Reproducibility of interictal spike propagation in children with refractory epilepsy

Spontaneous HFO Sequences Reveal Propagation Pathways for Precise Delineation of Epileptogenic Networks

Epilepsy, a neurological disorder affecting millions worldwide, poses great challenges in precisely delineating the epileptogenic zone - the brain region generating seizures - for effective treatment. High-frequency oscillations (HFOs) are emerging as promising biomarkers; however, the clinical utility is hindered by the difficulties in distinguishing pathological HFOs from non- epileptiform activities at single electrode and single patient resolution and understanding their dynamic role in epileptic networks. Here, we introduce an HFO-sequencing approach to analyze spontaneous HFOs traversing cortical regions in 40 drug-resistant epilepsy patients. This data- driven method automatically detected over 8.9 million HFOs, pinpointing pathological HFO- networks, and unveiled intricate millisecond-scale spatiotemporal dynamics, stability, and functional connectivity of HFOs in prolonged intracranial EEG recordings. These HFO sequences demonstrated a significant improvement in localization of epileptic tissue, with an 818.47% increase in concordance with seizure-onset zone (mean error: 2.92 mm), compared to conventional benchmarks. They also accurately predicted seizure outcomes for 90% AUC based on pre-surgical information using generalized linear models. Importantly, this mapping remained reliable even with short recordings (mean standard deviation: 3.23 mm for 30-minute segments). Furthermore, HFO sequences exhibited distinct yet highly repetitive spatiotemporal patterns, characterized by pronounced synchrony and predominant inward information flow from periphery towards areas involved in propagation, suggesting a crucial role for excitation-inhibition balance in HFO initiation and progression. Together, these findings shed light on the intricate organization of epileptic network and highlight the potential of HFO-sequencing as a translational tool for improved diagnosis, surgical targeting, and ultimately, better outcomes for vulnerable patients with drug-resistant epilepsy.

One Sentence Summary

Pathological fast brain oscillations travel like traffic along varied routes, outlining recurrently visited neural sites emerging as critical hotspots in epilepsy network.

Widespread slow oscillations support interictal epileptiform discharge networks in focal epilepsy

Interictal epileptiform discharges (IEDs) often co-occur across spatially-separated cortical regions, forming IED networks. However, the factors prompting IED propagation remain unelucidated. We hypothesized that slow oscillations (SOs) might facilitate IED propagation. Here, the amplitude and phase synchronization of SOs preceding propagating and non-propagating IEDs were compared in 22 patients with focal epilepsy undergoing intracranial electroencephalography (EEG) evaluation. Intracranial channels were categorized into the irritative zone (IZ) and normal zone (NOZ) regarding the presence of IEDs. During wakefulness, we found that pre-IED SOs within the IZ exhibited higher amplitudes for propagating IEDs than non-propagating IEDs (delta band: p = 0.001, theta band: p < 0.001). This increase in SOs was also concurrently observed in the NOZ (delta band: p = 0.04). Similarly, the inter-channel phase synchronization of SOs prior to propagating IEDs was higher than those preceding non-propagating IEDs in the IZ (delta band: p = 0.04). Through sliding window analysis, we observed that SOs preceding propagating IEDs progressively increased in amplitude and phase synchronization, while those preceding non-propagating IEDs remained relatively stable. Significant differences in amplitude occurred approximately 1150 ms before IEDs. During non-rapid eye movement (NREM) sleep, SOs on scalp recordings also showed higher amplitudes before intracranial propagating IEDs than before non-propagating IEDs (delta band: p = 0.006). Furthermore, the analysis of IED density around sleep SOs revealed that only high-amplitude sleep SOs demonstrated correlation with IED propagation. Overall, our study highlights that transient but widely distributed SOs are associated with IED propagation as well as generation in focal epilepsy during sleep and wakefulness, providing new insight into the EEG substrate supporting IED networks.

Passive and active markers of cortical excitability in epilepsy

Electroencephalography (EEG) has been the primary diagnostic tool in clinical epilepsy for nearly a century. Its review is performed using qualitative clinical methods that have changed little over time. However, the intersection of higher resolution digital EEG and analytical tools developed in the past decade invites a re-exploration of relevant methodology. In addition to the established spatial and temporal markers of spikes and high-frequency oscillations, novel markers involving advanced postprocessing and active probing of the interictal EEG are gaining ground. This review provides an overview of the EEG-based passive and active markers of cortical excitability in epilepsy and of the techniques developed to facilitate their identification. Several different emerging tools are discussed in the context of specific EEG applications and the barriers we must overcome to translate these tools into clinical practice.

Spontaneous fast-ultradian dynamics of polymorphic interictal events in drug-resistant focal epilepsy

OBJECTIVE

We studied the rate dynamics of interictal events occurring over fast-ultradian time scales, as commonly examined in clinics to guide surgical planning in epilepsy.

METHODS

Stereo-electroencephalography (SEEG) traces of 35 patients with good surgical outcome (Engel I) were analyzed. For this we developed a general data mining method aimed at clustering the plethora of transient waveform shapes including interictal epileptiform discharges (IEDs) and assessed the temporal fluctuations in the capability of mapping the epileptogenic zone (EZ) of each type of event.

RESULTS

We found that the fast-ultradian dynamics of the IED rate may effectively impair the precision of EZ identification, and appear to occur spontaneously, that is, not triggered by or exclusively associated with a particular cognitive task, wakefulness, sleep, seizure occurrence, post-ictal state, or antiepileptic drug withdrawal. Propagation of IEDs from the EZ to the propagation zone (PZ) could explain the observed fast-ultradian fluctuations in a reduced fraction of the analyzed patients, suggesting that other factors like the excitability of the epileptogenic tissue could play a more relevant role. A novel link was found between the fast-ultradian dynamics of the overall rate of polymorphic events and the rate of specific IEDs subtypes. We exploited this feature to estimate in each patient the 5 min interictal epoch for near-optimal EZ and resected-zone (RZ) localization. This approach produces at the population level a better EZ/RZ classification when compared to both (1) the whole time series available in each patient (p = .084 for EZ, p < .001 for RZ, Wilcoxon signed-rank test) and (2) 5 min epochs sampled randomly from the interictal recordings of each patient (p < .05 for EZ, p < .001 for RZ, 105 random samplings).

SIGNIFICANCE

Our results highlight the relevance of the fast-ultradian IED dynamics in mapping the EZ, and show how this dynamics can be estimated prospectively to inform surgical planning in epilepsy.

Data-driven approach for the delineation of the irritative zone in epilepsy in MEG

The reliable identification of the irritative zone (IZ) is a prerequisite for the correct clinical evaluation of medically refractory patients affected by epilepsy. Given the complexity of MEG data, visual analysis of epileptiform neurophysiological activity is highly time consuming and might leave clinically relevant information undetected. We recorded and analyzed the interictal activity from seven patients affected by epilepsy (Vectorview Neuromag), who successfully underwent epilepsy surgery (Engel > = II). We visually marked and localized characteristic epileptiform activity (VIS). We implemented a two-stage pipeline for the detection of interictal spikes and the delineation of the IZ. First, we detected candidate events from peaky ICA components, and then clustered events around spatio-temporal patterns identified by convolutional sparse coding. We used the average of clustered events to create IZ maps computed at the amplitude peak (PEAK), and at the 50% of the peak ascending slope (SLOPE). We validated our approach by computing the distance of the estimated IZ (VIS, SLOPE and PEAK) from the border of the surgically resected area (RA). We identified 25 spatiotemporal patterns mimicking the underlying interictal activity (3.6 clusters/patient). Each cluster was populated on average by 22.1 [15.0–31.0] spikes. The predicted IZ maps had an average distance from the resection margin of 8.4 ± 9.3 mm for visual analysis, 12.0 ± 16.5 mm for SLOPE and 22.7 ±. 16.4 mm for PEAK. The consideration of the source spread at the ascending slope provided an IZ closer to RA and resembled the analysis of an expert observer. We validated here the performance of a data-driven approach for the automated detection of interictal spikes and delineation of the IZ. This computational framework provides the basis for reproducible and bias-free analysis of MEG recordings in epilepsy.

Diffusion tractography predicts propagated high-frequency activity during epileptic spasms

OBJECTIVE

Determine the structural networks that constrain propagation of ictal oscillations during epileptic spasm events, and compare observed propagation patterns across patients with successful or unsuccessful surgical outcomes.

METHODS

Subdural electrode recordings of 18 young patients (age 1-11 years) were analyzed during epileptic spasm events to determine ictal networks and quantify the amplitude and onset time of ictal oscillations across the cortical surface. Corresponding structural networks were generated with diffusion MRI tractography by seeding the cortical region associated with the earliest average oscillation onset time, and white matter pathways connecting active electrode regions within the ictal network were isolated. Properties of this structural network were used to predict oscillation onset times and amplitudes, and this relationship was compared across patients who did and did not achieve seizure freedom following resective surgery.

RESULTS

Onset propagation patterns were relatively consistent across each patients' spasm events. An electrode's average ictal oscillation onset latency was most significantly associated with the length of direct corticocortical tracts connecting to the area with the earliest average oscillation onset (p < .001, model R²  = 0.54). Moreover, patients demonstrating a faster propagation of ictal oscillation signals within the corticocortical network were more likely to have seizure recurrence following resective surgery (p = .039). Ictal oscillation amplitude was also associated with connecting tractography length and weighted fractional anisotropy (FA) measures along these pathways (p = .002/.030, model R²  = 0.31/0.25). Characteristics of analogous corticothalamic pathways did not show significant associations with ictal oscillation onset latency or amplitude.

SIGNIFICANCE

Spatiotemporal propagation patterns of high-frequency activity in epileptic spasms align with length and FA measures from onset-originating corticocortical pathways. Considering data in this individualized framework may help inform surgical decision making and expectations of surgical outcomes.

Interictal spike networks predict surgical outcome in patients with drug-resistant focal epilepsy

OBJECTIVE

To determine if properties of epileptic networks could be delineated using interictal spike propagation seen on stereo-electroencephalography (SEEG) and if these properties could predict surgical outcome in patients with drug-resistant epilepsy.

METHODS

We studied the SEEG of 45 consecutive drug-resistant epilepsy patients who underwent subsequent epilepsy surgery: 18 patients with good post-surgical outcome (Engel I) and 27 with poor outcome (Engel II-IV). Epileptic networks were derived from interictal spike propagation; these networks described the generation and propagation of interictal epileptic activity. We compared the regions in which spikes were frequent and the regions responsible for generating spikes to the area of resection and post-surgical outcome. We developed a measure termed source spike concordance, which integrates information about both spike rate and region of spike generation.

RESULTS

Inclusion in the resection of regions with high spike rate is associated with good post-surgical outcome (sensitivity = 0.82, specificity = 0.73). Inclusion in the resection of the regions responsible for generating interictal epileptic activity independently of rate is also associated with good post-surgical outcome (sensitivity = 0.88, specificity = 0.82). Finally, when integrating the spike rate and the generators, we find that the source spike concordance measure has strong predictability (sensitivity = 0.91, specificity = 0.94).

INTERPRETATIONS

Epileptic networks derived from interictal spikes can determine the generators of epileptic activity. Inclusion of the most active generators in the resection is strongly associated with good post-surgical outcome. These epileptic networks may aid clinicians in determining the area of resection during pre-surgical evaluation.

Localizing the epileptogenic zone

PURPOSE OF REVIEW

Epilepsy surgery is the therapy of choice for 30-40% of people with focal drug-resistant epilepsy. Currently only ∼60% of well selected patients become postsurgically seizure-free underlining the need for better tools to identify the epileptogenic zone. This article reviews the latest neurophysiological advances for EZ localization with emphasis on ictal EZ identification, interictal EZ markers, and noninvasive neurophysiological mapping procedures.

RECENT FINDINGS

We will review methods for computerized EZ assessment, summarize computational network approaches for outcome prediction and individualized surgical planning. We will discuss electrical stimulation as an option to reduce the time needed for presurgical work-up. We will summarize recent research regarding high-frequency oscillations, connectivity measures, and combinations of multiple markers using machine learning. This latter was shown to outperform single markers. The role of NREM sleep for best identification of the EZ interictally will be discussed. We will summarize recent large-scale studies using electrical or magnetic source imaging for clinical decision-making.

SUMMARY

New approaches based on technical advancements paired with artificial intelligence are on the horizon for better EZ identification. They are ultimately expected to result in a more efficient, less invasive, and less time-demanding presurgical investigation.

Spatial distribution of interictal spikes fluctuates over time and localizes seizure onset

The location of interictal spikes is used to aid surgical planning in patients with medically refractory epilepsy; however, their spatial and temporal dynamics are poorly understood. In this study, we analysed the spatial distribution of interictal spikes over time in 20 adult and paediatric patients (12 females, mean age = 34.5 years, range = 5-58) who underwent intracranial EEG evaluation for epilepsy surgery. Interictal spikes were detected in the 24 h surrounding each seizure and spikes were clustered based on spatial location. The temporal dynamics of spike spatial distribution were calculated for each patient and the effects of sleep and seizures on these dynamics were evaluated. Finally, spike location was assessed in relation to seizure onset location. We found that spike spatial distribution fluctuated significantly over time in 14/20 patients (with a significant aggregate effect across patients, Fisher's method: P < 0.001). A median of 12 sequential hours were required to capture 80% of the variability in spike spatial distribution. Sleep and postictal state affected the spike spatial distribution in 8/20 and 4/20 patients, respectively, with a significant aggregate effect (Fisher's method: P < 0.001 for each). There was no evidence of pre-ictal change in the spike spatial distribution for any patient or in aggregate (Fisher's method: P = 0.99). The electrode with the highest spike frequency and the electrode with the largest area of downstream spike propagation both localized the seizure onset zone better than predicted by chance (Wilcoxon signed-rank test: P = 0.005 and P = 0.002, respectively). In conclusion, spikes localize seizure onset. However, temporal fluctuations in spike spatial distribution, particularly in relation to sleep and post-ictal state, can confound localization. An adequate duration of intracranial recording-ideally at least 12 sequential hours-capturing both sleep and wakefulness should be obtained to sufficiently sample the interictal network.

Networks in Temporal Lobe Epilepsy

Temporal lobe epilepsy (TLE) is the most common type of drug-resistant focal epilepsy. Epilepsy can be conceptualized as a network disorder with the epileptogenic zone a critical node of the network. Temporal lobe networks can be identified on the microscale and macroscale, both during the interictal and ictal periods. This review summarizes the current understanding of TLE networks as studied by neurophysiological and imaging techniques discussing both functional and structural connectivity.