Targeted density electrode placement achieves high concordance with traditional high-density EEG for electrical source imaging in epilepsy.

OBJECTIVE: High-density (HD) electroencephalography (EEG) is increasingly used in presurgical epilepsy evaluation, but it is demanding in time and resources. To overcome these issues, we compared EEG source imaging (ESI) solutions with a targeted density and HD-EEG montage. METHODS: HD-EEGs from patients undergoing presurgical evaluation were analyzed. A low-density recording was created by selecting the 25 electrodes of a standard montage from the 83 electrodes of the HD-EEG and adding 8-11 electrodes around the electrode with the highest amplitude interictal epileptiform discharges. The ESI solution from this "targeted" montage was compared to that from the HD-EEG using the distance between peak vertices, sublobar concordance and a qualitative similarity measure. RESULTS: Fifty-eight foci of forty-three patients were included. The median distance between the peak vertices of the two montages was 13.2 mm, irrespective of focus' location. Tangential generators (n = 5/58) showed a higher distance than radial generators (p = 0.04). We found sublobar concordance in 54/58 of the foci (93%). Map similarity, assessed by an epileptologist, had a median score of 4/5. CONCLUSIONS: ESI solutions obtained from a targeted density montage show high concordance with those calculated from HD-EEG. SIGNIFICANCE: Requiring significantly fewer electrodes, targeted density EEG allows obtaining similar ESI solutions as traditional HD-EEG montage.

Has recording of seizures become obsolete?

Some patients with medically intractable epilepsy are considered for surgical treatment. In some surgical candidates, the investigation includes the placement of intracerebral electrodes and long-term monitoring to find the region of seizure onset. This region is the primary determinant of the surgical resection but about one-third of patients are not offered surgery after electrode implantation and among those operated only about 55% are seizure free after five years. This paper discusses why the primary reliance on the seizure onset maybe suboptimal and may be in part responsible for the relatively low surgical success rate. It also proposes to consider some interictal markers that may have advantages over seizure onset and may be easier to obtain.

Value of ictal and interictal epileptiform discharges and high frequency oscillations for delineating the epileptogenic zone in patients with focal cortical dysplasia.

OBJECTIVES: There are different neurophysiological markers of the Epileptogenic Zone (EZ), but their sensitivity and specificity for the EZ is not known in Focal Cortical Dysplasia (FCD) patients. METHODS: We studied patients with FCD who underwent stereoelectroencephalography (SEEG) and surgery. We marked in the SEEG: (a) typical and atypical interictal epileptiform patterns, (b) ictal onset patterns, and (c) rates of ripples (80-250 Hz) and fast ripples (FRs) (>250 Hz). High frequency oscillations were marked automatically during one hour of deep sleep. Surgical outcome was defined as good (Engel I) or poor (Engel II-IV). We computed the sensitivity and, as a measure of specificity, the false positive rate to identify the EZ, and compared them across the different neurophysiological markers. RESULTS: We studied 21 patients, 19 with FCD II. Ictal and typical interictal pattern were the markers with highest sensitivity, while the atypical interictal pattern had the lowest. We found no significant difference in specificity among markers. However, there is a tendency that FRs had the lowest false positive rate. CONCLUSION: The typical interictal pattern has the highest sensitivity. The clinical use of FRs is limited by their low sensitivity. SIGNIFICANCE: We suggest to analyze the typical interictal pattern first. FRs should be analyzed in a second step. If, for instance, a focus with FRs and no typical interictal pattern is found, this area could be considered for resection.

Scalp EEG is not a blur: it can see high frequency oscillations although their generators are small.

High frequency oscillations (HFOs) are emerging as biomarkers of epileptogenicity. They have been shown to originate from small brain regions. Surprisingly, spontaneous HFOs can be recorded from the scalp. To understand how is it possible to observe these small events on the scalp, one avenue is the analysis of the cortical correlates at the time of scalp HFOs. Using simultaneous scalp and intracranial recordings of 11 patients, we studied the spatial distribution of scalp events on the cortical surface. For typical interictal epileptiform discharges the subdural distributions were, as expected, spatially extended. On the contrary, for scalp HFOs the subdural maps corresponded to focal sources, consisting of one or a few small spatial extent activations. These topographies suggest that small cortical areas generated the HFOs seen on the scalp. Similar scalp distributions corresponded to distinct distributions on a standard 1 cm subdural grid and averaging similar scalp HFOs resulted in focal subdural maps. The assumption that a subdural grid "sees" everything that contributes to the potential of nearby scalp contacts was not valid for HFOs. The results suggest that these small extent events are spatially undersampled with standard scalp and grid inter-electrode distances. High-density scalp electrode distributions seem necessary to obtain a solid sampling of HFOs on the scalp. A better understanding of the influence of spatial sampling on the observation of high frequency brain activity on the scalp is important for their clinical use as biomarkers of epilepsy.

Influence of contact size on the detection of HFOs in human intracerebral EEG recordings.

OBJECTIVE: High frequency oscillations (HFOs) are brief electroencephalographic events associated with epileptic activity, and likely representing biological markers of the epileptogenic zone. HFOs are usually detected with intracranial EEG and detection is influenced by contact size. The size of commercially available intracerebral electrodes varies widely. This study assesses HFO detection rates from adjacent electrode contacts in human intracerebral recordings. METHODS: Intracerebral recordings were collected from 11 patients undergoing stereoelectroencephalographic investigation using hybrid depth electrodes containing adjacent large (0.8 or 5 mm(2)) and small (0.2 or 0.3 mm(2)) contacts. HFOs were marked manually during 5-min tracings in 131 pairs of adjacent large and small contacts. HFO rates per minute and mean event durations were compared between adjacent contacts. RESULTS: A minimal but statistically significant advantage in ripple detection was found in a subgroup of large contacts. Otherwise, HFO rates and mean event durations were not statistically different between groups. CONCLUSION: The size of clinical contacts within the studied range did not influence HFO detection in a clinically relevant manner. Larger contacts provide a minimal advantage for ripple detection. SIGNIFICANCE: Our findings suggest that commercially available intracerebral electrodes with contacts between 0.2 and 5 mm(2) likely possess similar HFO detection abilities.

Automatic seizure detection in SEEG using high frequency activities in wavelet domain.

Existing automatic detection techniques show high sensitivity and moderate specificity, and detect seizures a relatively long time after onset. High frequency (80-500 Hz) activity has recently been shown to be prominent in the intracranial EEG of epileptic patients but has not been used in seizure detection. The purpose of this study is to investigate if these frequencies can contribute to seizure detection. The system was designed using 30 h of intracranial EEG, including 15 seizures in 15 patients. Wavelet decomposition, feature extraction, adaptive thresholding and artifact removal were employed in training data. An EMG removal algorithm was developed based on two features: Lack of correlation between frequency bands and energy-spread in frequency. Results based on the analysis of testing data (36 h of intracranial EEG, including 18 seizures) show a sensitivity of 72%, a false detection of 0.7/h and a median delay of 5.7 s. Missed seizures originated mainly from seizures with subtle or absent high frequencies or from EMG removal procedures. False detections were mainly due to weak EMG or interictal high frequency activities. The system performed sufficiently well to be considered for clinical use, despite the exclusive use of frequencies not usually considered in clinical interpretation. High frequencies have the potential to contribute significantly to the detection of epileptic seizures.

High-frequency oscillations (HFOs) in clinical epilepsy.

Epilepsy is one of the most frequent neurological diseases. In focal medically refractory epilepsies, successful surgical treatment largely depends on the identification of epileptogenic zone. High-frequency oscillations (HFOs) between 80 and 500Hz, which can be recorded with EEG, may be novel markers of the epileptogenic zone. This review discusses the clinical importance of HFOs as markers of epileptogenicity and their application in different types of epilepsies. HFOs are clearly linked to the seizure onset zone, and the surgical removal of regions generating them correlates with a seizure free post-surgical outcome. Moreover, HFOs reflect the seizure-generating capability of the underlying tissue, since they are more frequent after the reduction of antiepileptic drugs. They can be successfully used in pediatric epilepsies such as epileptic spasms and help to understand the generation of this specific type of seizures. While mostly recorded on intracranial EEGs, new studies suggest that identification of HFOs on scalp EEG or magnetoencephalography (MEG) is possible as well. Thus not only patients with refractory epilepsies and invasive recordings but all patients might profit from the analysis of HFOs. Despite these promising results, the analysis of HFOs is not a routine clinical procedure; most results are derived from relatively small cohorts of patients and many aspects are not yet fully understood. Thus the review concludes that even if HFOs are promising biomarkers of epileptic tissue, there are still uncertainties about mechanisms of generation, methods of analysis, and clinical applicability. Large multicenter prospective studies are needed prior to widespread clinical application.

Detection of epileptic activity in fMRI without recording the EEG.

EEG-fMRI localizes epileptic foci by detecting cerebral hemodynamic changes that are correlated to epileptic events visible in EEG. However, scalp EEG is insensitive to activity restricted to deep structures and recording the EEG in the scanner is complex and results in major artifacts that are difficult to remove. This study presents a new framework for identifying the BOLD manifestations of epileptic discharges without having to record the EEG. The first stage is based on the detection of epileptic events for each voxel by sparse representation in the wavelet domain. The second stage is to gather voxels according to proximity in time and space of detected activities. This technique was evaluated on data generated by superposing artificial responses at different locations and responses amplitude in the brain for 6 control subject runs. The method was able to detect effectively and consistently for responses amplitude of at least 1% above baseline. 46 runs from 15 patients with focal epilepsy were investigated. The results demonstrate that the method detected at least one concordant event in 37/41 runs. The maps of activation obtained from our method were more similar to those obtained by EEG-fMRI than to those obtained by the other method used in this context, 2D-Temporal Cluster Analysis. For 5 runs without event read on scalp EEG, 3 runs showed an activation concordant with the patient's diagnostic. It may therefore be possible, at least when spikes are infrequent, to detect their BOLD manifestations without having to record the EEG.

A comparison between detectors of high frequency oscillations.

OBJECTIVE: High frequency oscillations (HFOs) are a biomarker of epileptogenicity. Visual marking of HFOs is highly time-consuming and inevitably subjective, making automatic detection necessary. We compare four existing detectors on the same dataset. METHODS: HFOs and baselines were identified by experienced reviewers in intracerebral EEGs from 20 patients. A new feature of our detector to deal with channels where baseline cannot be found is presented. The original and an optimal configuration are implemented. Receiver operator curves, false discovery rate, and channel ranking are used to evaluate performance. RESULTS: All detectors improve performance with the optimal configuration. Our detector had higher sensitivity, lower false positives than the others, and similar false detections. The main difference in performance was in very active channels. CONCLUSIONS: Each detector was developed for different recordings and with different aims. Our detector performed better in this dataset, but was developed on data similar to the test data. Moreover, optimizing on a particular data type improves performance in any detector. SIGNIFICANCE: Automatic HFO detection is crucial to propel their clinical use as biomarkers of epileptogenic tissue. Comparing detectors on a single dataset is important to analyze their performance and to emphasize the issues involved in validation.

Interictal scalp fast oscillations as a marker of the seizure onset zone.

OBJECTIVE: This study aims to identify if oscillations at frequencies higher than the traditional EEG can be recorded on the scalp EEG of patients with focal epilepsy and to analyze the association of these oscillations with interictal discharges and the seizure onset zone (SOZ). METHODS: The scalp EEG of 15 patients with focal epilepsy was studied. We analyzed the rates of gamma (40-80 Hz) and ripple (>80 Hz) oscillations, their co-occurrence with spikes, the number of channels with fast oscillations inside and outside the SOZ, and the specificity, sensitivity, and accuracy of gamma, ripples, and spikes to determine the SOZ. RESULTS: Gamma and ripples frequently co-occurred with spikes (77.5% and 63% of cases). For all events, the proportion of channels with events was consistently higher inside than outside the SOZ: spikes (100% vs 70%), gamma (82% vs 33%), and ripples (48% vs 11%); p < 0.0001. The mean rates (events/min) were higher inside than outside the SOZ: spikes (2.64 ± 1.70 vs 0.69 ± 0.26, p = 0.02), gamma (0.77 ± 0.71 vs 0.20 ± 0.25, p = 0.02), and ripples (0.08 ± 0.12 vs 0.04 ± 0.09, p = 0.04). The sensitivity to identify the SOZ was spikes 100%, gamma 82%, and ripples 48%; the specificity was spikes 30%, gamma 68%, and ripples 89%; and the accuracy was spikes 43%, gamma 70%, and ripples 81%. CONCLUSION: The rates and the proportion of channels with gamma and ripple fast oscillations are higher inside the SOZ, indicating that they can be used as interictal scalp EEG markers for the SOZ. These fast oscillations are less sensitive but much more specific and accurate than spikes to delineate the SOZ.

[Seizure prediction: from myth to reality]. / Prédiction des crises d'épilepsie: du mythe à la réalité.

INTRODUCTION: Clinical, metabolic and electrophysiologic studies suggest the existence of a preictal state, a transition between the interictal state and seizure. STATE OF THE ART: Analysis of the intracranial EEG by mathematical methods shows changes of the brain dynamics several minutes before the occurrence of partial seizures. These modifications can be widespread and not restricted to the epileptogenic focus, which would explain why they can also be detected from scalp EEG. Several scenarios could underlie the preictal state: a progressive recruitment of neurons or a facilitating state with a high probability of seizure occurrence. Because of the high rate of false predictions, no satisfactory method for seizure prediction has been currently proposed. PERSPECTIVES: A European multicenter study (Evolving platform for improving living expectation of patients suffering from IctAl events [EPILEPSIAE]) is currently evaluating a combination of 44 methods applied for EEG and ECG analysis on long-term recordings obtained from a large multicenter database (www.epilepsiae.eu). CONCLUSION: Combining analyses of multi-level signals including intracranial EEG and microelectrodes, scalp EEG and in vitro electrophysiological studies of post-operative tissues should help clarify brain dynamics during the pre-ictal state.

Automatic detector of high frequency oscillations for human recordings with macroelectrodes.

High Frequency Oscillations (HFOs) in the EEG are a promising biomarker of epileptogenic tissue. Given that the visual marking of HFOs is highly time-consuming and subjective, automatic detectors are necessary. In this study, we present a novel automatic detector that detects HFOs by incorporating information of previously detected baselines. The detector was trained on 72 channels and tested on 278, achieving a mean sensitivity of 96.8% with a mean false positive rate of 4.86%. This low rate is reasonable since only visually marked baseline segments were considered as the true negatives. This detector could be useful for the systematic study of HFOs and for their eventual clinical application.

Thalamic nuclei activity in idiopathic generalized epilepsy: an EEG-fMRI study.

OBJECTIVE: Idiopathic generalized epilepsies (IGE) are characterized by specific EEG changes including 3- to 5-Hz generalized spike-and-wave discharges. The thalamus and its cortical interactions are considered essential in the production and propagation of spike-and-wave discharges. In animal studies, corticoreticular and limbic system property changes have been observed in absence seizures and during spike-and-wave discharges and suggest the involvement of different types of thalamic nuclei. With the development of deep brain stimulation in epilepsy, the role of the thalamic nuclei needs to be clarified in human IGE. METHODS: Ten patients with IGE were recorded using 3T EEG-fMRI during spike-and-wave discharges. Hemodynamic response functions were calculated for 4 regions of interest corresponding to the anterior thalamic and centromedian and parafascicular (CM-Pf) nuclei of each thalamus. The time to peak of the hemodynamic response function was compared within thalamic structures (left compared to right) and between structures (anterior thalamic compared to CM-Pf nucleus). RESULTS: CM-Pf and anterior nucleus are both activated during GSWDs. However, the positive time to peak in the CM-Pf (4.4 +/- 2.5 s) occurred significantly earlier than in the anterior nucleus (7.6 +/- 3.2 s). CONCLUSIONS: We demonstrated in humans the involvement of the centromedian and parafascicular part of the corticoreticular system and of the anterior nucleus part of the limbic system during generalized spike-and-wave discharges. The different time courses suggest that the posterior intralaminar nuclei may be involved in epileptic discharge initiation or early propagation, while the anterior nucleus may only play a role in its maintenance. These results may help to understand the clinical effect of deep brain stimulation within thalamic nuclei in intractable idiopathic generalized epilepsy patients.

EEG-fMRI: adding to standard evaluations of patients with nonlesional frontal lobe epilepsy.

OBJECTIVE: In patients with nonlesional frontal lobe epilepsy (FLE), the delineation of the epileptogenic zone is difficult. Therefore these patients are often not considered for surgery due to an unclear seizure focus. The aim of this study was to investigate whether EEG-fMRI can add useful information in the preoperative evaluation of these patients. METHODS: Nine nonlesional FLE patients were studied with EEG-fMRI using a 3 T scanner. Spike-related blood oxygen level dependent (BOLD) signal changes were compared to the topography of the spikes and to PET and SPECT results if available. The structural MRIs were reviewed for subtle abnormalities in areas that showed BOLD responses. For operated patients, postoperative resection and histology were compared to BOLD responses. RESULTS: Concordance between spike localization and positive BOLD response was found in 8 patients. PET and SPECT investigations corresponded with BOLD signal changes in 6 of 7 investigations. In 2 cases, reviewing the structural MRI guided by EEG-fMRI data resulted in considering a suspicious deep sulcus. Two patients were operated. In 1, the resected cortex corresponded with the suspicious sulcus and fMRI results and histology showed cortical dysplasia. In another, histology revealed an extended microdysgenesis not visible on structural MRI. EEG-fMRI had shown activation just adjacent to the resected pathologic area. CONCLUSIONS: Our study provides different types of support (topography, concordance with PET and SPECT, structural peculiarities, postoperative histology) that EEG-fMRI may help to delineate the epileptic focus in patients with nonlesional frontal lobe epilepsy, a challenging group in the preoperative evaluation.

High-frequency oscillations mirror disease activity in patients with epilepsy.

OBJECTIVE: High-frequency oscillations (HFOs) can be recorded in epileptic patients with clinical intracranial EEG. HFOs have been associated with seizure genesis because they occur in the seizure focus and during seizure onset. HFOs are also found interictally, partly co-occurring with epileptic spikes. We studied how HFOs are influenced by antiepileptic medication and seizure occurrence, to improve understanding of the pathophysiology and clinical meaning of HFOs. METHODS: Intracerebral depth EEG was partly sampled at 2,000 Hz in 42 patients with intractable focal epilepsy. Patients with five or more usable nights of recording were selected. A sample of slow-wave sleep from each night was analyzed, and HFOs (ripples: 80-250 Hz, fast ripples: 250-500 Hz) and spikes were identified on all artifact-free channels. The HFOs and spikes were compared before and after seizures with stable medication dose and during medication reduction with no intervening seizures. RESULTS: Twelve patients with five to eight nights were included. After seizures, there was an increase in spikes, whereas HFO rates remained the same. Medication reduction was followed by an increase in HFO rates and mean duration. CONCLUSIONS: Contrary to spikes, high-frequency oscillations (HFOs) do not increase after seizures, but do so after medication reduction, similarly to seizures. This implies that spikes and HFOs have different pathophysiologic mechanisms and that HFOs are more tightly linked to seizures than spikes. HFOs seem to play an important role in seizure genesis and can be a useful clinical marker for disease activity.

Different structures involved during ictal and interictal epileptic activity in malformations of cortical development: an EEG-fMRI study.

Malformations of cortical development (MCDs) are commonly complicated by intractable focal epilepsy. Epileptogenesis in these disorders is not well understood and may depend on the type of MCD. The cellular mechanisms involved in interictal and ictal events are notably different, and could be influenced independently by the type of pathology. We evaluated the relationship between interictal and ictal zones in eight patients with different types of MCD in order to better understand the generation of these activities: four had nodular heterotopia, two focal cortical dysplasia and two subcortical band heterotopia (double-cortex). We used the non-invasive EEG-fMRI technique to record simultaneously all cerebral structures with a high spatio-temporal resolution. We recorded interictal and ictal events during the same session. Ictal events were either electrical only or clinical with minimal motion. BOLD changes were found in the focal cortical dysplasia during interictal and ictal epileptiform events in the two patients with this disorder. Heterotopic and normal cortices were involved in BOLD changes during interictal and ictal events in the two patients with double cortex, but the maximum BOLD response was in the heterotopic band in both patients. Only two of the four patients with nodular heterotopia showed involvement of a nodule during interictal activity. During seizures, although BOLD changes affected the lesion in two patients, the maximum was always in the overlying cortex and never in the heterotopia. For two patients intracranial recordings were available and confirm our findings. The dysplastic cortex and the heterotopic cortex of band heterotopia were involved in interictal and seizure processes. Even if the nodular gray matter heterotopia may have the cellular substrate to produce interictal events, the often abnormal overlying cortex is more likely to be involved during the seizures. The non-invasive BOLD study of interictal and ictal events in MCD patients may help to understand the role of the lesion in epileptogenesis and also determine the potential surgical target.

Concordance between distributed EEG source localization and simultaneous EEG-fMRI studies of epileptic spikes.

In order to analyze where epileptic spikes are generated, we assessed the level of concordance between EEG source localization using distributed source models and simultaneous EEG-fMRI which measures the hemodynamic correlates of EEG activity. Data to be compared were first estimated on the same cortical surface and two comparison strategies were used: (1) MEM-concordance: a comparison between EEG sources localized with the Maximum Entropy on the Mean (MEM) method and fMRI clusters showing a significant hemodynamic response. Minimal geodesic distances between local extrema and overlap measurements between spatial extents of EEG sources and fMRI clusters were used to quantify MEM-concordance. (2) fMRI-relevance: estimation of the fMRI-relevance index alpha quantifying if sources located in an fMRI cluster could explain some scalp EEG data, when this fMRI cluster was used to constrain the EEG inverse problem. Combining MEM-concordance and fMRI-relevance (alpha) indexes, each fMRI cluster showing a significant hemodynamic response (p<0.05 corrected) was classified according to its concordance with EEG data. Nine patients with focal epilepsy who underwent EEG-fMRI examination followed by EEG recording outside the scanner were selected for this study. Among the 62 fMRI clusters analyzed (7 patients), 15 (24%) found in 6 patients were highly concordant with EEG according to both MEM-concordance and fMRI-relevance. EEG concordance was found for 5 clusters (8%) according to alpha only, suggesting sources missed by the MEM. No concordance with EEG was found for 30 clusters (48%) and for 10 clusters (16%) alpha was significantly negative, suggesting EEG-fMRI discordance. We proposed two complementary strategies to assess and classify EEG-fMRI concordance. We showed that for most patients, part of the hemodynamic response to spikes was highly concordant with EEG sources, whereas other fMRI clusters in response to the same spikes were found distant or discordant with EEG sources.

Anatomically informed interpolation of fMRI data on the cortical surface.

Analyzing functional magnetic resonance imaging (fMRI) data restricted to the cortical surface is of particular interest for two reasons: (1) to increase detection sensitivity using anatomical constraints and (2) to compare or use fMRI results in the context of source localization from magneto/electro-encephalography (MEEG) data, which requires data to be projected on the same spatial support. Designing an optimal scheme to interpolate fMRI raw data or resulting activation maps on the cortical surface relies on a trade-off between choosing large enough interpolation kernels, because of the distributed nature of the hemodynamic response, and avoiding mixing data issued from different anatomical structures. We propose an original method that automatically adjusts the level of such a trade-off, by defining interpolation kernels around each vertex of the cortical surface using a geodesic Voronoï diagram. This Voronoï-based interpolation method was evaluated using simulated fMRI activation maps, manually generated on an anatomical MRI, and compared with a more standard approach where interpolation kernels were defined as local spheres of radius r=3 or 5 mm. Several validation parameters were considered: the spatial resolution of the simulated activation map, the spatial resolution of the cortical mesh, the level of anatomical/functional data misregistration and the location of the vertices within the gray matter ribbon. Using an activation map at the spatial resolution of standard fMRI data, robustness to misregistration errors was observed for both methods, whereas only the Voronoï-based approach was insensitive to the position of the vertices within the gray matter ribbon.

High-frequency oscillations during human focal seizures.

Discrete high-frequency oscillations (HFOs) in the range of 100-500 Hz have previously been recorded in human epileptic brains using depth microelectrodes. We describe for the first time similar oscillations in a cohort of unselected focal epileptic patients implanted with EEG macroelectrodes. Spectral analysis and visual inspection techniques were used to study seizures from 10 consecutive patients undergoing pre-surgical evaluation for medically refractory focal epilepsy. Four of these patients had focal seizure onset in the mesial temporal lobe, and in all 12 of their seizures, well-localized, segmental, very high frequency band (VHF: 250-500 Hz) oscillations were visually identified near the time of seizure onset from contacts in this zone. Increased high-frequency band (HF: 100-200 Hz) activity compared with the background was distinguished both visually and with spectral analysis later in the seizures of 3/4 mesial temporal patients, involving contacts in the generator region and, in one patient, areas of contralateral peri-hippocampal propagation. Three patients with well-defined neocortical seizure-onset areas also demonstrated focal HF or VHF oscillations confined to the seizure-onset channels during their eight seizures. No discrete HF or VHF activity was present in the poorly localized seizures from the remaining three patients. These results show that discrete HFOs can be recorded from human focal epileptic brain using depth macroelectrodes, and that they occur mostly in regions of primary epileptogenesis and rarely in regions of secondary spread. Absent high-frequency activity seems to indicate poor localization, whereas the presence of focal HFOs near the time of seizure onset may signify proximity to the epileptogenic focus in mesial temporal lobe and neocortical seizures. We postulate that focal HFOs recorded with depth macroelectrodes reflect the partial synchronization of very local oscillations such as those previously studied using microelectrodes, and result from interconnected small neuronal ensembles. Our finding that localized HFOs occur in varying anatomical structures and pathological conditions perhaps indicates commonality to diverse epileptogenic aetiologies.