Locating chronically implanted subdural electrodes using surface reconstruction

Advances in human intracranial electroencephalography research, guidelines and good practices

Since the second-half of the twentieth century, intracranial electroencephalography (iEEG), including both electrocorticography (ECoG) and stereo-electroencephalography (sEEG), has provided an intimate view into the human brain. At the interface between fundamental research and the clinic, iEEG provides both high temporal resolution and high spatial specificity but comes with constraints, such as the individual's tailored sparsity of electrode sampling. Over the years, researchers in neuroscience developed their practices to make the most of the iEEG approach. Here we offer a critical review of iEEG research practices in a didactic framework for newcomers, as well addressing issues encountered by proficient researchers. The scope is threefold: (i) review common practices in iEEG research, (ii) suggest potential guidelines for working with iEEG data and answer frequently asked questions based on the most widespread practices, and (iii) based on current neurophysiological knowledge and methodologies, pave the way to good practice standards in iEEG research. The organization of this paper follows the steps of iEEG data processing. The first section contextualizes iEEG data collection. The second section focuses on localization of intracranial electrodes. The third section highlights the main pre-processing steps. The fourth section presents iEEG signal analysis methods. The fifth section discusses statistical approaches. The sixth section draws some unique perspectives on iEEG research. Finally, to ensure a consistent nomenclature throughout the manuscript and to align with other guidelines, e.g., Brain Imaging Data Structure (BIDS) and the OHBM Committee on Best Practices in Data Analysis and Sharing (COBIDAS), we provide a glossary to disambiguate terms related to iEEG research.

Validating Patient-Specific Finite Element Models of Direct Electrocortical Stimulation

Direct electrocortical stimulation (DECS) with electrocorticography electrodes is an established therapy for epilepsy and an emerging application for stroke rehabilitation and brain-computer interfaces. However, the electrophysiological mechanisms that result in a therapeutic effect remain unclear. Patient-specific computational models are promising tools to predict the voltages in the brain and better understand the neural and clinical response to DECS, but the accuracy of such models has not been directly validated in humans. A key hurdle to modeling DECS is accurately locating the electrodes on the cortical surface due to brain shift after electrode implantation. Despite the inherent uncertainty introduced by brain shift, the effects of electrode localization parameters have not been investigated. The goal of this study was to validate patient-specific computational models of DECS against in vivo voltage recordings obtained during DECS and quantify the effects of electrode localization parameters on simulated voltages on the cortical surface. We measured intracranial voltages in six epilepsy patients during DECS and investigated the following electrode localization parameters: principal axis, Hermes, and Dykstra electrode projection methods combined with 0, 1, and 2 mm of cerebral spinal fluid (CSF) below the electrodes. Greater CSF depth between the electrode and cortical surface increased model errors and decreased predicted voltage accuracy. The electrode localization parameters that best estimated the recorded voltages across six patients with varying amounts of brain shift were the Hermes projection method and a CSF depth of 0 mm (r = 0.92 and linear regression slope = 1.21). These results are the first to quantify the effects of electrode localization parameters with in vivo intracranial recordings and may serve as the basis for future studies investigating the neuronal and clinical effects of DECS for epilepsy, stroke, and other emerging closed-loop applications.

Clinical safety of intracranial EEG electrodes in MRI at 1.5 T and 3 T: a single-center experience and literature review

PURPOSE

Intracranial electroencephalography (EEG) can be a critical part of presurgical evaluation for drug resistant epilepsy. With the increasing use of intracranial EEG, the safety of these electrodes in the magnetic resonance imaging (MRI) environment remains a concern, particularly at higher field strengths. However, no studies have reported the MRI safety experience of intracranial electrodes at 3 T. We report an MRI safety review of patients with intracranial electrodes at 1.5 and 3 T.

METHODS

One hundred and sixty-five consecutive admissions for intracranial EEG monitoring were reviewed. A total of 184 MRI scans were performed on 135 patients over 140 admissions. These included 118 structural MRI studies at 1.5 T and 66 functional MRI studies at 3 T. The magnetic resonance (MR) protocols avoided the use of high specific energy absorption rate sequences that could result in electrode heating. The intracranial implantations included 114 depth, 15 subdural, and 11 combined subdural and depth electrodes. Medical records were reviewed for patient-reported complications and radiologic complications related to these studies. Pre-implantation, post-implantation, and post-explantation imaging studies were reviewed for potential complications.

RESULTS

No adverse events or complications were seen during or after MRI scanning at 1.5 or 3 T apart from those attributed to electrode implantation. There was also no clinical or imaging evidence of worsening of pre-existing implantation-related complications after MR imaging.

CONCLUSION

No clinical or radiographic complications are seen when performing MRI scans at 1.5 or 3 T on patients with implanted intracranial EEG electrodes while avoiding high specific energy absorption rate sequences.

Enhanced co-registration methods to improve intracranial electrode contact localization

Background

Electrode contact locations are important when planning tailored brain surgeries to identify pathological tissue targeted for resection and conversely avoid eloquent tissue. Current methods employ trained experts to use neuroimaging scans that are manually co-registered and localize contacts within ~2 mm. Yet, the state of the art is limited by either the expertise needed for each type of intracranial electrode or the inter-modality co-registration which increases error, reducing accuracy. Patients often have a variety of strips, grids and depths implanted; therefore, it is cumbersome and time-consuming to apply separate localization methods for each type of electrode, requiring expertise across different approaches.

New method

To overcome these limitations, a computational method was developed by separately registering an implant magnetic resonance image (MRI) and implant computed tomography image (CT) to the pre-implant MRI, then calculating an iterative closest point transformation using the contact locations extracted from the signal voids as ground truth.

Results

The implant MRI is robustly co-registered to the pre-implant MRI with a boundary-based registration algorithm. By extracting and utilizing ‘signal voids’ (the metal induced artifacts from the implant MRI) as electrode fiducials, the novel method is an all-in-one approach for all types of intracranial electrodes while eliminating inter-modality co-registration errors.

Comparison with existing methods

The distance between each electrode centroid and the brain's surface was measured, for the proposed method as well as the state of the art method using two available software packages, SPM 12 and FSL 4.1. The method presented here achieves the smallest distances to the brain's surface for all strip and grid type electrodes, i.e. contacts designed to rest directly on the brain surface.

Conclusion

We use one of the largest reported sample sizes in localization studies to validate this novel method for localizing different kinds of intracranial electrodes including grids, strips and depth electrodes.

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Co-registration between intramodal pre- and implant images allows for accurate localization of all subdural electrode types.

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Iterative closest point (ICP) assisted grid electrode localization is comparable to existing implant MRI based methods.

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ICP is a novel, semi-automated method to localize grid, strip and depth electrodes with state-of-the-art accuracy

Surface based electrode localization and standardized regions of interest for intracranial EEG

Intracranial recordings captured from subdural electrodes in patients with drug resistant epilepsy offer clinicians and researchers a powerful tool for examining neural activity in the human brain with high spatial and temporal precision. There are two major challenges, however, to interpreting these signals both within and across individuals. Anatomical distortions following implantation make accurately identifying the electrode locations difficult. In addition, because each implant involves a unique configuration, comparing neural activity across individuals in a standardized manner has been limited to broad anatomical regions such as cortical lobes or gyri. We address these challenges here by introducing a semi-automated method for localizing subdural electrode contacts to the unique surface anatomy of each individual, and by using a surface-based grid of regions of interest (ROIs) to aggregate electrode data from similar anatomical locations across individuals. Our localization algorithm, which uses only a postoperative CT and preoperative MRI, builds upon previous spring-based optimization approaches by introducing manually identified anchor points directly on the brain surface to constrain the final electrode locations. This algorithm yields an accuracy of 2 mm. Our surface-based ROI approach involves choosing a flexible number of ROIs with different spatial resolutions. ROIs are registered across individuals to represent identical anatomical locations while accounting for the unique curvature of each brain surface. This ROI based approach therefore enables group level statistical testing from spatially precise anatomical regions.

Automatic and Precise Localization and Cortical Labeling of Subdural and Depth Intracranial Electrodes

Object: Subdural or deep intracerebral electrodes are essential in order to precisely localize epileptic zone in patients with medically intractable epilepsy. Precise localization of the implanted electrodes is critical to clinical diagnosing and treatment as well as for scientific studies. In this study, we sought to automatically and precisely extract intracranial electrodes using pre-operative MRI and post-operative CT images.

Method: The subdural and depth intracranial electrodes were readily detected using clustering-based segmentation. Depth electrodes were tracked by fitting a quadratic curve to account for potential bending during the neurosurgery. The identified electrodes can be manipulated using a graphic interface and labeled to cortical areas in individual native space based on anatomical parcellation and displayed in the volume and surface space.

Results: The electrodes' localizations were validated with high precision. The electrode coordinates were normalized to a standard space. Moreover, the probabilistic value being to a specific area or a functional network was provided.

Conclusions: We developed an integrative toolbox to reconstruct and label the intracranial electrodes implanted in the patients with medically intractable epilepsy. This toolbox provided a convenient way to allow inter-subject comparisons and relation of intracranial EEG findings to the larger body of neuroimaging literature.

Registering imaged ECoG electrodes to human cortex: A geometry-based technique

BACKGROUND

The accurate localization of implanted ECoG electrodes over the brain is of critical importance to invasive diagnostic work-up for the surgical treatment of intractable epileptic seizures. The implantation of subdural electrodes is an invasive procedure which typically introduces non-uniform deformations of a subject's brain, increasing the difficulty of determining the precise location of the electrodes vis-à-vis cortex. Formalization of this problem is used to define a novel solution for the optimal localization of subdural electrodes.

NEW METHOD

We demonstrate that nonlinear transformation is required to accurately register the implanted electrodes to the non-deformed pre-surgical cortical surface, and that this problem is accommodated by utilizing known features of electrode geometry. Techniques to register chronically implanted subdural electrodes to the undistorted brain image are described and evaluated using simulated and clinical data.

RESULTS

Principal Axis, our novel analysis method that estimates an electrode's orientation by the moment of inertia of the solid electrode volume, proved to be the most reliable measure in both the simulated and clinical datasets.

COMPARISON WITH EXISTING METHODS

This method of electrode translation along its principal axis is an improvement over other techniques, such as the limited view provided by intraoperative photography, and the image degradation inherent in post-operative MRI.

CONCLUSIONS

This technique compensates for alterations due to post-operative brain edema, and translates subdural electrodes to their original location on pre-operative MRI 3D models. This is helpful in the correct localization of seizure foci and functional mapping of epilepsy patients.

An open-source automated platform for three-dimensional visualization of subdural electrodes using CT-MRI coregistration

OBJECTIVE

Visualizing implanted subdural electrodes in three-dimensional (3D) space can greatly aid in planning, executing, and validating resection in epilepsy surgery. Coregistration software is available, but cost, complexity, insufficient accuracy, or validation limit adoption. We present a fully automated open-source application, based on a novel method using postimplant computerized tomography (CT) and postimplant magnetic resonance (MR) images, for accurately visualizing intracranial electrodes in 3D space.

METHODS

CT-MR rigid brain coregistration, MR nonrigid registration, and prior-based segmentation were carried out on seven patients. Postimplant CT, postimplant MR, and an external labeled atlas were then aligned in the same space. The coregistration algorithm was validated by manually marking identical anatomic landmarks on the postimplant CT and postimplant MR images. Following coregistration, distances between the center of the landmark masks on the postimplant MR and the coregistered CT images were calculated for all subjects. Algorithms were implemented in open-source software and translated into a "drag and drop" desktop application for Apple Mac OS X.

RESULTS

Despite postoperative brain deformation, the method was able to automatically align intrasubject multimodal images and segment cortical subregions, so that all electrodes could be visualized on the parcellated brain. Manual marking of anatomic landmarks validated the coregistration algorithm with a mean misalignment distance of 2.87 mm (standard deviation 0.58 mm)between the landmarks. Software was easily used by operators without prior image processing experience.

SIGNIFICANCE

We demonstrate an easy to use, novel platform for accurately visualizing subdural electrodes in 3D space on a parcellated brain. We rigorously validated this method using quantitative measures. The method is unique because it involves no preprocessing, is fully automated, and freely available worldwide. A desktop application, as well as the source code, are both available for download on the International Epilepsy Electrophysiology Portal (https://www.ieeg.org) for use and interactive refinement.

Rapid and efficient localization of depth electrodes and cortical labeling using free and open source medical software in epilepsy surgery candidates

Depth intracranial electrodes (IEs) placement is one of the most used procedures to identify the epileptogenic zone (EZ) in surgical treatment of drug resistant epilepsy patients, about 20–30% of this population. IEs localization is therefore a critical issue defining the EZ and its relation with eloquent functional areas. That information is then used to target the resective surgery and has great potential to affect outcome. We designed a methodological procedure intended to avoid the need for highly specialized medical resources and reduce time to identify the anatomical location of IEs, during the first instances of intracranial EEG recordings. This workflow is based on established open source software; 3D Slicer and Freesurfer that uses MRI and Post-implant CT fusion for the localization of IEs and its relation with automatic labeled surrounding cortex. To test this hypothesis we assessed the time elapsed between the surgical implantation process and the final anatomical localization of IEs by means of our proposed method compared against traditional visual analysis of raw post-implant imaging in two groups of patients. All IEs were identified in the first 24 H (6–24 H) of implantation using our method in 4 patients of the first group. For the control group; all IEs were identified by experts with an overall time range of 36 h to 3 days using traditional visual analysis. It included (7 patients), 3 patients implanted with IEs and the same 4 patients from the first group. Time to localization was restrained in this group by the specialized personnel and the image quality available. To validate our method; we trained two inexperienced operators to assess the position of IEs contacts on four patients (5 IEs) using the proposed method. We quantified the discrepancies between operators and we also assessed the efficiency of our method to define the EZ comparing the findings against the results of traditional analysis.

Recursive grid partitioning on a cortical surface model: an optimized technique for the localization of implanted subdural electrodes

Object

Precise localization of subdural electrodes (SDEs) is essential for the interpretation of data from intracranial electrocorticography recordings. Blood and fluid accumulation underneath the craniotomy flap leads to a nonlinear deformation of the brain surface and of the SDE array on postoperative CT scans and adversely impacts the accurate localization of electrodes located underneath the craniotomy. Older methods that localize electrodes based on their identification on a postimplantation CT scan with coregistration to a preimplantation MR image can result in significant problems with accuracy of the electrode localization. The authors report 3 novel methods that rely on the creation of a set of 3D mesh models to depict the pial surface and a smoothed pial envelope. Two of these new methods are designed to localize electrodes, and they are compared with 6 methods currently in use to determine their relative accuracy and reliability.

Methods

The first method involves manually localizing each electrode using digital photographs obtained at surgery. This is highly accurate, but requires time intensive, operator-dependent input. The second uses 4 electrodes localized manually in conjunction with an automated, recursive partitioning technique to localize the entire electrode array. The authors evaluated the accuracy of previously published methods by applying the methods to their data and comparing them against the photograph-based localization. Finally, the authors further enhanced the usability of these methods by using automatic parcellation techniques to assign anatomical labels to individual electrodes as well as by generating an inflated cortical surface model while still preserving electrode locations relative to the cortical anatomy.

Results

The recursive grid partitioning had the least error compared with older methods (672 electrodes, 6.4-mm maximum electrode error, 2.0-mm mean error, p < 10−18). The maximum errors derived using prior methods of localization ranged from 8.2 to 11.7 mm for an individual electrode, with mean errors ranging between 2.9 and 4.1 mm depending on the method used. The authors also noted a larger error in all methods that used CT scans alone to localize electrodes compared with those that used both postoperative CT and postoperative MRI. The large mean errors reported with these methods are liable to affect intermodal data comparisons (for example, with functional mapping techniques) and may impact surgical decision making.

Conclusions

The authors have presented several aspects of using new techniques to visualize electrodes implanted for localizing epilepsy. The ability to use automated labeling schemas to denote which gyrus a particular electrode overlies is potentially of great utility in planning resections and in corroborating the results of extraoperative stimulation mapping. Dilation of the pial mesh model provides, for the first time, a sense of the cortical surface not sampled by the electrode, and the potential roles this “electrophysiologically hidden” cortex may play in both eloquent function and seizure onset.

Localization of dense intracranial electrode arrays using magnetic resonance imaging

Intracranial electrode arrays are routinely used in the pre-surgical evaluation of patients with medically refractory epilepsy, and recordings from these electrodes have been increasingly employed in human cognitive neurophysiology due to their high spatial and temporal resolution. For both researchers and clinicians, it is critical to localize electrode positions relative to the subject-specific neuroanatomy. In many centers, a post-implantation MRI is utilized for electrode detection because of its higher sensitivity for surgical complications and the absence of radiation. However, magnetic susceptibility artifacts surrounding each electrode prohibit unambiguous detection of individual electrodes, especially those that are embedded within dense grid arrays. Here, we present an efficient method to accurately localize intracranial electrode arrays based on pre- and post-implantation MR images that incorporates array geometry and the individual's cortical surface. Electrodes are directly visualized relative to the underlying gyral anatomy of the reconstructed cortical surface of individual patients. Validation of this approach shows high spatial accuracy of the localized electrode positions (mean of 0.96 mm ± 0.81 mm for 271 electrodes across 8 patients). Minimal user input, short processing time, and utilization of radiation-free imaging are strong incentives to incorporate quantitatively accurate localization of intracranial electrode arrays with MRI for research and clinical purposes. Co-registration to a standard brain atlas further allows inter-subject comparisons and relation of intracranial EEG findings to the larger body of neuroimaging literature.

Individualized localization and cortical surface-based registration of intracranial electrodes

In addition to its widespread clinical use, the intracranial electroencephalogram (iEEG) is increasingly being employed as a tool to map the neural correlates of normal cognitive function as well as for developing neuroprosthetics. Despite recent advances, and unlike other established brain-mapping modalities (e.g. functional MRI, magneto- and electroencephalography), registering the iEEG with respect to neuroanatomy in individuals-and coregistering functional results across subjects-remains a significant challenge. Here we describe a method which coregisters high-resolution preoperative MRI with postoperative computerized tomography (CT) for the purpose of individualized functional mapping of both normal and pathological (e.g., interictal discharges and seizures) brain activity. Our method accurately (within 3mm, on average) localizes electrodes with respect to an individual's neuroanatomy. Furthermore, we outline a principled procedure for either volumetric or surface-based group analyses. We demonstrate our method in five patients with medically-intractable epilepsy undergoing invasive monitoring of the seizure focus prior to its surgical removal. The straight-forward application of this procedure to all types of intracranial electrodes, robustness to deformations in both skull and brain, and the ability to compare electrode locations across groups of patients makes this procedure an important tool for basic scientists as well as clinicians.

Three-dimensional visualization of subdural electrodes for presurgical planning

BACKGROUND

Accurate localization and visualization of subdural electrodes implanted for intracranial electroencephalography in cases of medically refractory epilepsy remains a challenging clinical problem.

OBJECTIVE

We introduce a technique for creating accurate 3-dimensional (3D) brain models with electrode overlays, ideal for resective surgical planning.

METHODS

Our procedure uses postimplantation magnetic resonance imaging (MRI) and computed tomographic (CT) imaging to create 3D models of compression-affected brain combined with intensity-thresholded CT-derived electrode models using freely available software. Footprints, or "shadows," beneath electrodes are also described for better visualization of sulcus-straddling electrodes. Electrode models were compared with intraoperative photography for validation.

RESULTS

Realistic representations of intracranial electrode positions on patient-specific postimplantation MRI brain renderings were reliably created and proved accurate when compared with photographs. Electrodes placed interhemispherically were also visible with our rendering technique. Electrode shadows were useful in locating electrodes that straddle sulci.

CONCLUSION

We present an accurate method for visualizing subdural electrodes on brain compression effected 3D models that serves as an ideal platform for surgical planning.

ECoG gamma activity during a language task: differentiating expressive and receptive speech areas

Electrocorticographic (ECoG) spectral patterns obtained during language tasks from 12 epilepsy patients (age: 12-44 years) were analysed in order to identify and characterize cortical language areas. ECoG from 63 subdural electrodes (500 Hz/channel) chronically implanted over frontal, parietal and temporal lobes were examined. Two language tasks were performed. During the first language task, patients listened to a series of 50 words preceded by warning tones, and were asked to repeat each word. During a second memory task, subjects heard the 50 words from the first task randomly mixed with 50 new words and were asked to repeat the word only if it was a new word. Increases in ECoG gamma power (70-100 Hz) were observed in response to hearing tones (primary auditory cortex), hearing words (posterior temporal and parietal cortex) and repeating words (lateral frontal and anterior parietal cortex). These findings were compared to direct electrical stimulation and separate analysis of ECoG gamma changes during spontaneous inter-personal conversations. The results indicate that high-frequency ECoG reliably differentiates cortical areas associated with receptive and expressive speech processes for individual patients. Compared to listening to words, greater frontal lobe and decreased temporal lobe gamma activity was observed while speaking. The data support the concept of distributed functionally specific language modules interacting to serve receptive and expressive speech, with frontal lobe 'corollary discharges' suppressing low-level receptive cortical language areas in the temporal lobe during speaking.

Localization of neurosurgically implanted electrodes via photograph-MRI-radiograph coregistration

Intracranial electroencephalography (iEEG) is clinically indicated for medically refractory epilepsy and is a promising approach for developing neural prosthetics. These recordings also provide valuable data for cognitive neuroscience research. Accurate localization of iEEG electrodes is essential for evaluating specific brain regions underlying the electrodes that indicate normal or pathological activity, as well as for relating research findings to neuroimaging and lesion studies. However, electrodes are frequently tucked underneath the edge of a craniotomy, inserted via a burr hole, or placed deep within the brain, where their locations cannot be verified visually or with neuronavigational systems. We show that one existing method, registration of postimplant computed tomography (CT) with preoperative magnetic resonance imaging (MRI), can result in errors exceeding 1cm. We present a novel method for localizing iEEG electrodes using routinely acquired surgical photographs, X-ray radiographs, and magnetic resonance imaging scans. Known control points are used to compute projective transforms that link the different image sets, ultimately allowing hidden electrodes to be localized, in addition to refining the location of manually registered visible electrodes. As the technique does not require any calibration between the different image modalities, it can be applied to existing image databases. The final result is a set of electrode positions on the patient's rendered MRI yielding locations relative to sulcal and gyral landmarks on individual anatomy, as well as MNI coordinates. We demonstrate the results of our method in eight epilepsy patients implanted with electrode grids spanning the left hemisphere.

Coregistration of digital photography of the human cortex and cranial magnetic resonance imaging for visualization of subdural electrodes in epilepsy surgery

OBJECTIVE

To develop a method for the coregistration of digital photographs of the human cortex with head magnetic resonance imaging (MRI) scans for invasive diagnostics and resective neocortical epilepsy surgery.

METHODS

Six chronically epileptic patients (two women, four men; mean age, 34 yr; age range, 20-43 yr) underwent preoperative three-dimensional (3D) T1-weighted MRI scans. Digital photographs of the exposed cortex were taken during implantation of subdural grid electrodes. Rendering software (Analyze 3.1; Biomedical Imaging Resource, Mayo Foundation, Rochester, MN) was used to create an MRI-based 3D model of the brain surface. Digital photographs were manually coregistered with the brain surface MRI model using the registration tool in the Analyze software. By matching the digital photograph and the brain surface model, the position of the subdural electrodes was integrated into the coordinate system of the preoperatively acquired 3D MRI dataset.

RESULTS

In all patients, the position of the labeled electrode contacts in relation to the cortical anatomy could be visualized on the 3D models of the cortical surface. At the time of resection, the resulting image of the coregistration process provides a realistic view of the cortex and the position of the subdural electrode.

CONCLUSION

The coregistration of digital photographs of the brain cortex with the results of 3D MRI data sets is possible. This allows for identification of anatomic details underlying the subdural grid electrodes and enhances the orientation of the surgeon.

Frequency Domain Analysis of Human Subdural Recordings

SUMMARY

It is possible to localize many aspects of cortical function and dysfunction without the use of direct electrical stimulation of cortex. This study explores the degree to which information can be obtained about functional cortical organization relative to epileptogenic regions through analysis of electrocorticographic recordings in the frequency domain. Information about the extent of seizure regions and the location of the normal sensory and motor homunculus and some higher language and memory related areas can be obtained through the analysis of task-related power spectrum changes and changes in lateral interelectrode coherence patterns calculated from interictal and ictal recordings.

Mutually suppressive interrelations of symmetric epileptic foci in bitemporal epilepsy and their inhibitory stimulation

OBJECTIVES

The goal of this study is to analyze the suppressive interaction of symmetric temporal lobe epileptic foci, assess some failures of epilepsy surgery, and evaluate the possibility of terminating focal seizures with stimulation of symmetric epileptic foci.

MATERIALS AND METHODS

One hundred and twenty-nine intractable epilepsy patients (age range 6-53 years) with bitemporal epileptiform abnormalities in multiple scalp EEGs were evaluated with chronically implanted depth and subdural electrodes. Interelectrode coherence and power spectra were studied using internally developed software.

RESULTS

Bitemporal epileptic foci were found in 85/129 (66%) patients with reciprocal relations between these foci in 57/85 (67%) patients. Temporal lobectomy was performed for 67/85 patients. 12/67 patients became free of seizures (Engel's Class I), 32/67 improved (Classes II and III), and 23/67 did not improve. 14/23 patients demonstrated post-surgical activation of the contralateral temporal lobe epileptic focus. For 8/14 of these patients, the stereotactic cryoamygdalatomy was performed in the temporal lobe contralateral to the first surgery. 5/8 patients became free of seizures. It was found that stimulation of temporal lobe deep epileptic focus may terminate focal seizures in the contralateral symmetric structures.

CONCLUSION

A mutually suppressive relationship is one of variants of the interaction of symmetric epileptic foci. Some epilepsy surgery failures may be a result of post-surgical activation of the intact focus. The increase of coherence between both temporal lobes before the seizure onset of the seizure suggests the establishment of functional interrelations between two epileptic foci at an early, "hidden" phase of seizures, and may predict the direction of seizure spread. Mutually suppressive interrelations of symmetric epileptic foci might be employed for chronic therapeutic stimulation.