30 electrodes was used. In another study using 64 channels (Koessler et al., 2010), the surface ictal patterns were compared to stereroelectroencephalography (SEEG), and a high level of agreement between EEG source localizations and the SEEG was obtained. Recently, the group of Holmes et al. has presented source-imaging results for epileptic seizures recorded with 128 or 256 channels. It has been demonstrated (Holmes, Brown and Tucker, 2004; Holmes, Quiring and Tucker, 2009) that so-called primary generalized seizures, such as absence seizures or seizures in juvenile myoclonic epilepsy, are not truly "generalized," with immediate global cortical involvement, but rather involve selective cortical networks including frontal and temporal regions. The same group also used high density EEG to capture seizures during clinical long term monitoring (LTM) investigations in more than 40 patients with pharmaco-resistant epilepsy, and in some cases confirmed the localization results with intracranial recordings (Holmes, 2008; Holmes et al., 2008; Holmes et al., 2010), thus demonstrating the usefulness of this technique for these purposes.

Techniques for defining functionally important brain areas
The presurgical workup and the planning of a resection of the epileptogenic zone not only involves the precise localization of the area which generates the seizures, but also areas whose resection is likely to result in an unacceptable neurological deficit. The most important areas in this respect are those involved in hand motor, visual, and language functions. Although deficits related to damage in these areas can generally be avoided based on anatomical considerations (Blume, 1993; Falconer, 1971; Lesser, Arroyo, Crone, and Gordon, 1998; Ojemann et al., 1993), many patients end up with major deficiencies, and more direct methods of defining functional relevant areas in the individual brain are needed.

The most used technique in presurgical workups for defining essential areas in individual patients is electrical cortical stimulation (ECS) complemented with intracranial evoked potentials (EPs). ECS may be carried out by stimulation in the operating room (Ojemann et al, 1989; Ojemann et al., 1993; Penfield and Jasper, 1954), or by the use of chronically implanted subdural electrodes (Lesser et al., 1998; Lesser et al., 1987). Functional MRI is a promising technique because of its high spatial resolution in individual subjects, and studies using fMRI to delineate motor areas in surgical candidates have already been presented (Nimsky et al., 1999; Schulder et al., 1999). However, for more complex functions, such as language, fMRI usually shows activation of many different parts of the brain, and the particular relevance of the different areas is not easy to determine.

High density EEG recordings combined with source localizations represent an alternative for mapping human brain functions. Because of the high temporal resolution of EEG, the activity can be followed in real time and attentional, perceptual, cognitive, and motor functions can be separated because they are likely to appear at slightly different moments in time after stimulus presentation. In this way, electromagnetic source imaging of the signals recorded during sensory, cognitive and motor tasks allows to unravel the temporal dynamics of cognitive networks without having to rely on subtraction techniques (Gevins, et al., 1999). The high spatial precision of these techniques, at least concerning the sensorimotor cortex, has been demonstrated in several studies (Ganslandt et al., 1999; Ganslandt et al., 1997; Morioka et al., 1998; Morioka et al., 1995; Rezai et al., 1997).

For a more comprehensive description of the subject, see Michel et al (2004), Plummer, Harvey and Cook (2008), Barkley (2004), Baumgartner (2004) and Vulliemoz et al (2010).
 

Review articles

Barkley, G.L. (2004). Controversies in neurophysiology: MEG is superior to EEG in localization of interictal epileptiform activity: Pro. Clinical Neurophysiology, 115, 1001-1009.

Baumgartner, C. (2004). Controversies in clinical neurophysiology. MEG is superior to EEG in the localization of interictal epileptiform activity. Con. Clinical Neurophysiology 2004, 115, 1010-1020. 

Michel, C.M., Murray, M., Lantz, G., Gonzalez, S., Spinelli, L., Grave de Peralta, R. (2004). EEG source imaging. Clinical Neurophysiology, 115, 2195-2222. 

Plummer, C., Harvey, A.S., Cook M. (2008). EEG source localization in focal epilepsy: where are we now? Epilepsia, 49, 201-218. 

Vulliemoz, S., Lemieux, L., Daunizeau, J., Michel, C.M., Duncan, J.S. (2010a) The combination of EEG source imaging and EEG-correlated functional MRI to map epileptic networks. Epilepsia, 51, 491-505. 

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