Simultaneous MEG and EEG to detect ripples in people with focal epilepsy

ObjectiveWe studied ripples (80–250 Hz) simultaneously recorded in electroencephalography (EEG) and magnetoencephalography (MEG) to evaluate the differences.MethodsSimultaneous EEG and MEG were recorded in 30 patients with drug resistant focal epilepsy. Ripples were automatically detected and visually checked in virtual channels throughout the cortex. The number and location of ripples in EEG and MEG were compared to each other and to a region of interest (ROI) defined by clinically available information.ResultsEleven patients showed ripples in both MEG and EEG, 11 only in EEG and one only in MEG. Twenty-four percent of the ripples occurred simultaneously in EEG and MEG, 71% only in EEG, and 5% only in MEG. Three patients without spikes in EEG showed EEG ripples. Ripple localization was concordant with the ROI in 80% of patients with MEG ripples, as opposed to 62% full or partial concordance for EEG ripples. With the optimal threshold for localizing the ROI, sensitivity and specificity were more than 80%.ConclusionsRipples in MEG are less frequent but more specific and sensitive for the region of interest than ripples in EEG. Ripples in EEG can exist without spikes in the EEG.SignificanceRipples in MEG and EEG provide complementary information.     

Interictal high frequency oscillations (HFOs) in patients with focal epilepsy and normal MRI

Objective

We aim to analysis the relationship between HFOs-generating regions and the seizure onset zone (SOZ) in epileptic patients without a visible lesion on MRI.

Methods

Intracerebral EEGs were recorded in 17 patients with intractable focal seizures and normal MRIs. The rates of interictal HFOs and spikes inside and outside the SOZ were analyzed as well as the specificity, sensitivity and accuracy of HFOs and spikes to determine the SOZ.

Results

The mean rate of spikes, ripples and fast ripples (FR) was higher in the SOZ than in the non-SOZ channels. In regard to the identification of the SOZ the sensitivity was 91% for spikes, 91% for ripples and 66% for FR, the specificity was 30% for spikes, 42% for ripples and 80% for FR, and the accuracy was 44% for spikes, 54% for ripples and 76% for FR.

Conclusions

The rates of spikes and HFOs were higher inside than outside the SOZ. However, HFOs are also more specific and accurate than spikes to delineate the SOZ.

Significance

Analysis of interictal HFOs during 5-10 min of sleep recording is a good tool to localize the SOZ in patients with epilepsy and normal MRI, and could potentially reduce the duration of chronic intracerebral EEG recordings.     

BOLD signal changes preceding negative responses in EEG‐fMRI in patients with focal epilepsy

Purpose: In simultaneous electroencephalography (EEG) and functional magnetic resonance imaging (fMRI), increased neuronal activity from epileptiform spikes commonly elicits positive blood oxygenation level–dependent (BOLD) responses. Negative responses are also occasionally seen and have not been explained. Recent studies describe BOLD signal changes before focal EEG spikes. We aimed to systematically study if the undershoot of a preceding positive response might explain the negative BOLD seen in the focus. Methods: Eighty‐two patients with focal epilepsy who underwent EEG‐fMRI at 3T were retrospectively studied. Studies with a focal negative BOLD response in the region of the spike field were reanalyzed using models with hemodynamic response functions (HRFs) peaking from ?9 to +9 s around the spike. Results: Eight patients met the inclusion criteria, showing negative BOLD responses in the spike field on standard analysis. None had positive BOLD responses immediately adjacent to the areas of deactivation. Regions of deactivation were found to have congruent preceding positive responses in two cases. These early activations were seen at the combined maps of ?5 to ?9 s. Discussion: This study indicates that in a small proportion of patients with focal epilepsy in whom the standard analysis reveals focal negative responses, an earlier positive BOLD response is probably the cause. The origin of negative BOLD signal changes in the focus as a result of an epileptic event remains, however, unexplained in most of the patients in whom it occurs.     

Cortical contribution to scalp EEG gamma rhythms associated with epileptic spasms

The cortical contribution for the generation of gamma rhythms detected from scalp ictal EEG was studied in unique cases of epileptic spasms and a review of the related literature was conducted. Ictal scalp gamma rhythms were investigated through time–frequency analysis in two cases with a combination of focal seizures and spasms and another case with spasms associated with cortical dysplasia. In the two patients with combined seizures, the scalp distribution of ictal gamma rhythms was related to that of focal seizure activity. In the third patient, an asymmetric distribution of the ictal scalp gamma rhythms was transiently revealed in correspondence to the dysplasic cortex during hormonal treatment. Therefore, the dominant region of scalp gamma rhythms may correspond to the epileptogenic cortical area. The current findings have reinforced the possibility of the cortical generation of ictal scalp gamma rhythms associated with spasms. The detection of high frequencies through scalp EEG is a technical challenge, however, and the clinical significance of scalp gamma rhythms may not be the same as that of invasively recorded high frequencies. Further studies on the pathophysiological mechanisms related to the generation of spasms involving high frequencies are necessary in the future, and the development of animal models of spasms will play an important role in this regard.     

Negative BOLD responses to epileptic spikes

Simultaneous electroencephalogram/functional magnetic resonance imaging (EEG-fMRI) during interictal epileptiform discharges can result in positive (activation) and negative (deactivation) changes in the blood oxygenation level-dependent (BOLD) signal. Activation probably reflects increased neuronal activity and energy demand, but deactivation is more difficult to explain. Our objective was to evaluate the occurrence and significance of deactivations related to epileptiform discharges in epilepsy. We reviewed all EEG-fMRI studies from our database, identified those with robust responses (P = 0.01, with > or =5 contiguous voxels with a |t| > 3.1, including > or =1 voxel at |t| > 5.0), and divided them into three groups: activation (A = 8), deactivation (D = 9), and both responses (AD = 43). We correlated responses with discharge type and location and evaluated their spatial relationship with regions involved in the "default" brain state (Raichle et al. [2001]: Proc Natl Acad Sci 98:676-682]. Deactivations were seen in 52/60 studies (AD + D): 26 related to focal discharges, 12 bilateral, and 14 generalized. Deactivations were usually distant from anatomical areas related to the discharges and more frequently related to polyspike- and spike-and-slow waves than to spikes. The "default" pattern occurred in 10/43 AD studies, often associated with bursts of generalized discharges. In conclusion, deactivations are frequent, mostly with concomitant activation, for focal and generalized discharges. Discharges followed by a slow wave are more likely to result in deactivation, suggesting neuronal inhibition as the underlying phenomenon. Involvement of the "default" areas, related to bursts of generalized discharges, provides evidence of a subclinical effect of the discharges, temporarily suspending normal brain function in the resting state.     

Intracranial EEG-fMRI analysis of focal epileptiform discharges in humans

Purpose: Combining intracranial electroencephalography (iEEG) with functional magnetic resonance imaging (fMRI) is of interest in epilepsy studies as it would allow the detection of much smaller interictal epileptiform discharges than can be recorded using scalp EEG‐fMRI. This may help elucidate the spatiotemporal mechanisms underlying the generation of interictal discharges. To our knowledge, iEEG‐fMRI has never been performed at 3 Tesla (3T) in humans. We report our findings relating to spike‐associated blood oxygen level–dependent (BOLD) signal changes in two subjects. Methods: iEEG‐fMRI at 3T was performed in two subjects. Twelve channels of iEEG were recorded from subdural strips implanted on the left posterior temporal and middle frontal lobes in a 20‐year‐old female with bilateral periventricular gray matter heterotopia. Twenty channels of iEEG were recorded bilaterally from two subdural strips laid anterior–posterior along mesial temporal surfaces in a 29‐year‐old woman with bilateral temporal seizures and mild left amygdalar enlargement on MRI. Functional MRI (fMRI) statistical maps were generated and thresholded at p = 0.01. Key Findings: No adverse events were noted. A total of 105 interictal discharges were recorded in the posterior middle temporal gyrus of Subject 1. In Subject 2, 478 discharges were recorded from both mesial temporal surfaces (n = 194 left, 284 right). The right and left discharges were modeled separately, as they were independent. Subject 1 showed spike‐associated BOLD signal increases in the left superior temporal region, left middle frontal gyrus, and right parietal lobe. BOLD decreases were seen in the right frontal and parietal lobes. In Subject 2, BOLD signal increases were seen in both mesial temporal lobes, which when left and right spikes were modeled independently, were greater on the side of the discharge. In addition, striking BOLD signal decreases were observed in the thalamus and posterior cingulate gyrus. Significance: iEEG‐fMRI can be performed at 3T with low risk. Notably, runs of only 5 or 10 min of EEG‐fMRI were performed as part of our implementation protocol, yet a significant number of epileptiform discharges were recorded, allowing meaningful analyses. With these studies, we have shown that deactivation can be seen in individual subjects with focal epileptiform discharges. These preliminary observations suggest a novel mechanism through which focal interictal discharges may have widespread cortical and subcortical influences.     

High frequency oscillations in intra-operative electrocorticography before and after epilepsy surgery

ObjectiveRemoval of brain tissue showing high frequency oscillations (HFOs; ripples: 80–250 Hz and fast ripples: 250–500 Hz) in preresection electrocorticography (preECoG) in epilepsy patients seems a predictor of good surgical outcome. We analyzed occurrence and localization of HFOs in intra-operative preECoG and postresection electrocorticography (postECoG).MethodsHFOs were automatically detected in one-minute epochs of intra-operative ECoG sampled at 2048 Hz of fourteen patients. Ripple, fast ripple, spike, ripples on a spike (RoS) and not on a spike (RnoS) rates were analyzed in pre- and postECoG for resected and nonresected electrodes.ResultsRipple, spike and fast ripple rates decreased after resection. RnoS decreased less than RoS (74% vs. 83%; p = 0.01). Most fast ripples in preECoG were located in resected tissue. PostECoG fast ripples occurred in one patient with poor outcome. Patients with good outcome had relatively high postECoG RnoS rates, specifically in the sensorimotor cortex.ConclusionsOur observations show that fast ripples in intra-operative ECoG, compared to ripples, may be a better biomarker for epileptogenicity. Further studies have to determine the relation between resection of epileptogenic tissue and physiological ripples generated by the sensorimotor cortex.SignificanceFast ripples in intra-operative ECoG can help identify the epileptogenic zone, while ripples might also be physiological.     

Independent component analysis as a model-free approach for the detection of BOLD changes related to epileptic spikes: a simulation study

EEG-fMRI in epileptic patients is commonly analyzed using the general linear model (GLM), which assumes a known hemodynamic response function (HRF) to epileptic spikes in the EEG. In contrast, independent component analysis (ICA) can extract Blood-Oxygenation Level Dependent (BOLD) responses without imposing constraints on the HRF. This technique was evaluated on data generated by superimposing artificial responses on real background fMRI signals. Simulations were run using a wide range of EEG spiking rates, HRF amplitudes, and activation regions. The data were decomposed by spatial ICA into independent components. A deconvolution method then identified component time courses significantly related to the simulated spikes, without constraining the shape of the HRF. Components matching the simulated activation regions ("concordant components") were found in 84.4% of simulations, while components at discordant locations were found in 12.2% of simulations. These false activations were often related to large artifacts that coincidentally occurred simultaneously with some of the random simulated spikes. The performance of the method depended closely on the simulation parameters; when the number of spikes was low, concordant components could only be identified when HRF amplitudes were large. Although ICA did not depend on the shape of the HRF, data processed with the GLM did not reveal the appropriate activation region when the HRF varied slightly from the canonical shape used in the model. ICA may thus be able to extract BOLD responses from EEG-fMRI data in epileptic patients, in a way that is robust to uncertainty and variability in the shape of the HRF.     

EEG spectral changes underlying BOLD responses contralateral to spikes in patients with focal epilepsy

Purpose:   Simultaneous electroencephalogram and functional magnetic resonance imaging (EEG–fMRI) in patients with focal epilepsy and unilateral spikes often shows positive blood oxygenation level–dependent (BOLD) responses (activations), not only ipsilateral but also contralateral to the spikes. We aimed to investigate whether minimal EEG changes could underlie these contralateral BOLD responses by using EEG spectral analysis.
Methods:   We studied 19 patients with focal epilepsy and unilateral spikes. According to the pattern of BOLD activation, patients were divided into Group 1 (ipsi- and contralateral to the spikes) or Group 2 (only ipsilateral). EEG from outside the scanner was used to mark spikes similar to those recorded in the scanner. Epochs of 640 ms before and after the peak of the spikes were chosen as baseline and spike epochs. Spectral analysis was performed in referential montage (FCz reference), and differences between baselines and spikes were analyzed by paired t -test.
Results:   Significant EEG changes in electrodes contralateral to the spikes were seen in 9 of 10 patients in Group 1 and in only 2 of 10 patients in Group 2 (one patient had two types of spikes that were analyzed separately). Spectral changes were seen in delta and/or theta bands in all patients except one (in Group 1) who had changes in all bands.
Discussion:   Significant contralateral EEG changes occurred in 90% of contralateral BOLD activations and in only 20% of patients without contralateral BOLD responses. The reason why these changes predominate in lower frequencies rather than in higher frequencies is unclear. These spectral changes in areas corresponding to contralateral activations might reflect poorly synchronized but possibly intense neuronal activity.     

Resection of ictal high-frequency oscillations leads to favorable surgical outcome in pediatric epilepsy

Purpose: Intracranial electroencephalography (EEG) is performed as part of an epilepsy surgery evaluation when noninvasive tests are incongruent or the putative seizure‐onset zone is near eloquent cortex. Determining the seizure‐onset zone using intracranial EEG has been conventionally based on identification of specific ictal patterns with visual inspection. High‐frequency oscillations (HFOs, >80 Hz) have been recognized recently as highly correlated with the epileptogenic zone. However, HFOs can be difficult to detect because of their low amplitude. Therefore, the prevalence of ictal HFOs and their role in localization of epileptogenic zone on intracranial EEG are unknown. Methods: We identified 48 patients who underwent surgical treatment after the surgical evaluation with intracranial EEG, and 44 patients met criteria for this retrospective study. Results were not used in surgical decision making. Intracranial EEG recordings were collected with a sampling rate of 2,000 Hz. Recordings were first inspected visually to determine ictal onset and then analyzed further with time‐frequency analysis. Forty‐one (93%) of 44 patients had ictal HFOs determined with time‐frequency analysis of intracranial EEG. Key Findings: Twenty‐two (54%) of the 41 patients with ictal HFOs had complete resection of HFO regions, regardless of frequency bands. Complete resection of HFOs (n = 22) resulted in a seizure‐free outcome in 18 (82%) of 22 patients, significantly higher than the seizure‐free outcome with incomplete HFO resection (4/19, 21%). Significance: Our study shows that ictal HFOs are commonly found with intracranial EEG in our population largely of children with cortical dysplasia, and have localizing value. The use of ictal HFOs may add more promising information compared to interictal HFOs because of the evidence of ictal propagation and followed by clinical aspect of seizures. Complete resection of HFOs is a favorable prognostic indicator for surgical outcome.     

Interictal scalp fast ripple occurrence and high frequency oscillation slow wave coupling in epileptic spasms

ObjectiveIntracranial high frequency oscillation (HFO) occurrence rate (OR) and slow wave activity (SWA) coupling are potential markers of epileptogenicity in epileptic spasms (ES). Scalp ripple (R) detection and SWA coupling have been described in ES; however, the feasibility of scalp fast ripple (FR) detection and measurement of scalp FR coupling to SWA is not known. We evaluated interictal scalp R and FR OR and SWA coupling in pre-treatment EEG in children with short-term treatment-refractory ES compared to short-term treatment non-refractory ES.MethodsWe retrospectively identified children with ES and identified HFOs using a semi-automated HFO detector on pre-treatment scalp EEG during sleep. We evaluated HFO OR and event-triggered modulation index (MI) to quantify R (100–250 Hz) and FR (250–600 Hz) coupling strength with different SWA passbands (0.5–1, 1–2, 2–3, 3–4, and 4–8 Hz). We used HFO phasor transform and circular statistics to evaluate phase coupling angle distributions.ResultsWe identified 15 children with ES with pre-treatment EEG recorded at 2000 Hz. Thirteen out of 15 patients had HFOs and were included for analysis. There were six treatment responders and seven nonresponders three months after treatment initiation. Responders and nonresponders were similar in age (6.1 vs 7.2 mo), ES diagnosis duration (0.7 vs 2.6 mo), and HFO OR (R: 1.07 vs 2.30/min, FR: 0.43 vs 1.96/min). No differences between responders and nonresponders were seen in HFO MI at different SWA. Coupling of R and FR to 2–3 Hz SWA demonstrated increased incidence rate ratio in nonresponders relative to responders at distinct phase coupling angle distributions.ConclusionsThis study demonstrates the feasibility of interictal scalp R and FR detection and quantification of scalp R and FR coupling to SWA in ES.SignificanceHFO phase coupling with SWA may be useful as a marker of potential treatment refractoriness in patients with ES.     

Exploring the advantages of multiband fMRI with simultaneous EEG to investigate coupling between gamma frequency neural activity and the BOLD response in humans

We established an optimal combination of EEG recording during sparse multiband (MB) fMRI that preserves high‐resolution, whole‐brain fMRI coverage while enabling broad‐band EEG recordings which are uncorrupted by MRI gradient artefacts (GAs). We first determined the safety of simultaneous EEG recording during MB fMRI. Application of MB factor = 4 produced <1°C peak heating of electrode/hardware during 20 min of GE‐EPI data acquisition. However, higher SAR sequences require specific safety testing, with greater heating observed using PCASL with MB factor = 4. Heating was greatest in the electrocardiogram channel, likely due to it possessing longest lead length. We investigated the effect of MB factor on the temporal signal‐to‐noise ratio for a range of GE‐EPI sequences (varying MB factor and temporal interval between slice acquisitions). We found that, for our experimental purpose, the optimal acquisition was achieved with MB factor = 3, 3mm isotropic voxels, and 33 slices providing whole head coverage. This sequence afforded a 2.25 s duration quiet period (without GAs) in every 3 s TR. Using this sequence, we demonstrated the ability to record gamma frequency (55–80 Hz) EEG oscillations, in response to right index finger abduction, that are usually obscured by GAs during continuous fMRI data acquisition. In this novel application of EEG‐MB fMRI to a motor task, we observed a positive correlation between gamma and BOLD responses in bilateral motor regions. These findings support and extend previous work regarding coupling between neural and hemodynamic measures of brain activity in humans and showcase the utility of EEG‐MB fMRI for future investigations.     

Increased cortical BOLD signal anticipates generalized spike and wave discharges in adolescents and adults with idiopathic generalized epilepsies

Purpose: Electroencephalography–functional magnetic resonance imaging (EEG‐fMRI) coregistration has recently revealed that several brain structures are involved in generalized spike and wave discharges (GSWDs) in idiopathic generalized epilepsies (IGEs). In particular, deactivations and activations have been observed within the so‐called brain default mode network (DMN) and thalamus, respectively. In the present study we analyzed the dynamic time course of blood oxygen level–dependent (BOLD) changes preceding and following 3 Hz GSWDs in a group of adolescent and adult patients with IGE who presented with absence seizures (AS). Our aim was to evaluate cortical BOLD changes before, during, and after GSWD onset. Methods: Twenty‐one patients with IGE underwent EEG‐fMRI coregistration. EEG‐related analyses were run both at the single‐subject and at group level (random effect). The time‐course analysis was conducted for 3 s time windows before, during, and after GSWDs, and they were included until no further BOLD signal changes were observed. Key Findings: Fifteen patients (nine female, mean age 28 years) had GSWDs during EEG‐fMRI coregistration (262 total events, mean duration 4 s). Time‐course group analysis showed BOLD increments starting approximately 10 s before GSWD onset located in frontal and parietal cortical areas, and especially in the precuneus‐posterior cingulate region. At GSWD onset, BOLD increments were located in thalamus, cerebellum, and anterior cingulate gyrus, whereas BOLD decrements were observed in the DMN regions persisting until 9 s after onset. Significance: Hemodynamic changes (BOLD increments) occurred in specific cortical areas, namely the precuneus/posterior cingulate, lateral parietal, and frontal cortices, several seconds before EEG onset of GSWD. A dysfunction of these brain regions, some of which belongs to the DMN, may be crucial in generating GSWDs in patients with IGE.     

EEG-fMRI of focal epileptic spikes: analysis with multiple haemodynamic functions and comparison with gadolinium-enhanced MR angiograms

Combined EEG-fMRI has recently been used to explore the BOLD responses to interictal epileptiform discharges. This study examines whether misspecification of the form of the haemodynamic response function (HRF) results in significant fMRI responses being missed in the statistical analysis. EEG-fMRI data from 31 patients with focal epilepsy were analysed with four HRFs peaking from 3 to 9 sec after each interictal event, in addition to a standard HRF that peaked after 5.4 sec. In four patients, fMRI responses were correlated with gadolinium-enhanced MR angiograms and with EEG data from intracranial electrodes. In an attempt to understand the absence of BOLD responses in a significant group of patients, the degree of signal loss occurring as a result of magnetic field inhomogeneities was compared with the detected fMRI responses in ten patients with temporal lobe spikes. Using multiple HRFs resulted in an increased percentage of data sets with significant fMRI activations, from 45% when using the standard HRF alone, to 62.5%. The standard HRF was good at detecting positive BOLD responses, but less appropriate for negative BOLD responses, the majority of which were more accurately modelled by an HRF that peaked later than the standard. Co-registration of statistical maps with gadolinium-enhanced MRIs suggested that the detected fMRI responses were not in general related to large veins. Signal loss in the temporal lobes seemed to be an important factor in 7 of 12 patients who did not show fMRI activations with any of the HRFs.     

Continuous high-frequency activity in mesial temporal lobe structures

Purpose: Many recent studies have reported the importance of high‐frequency oscillations (HFOs) in the intracerebral electroencephalography (EEG) of patients with epilepsy. These HFOs have been defined as events that stand out from the background. We have noticed that this background often consists itself of high‐frequency rhythmic activity. The purpose of this study is to perform a first evaluation of the characteristics of high‐frequency continuous or semicontinuous background activity. Methods: Because the continuous high‐frequency pattern was noted mainly in mesial temporal structures, we reviewed the EEG studies from these structures in 24 unselected patients with electrodes implanted in these regions. Sections of background away from interictal spikes were marked visually during periods of slow‐wave sleep and wakefulness. They were then high‐passed filtered at 80 Hz and categorized as having high‐frequency rhythmic activity in one of three patterns: continuous/semicontinuous, irregular, sporadic. Wavelet entropy, which measures the degree of rhythmicity of a signal, was calculated for the marked background sections. Key Findings: Ninety‐six bipolar channels were analyzed. The continuous/semicontinuous pattern was found frequently (29/96 channels during wake and 34/96 during sleep). The different patterns were consistent between sleep and wakefulness. The continuous/semicontinuous pattern was found significantly more often in the hippocampus than in the parahippocampal gyrus and was rarely found in the amygdala. The types of pattern were not influenced by whether a channel was within the seizure‐onset zone, or whether it was a lesional channel. The continuous/semicontinuous pattern was associated with a higher frequency of spikes and with high rates of ripples and fast ripples. Significance: It appears that high‐frequency activity (above 80 Hz) does not appear only in the form of brief paroxysmal events but also in the form of continuous rhythmic activity or very long bursts. In this study limited to mesial temporal structures, we found a clear anatomic preference for the hippocampus. Although associated with spikes and with distinct HFOs, this pattern was not clearly associated with the seizure‐onset zone. Future studies will need to evaluate systematically the presence of this pattern, as it may have a pathophysiologic significance and it will also have an important influence on the very definition of HFOs.     

High frequency EEG activity associated with ictal events in an animal model of infantile spasms

Purpose : To describe high frequency (HF) electrographic activity accompanying ictal discharges in the tetrodotoxin (TTX) model of infantile spasms. Previous studies of HF oscillations in humans and animals suggest that they arise at sites of seizure onset. We compared HF oscillations at several cortical sites to determine regional differences. Methods : TTX was infused for 4 weeks into the neocortex of rats beginning on postnatal days 11 or 12. Electroencephalography (EEG) electrodes were implanted 2 weeks later and video‐EEG recordings were analyzed between postnatal days 31 and 47. EEG recordings were digitally sampled at 2,048 Hz. HF EEG activity (20–900 Hz) was quantified using compressed spectral arrays and band‐pass filtering. Key Findings : Multiple seizures were analyzed in 10 rats. Ictal onset was associated with multiple bands of rhythmic HF activity that could extend to 700 Hz. The earliest and most intense discharging typically occurred contralaterally to where TTX was infused. HF activity continued to occur throughout the seizure (even during the electrodecrement that is recorded with more traditional filter settings), although there was a gradual decrease of the intensity of the highest frequency components as the amplitude of lower frequency oscillations increased. Higher frequencies sometimes reappeared in association with spike/sharp‐waves at seizure termination. Significance : The findings show that HF EEG activity accompanies ictal events in the TTX model. Results also suggest that the seizures in this model do not originate from the TTX infusion site. Instead HF discharges are usually most intense and occur earliest contralaterally, suggesting that these homologous regions may be involved in seizure generation.