Psychiatric complications following SEEG-guided radiofrequency thermocoagulations in patients with drug-resistant epilepsy

SEEG-guided radiofrequency thermocoagulation (RF-TC) in the epileptogenic regions is a therapeutic option for patients with drug-resistant focal epilepsy who may have or not indication for epilepsy surgery. The most common adverse events of RF-TC are seizures, headaches, somatic pain, and sensory-motor deficits. If RF-TC could lead to psychiatric complications is unknown. In the present study, seven out of 164 patients (4.2 %) experienced psychiatric decompensation with or without memory deterioration after RF-TC of bilateral or unilateral amygdala and hippocampus. The appearance of symptoms was either acute, subacute, or chronic and the symptoms were either transient or lasted for several months. Common features among these patients were female sex, mesial temporal epilepsy, and a pre-existing history of psychological distress and memory dysfunction. Our study highlights the possibility of neuropsychiatric deterioration in specific patients following SEEG-guided RF-TC, despite its rarity.

Correspondence between scalp-EEG and stereoelectroencephalography seizure-onset patterns in patients with MRI-negative drug-resistant focal epilepsy

OBJECTIVE

Our objective was to evaluate the relationship between scalp-EEG and stereoelectroencephalography (SEEG) seizure-onset patterns (SOP) in patients with MRI-negative drug-resistant focal epilepsy.

METHODS

We analyzed retrospectively 41 patients without visible lesion on brain MRI who underwent video-EEG followed by SEEG. We defined five types of SOPs on scalp-EEG and eight types on SEEG. We examined how various clinical variables affected scalp-EEG SOPs.

RESULTS

The most prevalent scalp SOPs were rhythmic sinusoidal activity (56.8%), repetitive epileptiform discharges (22.7%), and paroxysmal fast activity (15.9%). The presence of paroxysmal fast activity on scalp-EEG was always seen without delay from clinical onset and correlated with the presence of low-voltage fast activity in SEEG (sensitivity = 22.6%, specificity = 100%). The main factor explaining the discrepancy between the scalp and SEEG SOPs was the delay between clinical and scalp-EEG onset. There was a correlation between the scalp and SEEG SOPs when the scalp onset was simultaneous with the clinical onset (p = 0.026). A significant delay between clinical and scalp discharge onset was observed in 25% of patients and featured always with a rhythmic sinusoidal activity on scalp, corresponding to similar morphology of the discharge on SEEG. The presence of repetitive epileptiform discharges on scalp was associated with an underlying focal cortical dysplasia (sensitivity = 30%, specificity = 90%). There was no significant association between the scalp SOP and the epileptogenic zone location (deep or superficial), or surgical outcome.

SIGNIFICANCE

In patients with MRI-negative focal epilepsy, scalp SOP could suggest the SEEG SOP and some etiology (focal cortical dysplasia) but has no correlation with surgical prognosis. Scalp SOP correlates with the SEEG SOP in cases of simultaneous EEG and clinical onset; otherwise, scalp SOP reflects the propagation of the SEEG discharge.

PLAIN LANGUAGE SUMMARY

We looked at the correspondence between the electrical activity recorded during the start of focal seizure using scalp and intracerebral electrodes in patients with no visible lesion on MRI. If there is a fast activity on scalp, it reflects similar activity inside the brain. We found a good correspondence between scalp and intracerebral electrical activity for cases without significant delay between clinical and scalp electrical onset (seen in 75% of the cases we studied). Visualizing repetitive epileptic activity on scalp could suggest a particular cause of the epilepsy: a subtype of brain malformation called focal cortical dysplasia.

Stereo-EEG-based ictal functional connectivity in patients with periventricular nodular heterotopia-related epilepsy

Nodular heterotopia (NH)-related drug-resistant epilepsy is challenging due to the deep location of the NH and the complexity of the underlying epileptogenic network. Using ictal stereo-electroencephalography (SEEG) and functional connectivity (FC) analyses in 14 patients with NH-related drug-resistant epilepsy, we aimed to determine the leading structure during seizures. For this purpose, we compared node IN and OUT strength between bipolar channels inside the heterotopia and inside gray matter, at the group level and at the individual level. At seizure onset, the channels within NH belonging to the epileptogenic and/or propagation network showed higher node OUT-strength than the channels within the gray matter (p = .03), with higher node OUT-strength than node IN-strength (p = .03). These results are in favor of a "leading" role of NH during seizure onset when involved in the epileptogenic- or propagation-zone network (50% of patients). However, when looking at the individual level, no significant difference between NH and gray matter was found, except for one patient (in two of three seizures). This result confirms the heterogeneity and the complexity of the epileptogenic network organization in NH and the need for SEEG exploration to characterize more precisely patient-specific epileptogenic network organization.

Combining independent component analysis and source localization for improving spatial sampling of stereoelectroencephalography in epilepsy

Stereoelectroencephalography is a powerful intracerebral EEG recording method for the presurgical evaluation of epilepsy. It consists in implanting depth electrodes in the patient's brain to record electrical activity and map the epileptogenic zone, which should be resected to render the patient seizure-free. Stereoelectroencephalography has high spatial accuracy and signal-to-noise ratio but remains limited in the coverage of the explored brain regions. Thus, the implantation might provide a suboptimal sampling of epileptogenic regions. We investigate the potential of improving a suboptimal stereoelectroencephalography recording by performing source localization on stereoelectroencephalography signals. We propose combining independent component analysis, connectivity measures to identify components of interest, and distributed source modelling. This approach was tested on two patients with two implantations each, the first failing to characterize the epileptogenic zone and the second giving a better diagnosis. We demonstrate that ictal and interictal source localization performed on the first stereoelectroencephalography recordings matches the findings of the second stereo-EEG exploration. Our findings suggest that independent component analysis followed by source localization on the topographies of interest is a promising method for retrieving the epileptogenic zone in case of suboptimal implantation.

Permutation entropy-derived parameters to estimate the epileptogenic zone network

OBJECTIVE

Quantification of the epileptogenic zone network (EZN) most frequently implies analysis of seizure onset. However, important information can also be obtained from the postictal period, characterized by prominent changes in the EZN. We used permutation entropy (PE), a measure of signal complexity, to analyze the peri-ictal stereoelectroencephalography (SEEG) signal changes with emphasis on the postictal state. We sought to determine the best PE-derived parameter (PEDP) for identifying the EZN.

METHODS

Several PEDPs were computed retrospectively on SEEG-recorded seizures of 86 patients operated on for drug-resistant epilepsy: mean baseline preictal entropy, minimum ictal entropy, maximum postictal entropy, the ratio between the maximum postictal and the minimum ictal entropy, and the ratio between the maximum postictal and the baseline preictal entropy. The performance of each biomarker was assessed by comparing the identified epileptogenic contacts or brain regions against the EZN defined by clinical analysis incorporating the Epileptogenicity Index and the connectivity epileptogenicity index methods (EZNc), using the receiver-operating characteristic and precision-recall.

RESULTS

The ratio between the maximum postictal and the minimum ictal entropy (defined as the Permutation Entropy Index [PEI]) proved to be the best-performing PEDP to identify the EZNC . It demonstrated the highest area under the curve (AUC) and F1 score at the contact level (AUC 0.72; F1 0.39) and at the region level (AUC 0.78; F1 0.47). PEI values gradually decreased between the EZN, the propagation network, and the non-involved regions. PEI showed higher performance in patients with slow seizure-onset patterns than in those with fast seizure-onset patterns. The percentage of resected epileptogenic regions defined by PEI was significantly correlated with surgical outcome.

SIGNIFICANCE

PEI is a promising tool to improve the delineation of the EZN. PEI combines ease and robustness in a routine clinical setting with high sensitivity for seizures without fast activity at seizure onset.

The Temporal Lobe Club: Newer Approaches to Treat Temporal Lobe Epilepsy

This brief review summarizes presentations at the Temporal Lobe Club Special Interest Group session held in December 2022 at the American Epilepsy Society meeting. The session addressed newer methods to treat temporal epilepsy, including methods currently in clinical use and techniques under investigation. Brief summaries are provided for each of 4 lectures. Dr Chengyuan Wu discussed ablative techniques such as laser interstitial thermal ablation, radiofrequency ablation, focused ultrasound; Dr Joon Kang reviewed neuromodulation techniques including electrical stimulation and focused ultrasound; Dr Julia Makhalova discussed network effects of the aforementioned techniques; and Dr Derek Southwell reviewed inhibitory interneuron transplantation. These summaries are intended to provide a brief overview and references are provided for the reader to learn more about each topic.

The role of quantitative markers in surgical prognostication after stereoelectroencephalography

OBJECTIVE

Stereoelectroencephalography (SEEG) is the reference method in the presurgical exploration of drug-resistant focal epilepsy. However, prognosticating surgery on an individual level is difficult. A quantified estimation of the most epileptogenic regions by searching for relevant biomarkers can be proposed for this purpose. We investigated the performances of ictal (Epileptogenicity Index, EI; Connectivity EI, cEI), interictal (spikes, high-frequency oscillations, HFO [80-300 Hz]; Spikes × HFO), and combined (Spikes × EI; Spikes × cEI) biomarkers in predicting surgical outcome and searched for prognostic factors based on SEEG-signal quantification.

METHODS

Fifty-three patients operated on following SEEG were included. We compared, using precision-recall, the epileptogenic zone quantified using different biomarkers (EZq ) against the visual analysis (EZC ). Correlations between the EZ resection rates or the EZ extent and surgical prognosis were analyzed.

RESULTS

EI and Spikes × EI showed the best precision against EZc (0.74; 0.70), followed by Spikes × cEI and cEI, whereas interictal markers showed lower precision. The EZ resection rates were greater in seizure-free than in non-seizure-free patients for the EZ defined by ictal biomarkers and were correlated with the outcome for EI and Spikes × EI. No such correlation was found for interictal markers. The extent of the quantified EZ did not correlate with the prognosis.

INTERPRETATION

Ictal or combined ictal-interictal markers overperformed the interictal markers both for detecting the EZ and predicting seizure freedom. Combining ictal and interictal epileptogenicity markers improves detection accuracy. Resection rates of the quantified EZ using ictal markers were the only statistically significant determinants for surgical prognosis.

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.

Multi-scale structural alterations of the thalamus and basal ganglia in focal epilepsy using 7T MRI

Focal epilepsy is characterized by repeated spontaneous seizures that originate from cortical epileptogenic zone networks (EZN). Analysis of intracerebral recordings showed that subcortical structures, and in particular the thalamus, play an important role in seizure dynamics as well, supporting their structural alterations reported in the neuroimaging literature. Nonetheless, between-patient differences in EZN localization (e.g., temporal vs. non-temporal lobe epilepsy) as well as extension (i.e., number of epileptogenic regions) might impact the magnitude as well as spatial distribution of subcortical structural changes. Here we used 7 Tesla MRI T₁ data to provide an unprecedented description of subcortical morphological (volume, tissue deformation, and shape) and longitudinal relaxation (T₁ ) changes in focal epilepsy patients and evaluate the impact of the EZN and other patient-specific clinical features. Our results showed variable levels of atrophy across thalamic nuclei that appeared most prominent in the temporal lobe epilepsy group and the side ipsilateral to the EZN, while shortening of T₁ was especially observed for the lateral thalamus. Multivariate analyses across thalamic nuclei and basal ganglia showed that volume acted as the dominant discriminator between patients and controls, while (posterolateral) thalamic T₁ measures looked promising to further differentiate patients based on EZN localization. In particular, the observed differences in T₁ changes between thalamic nuclei indicated differential involvement based on EZN localization. Finally, EZN extension was found to best explain the observed variability between patients. To conclude, this work revealed multi-scale subcortical alterations in focal epilepsy as well as their dependence on several clinical characteristics.

Ictal Fear during parietal seizures

Ictal fear is characterized by subjective fear sensation and consistent clinical manifestations during seizures. This phenomenon is rarely observed in parietal seizures. We report anatomical electroclinical correlations of an SEEG-recorded seizure with prominent fear semiology. Seizure onset zone was quantified using the Connectivity Epileptogenicity Index method (cEI). Occurrence of fear during seizures was related to the involvement of the left inferior parietal cortex and the superior temporal gyrus without amygdala involvement. Our case confirms that parietal seizure can produce ictal fear without concomitant involvement of the limbic temporal network.

The origin of pleasant sensations: Insight from direct electrical brain stimulation

Research into the neuroanatomical basis of emotions has resulted in a plethora of studies over the last twenty years. However, studies about positive emotions and pleasant sensations remain rare and their anatomical-functional bases are less understood than that of negative emotions. Pleasant sensations can be evoked by electrical brain stimulations (EBS) during stereotactic electroencephalography (SEEG) performed for pre-surgical exploration in patients with drug-resistant epilepsy. We conducted a retrospective analysis of 10 106 EBS performed in 329 patients implanted with SEEG in our epileptology department. We found that 13 EBS in 9 different patients evoked pleasant sensations (.60% of all responses). By contrast we collected 111 emotional responses of negative valence (i.e., 5.13% of all responses). EBS evoking pleasant sensations were applied at 50 Hz with an average intensity of 1.4 ± .55 mA (range .5-2 mA). Pleasant sensations were reported by nine patients of which three patients presented responses to several EBS. We found a male predominance among the patients reporting pleasant sensations and a prominent role of the right cerebral hemisphere. Results show the preponderant role of the dorsal anterior insula and amygdala in the occurrence of pleasant sensations.

Changes in Local and Network Brain Activity After Stereotactic Thermocoagulation in Patients with Drug-Resistant Epilepsy

OBJECTIVE

Stereoelectroencephalography-guided radiofrequency thermocoagulation (SEEG-guided RF-TC) aims to reduce seizure frequency by modifying epileptogenic networks through local thermocoagulative lesions. Although RF-TC is hypothesized to functionally modify brain networks, reports of changes in functional connectivity (FC) following the procedure are missing. We evaluated, by means of SEEG recordings, whether variation in brain activity after RF-TC is related to clinical outcome.

METHODS

Interictal SEEG recordings from 33 DRE patients were analyzed. Therapeutic response was defined as more than 50% reduction in seizure frequency for at least one month following RF-TC. Local (power spectral density, PSD) and FC changes were evaluated in three-minute segments recorded shortly before (baseline), shortly after and 15 minutes after RF-TC. The PSD and FC strength values after thermocoagulation were compared with baseline as well as between the responder and non-responder groups.

RESULTS

In responders, we found a significant reduction in PSD after RF-TC in channels that were thermocoagulated (TC) for all frequency bands (p-value =0.007 for broad, delta and theta, p-value <0.001 for alpha and beta bands). However, we did not observe such PSD decrease in non-responders. At the network level, non-responders displayed a significant FC increase in all frequency bands except theta (broad, delta, beta band: p-value < 0.001; alpha band: p-value < 0.01), while responders showed a significant FC decrease in delta (p-value<0.001) and alpha bands (p-value<0.05). Non-responders showed stronger FC changes with respect to responders exclusively in TC channels (broad, alpha, theta, beta: p-value>0.05; delta: p= 0.001).

SIGNIFICANCE

Thermocoagulation induces both local and network-related (FC) changes in electrical brain activity of patients with DRE lasting for at least 15 minutes. This study demonstrates that the observed short-term modifications in brain network and local activity significantly differ between responders and non-responders and opens new perspectives for studying the longer-lasting functional connectivity changes after RF-TC.

The anterior and pulvinar thalamic nuclei interactions in mesial temporal lobe seizure networks

OBJECTIVE

To evaluate the respective roles of the anterior thalamic nucleus (ANT) and the medial pulvinar (PuM) during mesial temporal lobe seizures recorded by stereoelectroencephalography (SEEG).

METHODS

We assessed functional connectivity (FC) in 15 SEEG recorded seizures from 6 patients using a non-linear correlation method. Functional interactions were explored between the mesial temporal region, the temporal neocortex, ANT and PuM. The node total-strength (the summed connectivity of the node with all other nodes) as well as the directionality of the links (IN and OUT strengths) were calculated to estimate drivers and receivers during the cortico-thalamic interactions.

RESULTS

Significant increased thalamo-cortical FC during seizures was observed, with the node total-strength reaching a maximum at seizure end. There was no significant difference in global connectivity values between ANT and PuM. Regarding directionality, significantly higher thalamic IN strength values were observed. However, compared to ANT, PuM appeared to be the driver at the end of seizures with synchronous termination.

CONCLUSIONS

This work demonstrates that during temporal seizures, both thalamic nuclei are highly connected with the mesial temporal region and that PuM could play a role in seizure termination.

SIGNIFICANCE

Understanding functional connectivity between the mesial temporal and thalamic nuclei could contribute to the development of target-specific deep brain stimulation strategies for drug-resistant epilepsy.

Personalized whole brain modeling of status epilepticus

How status epilepticus (SE) is generated and propagates in the brain is not known. As for seizures, a patient-specific approach is necessary, and the analysis should be performed at the whole brain level. Personalized brain models can be used to study seizure genesis and propagation at the whole brain scale in The Virtual Brain (TVB), using the Epileptor mathematical construct. Building on the fact that SE is part of the repertoire of activities that the Epileptor can generate, we present the first attempt to model SE at the whole brain scale in TVB, using data from a patient who experienced SE during presurgical evaluation. Simulations reproduced the patterns found with SEEG recordings. We find that if, as expected, the pattern of SE propagation correlates with the properties of the patient's structural connectome, SE propagation also depends upon the global state of the network, i.e., that SE propagation is an emergent property. We conclude that individual brain virtualization can be used to study SE genesis and propagation. This type of theoretical approach may be used to design novel interventional approaches to stop SE. This paper was presented at the 8th London-Innsbruck Colloquium on Status Epilepticus and Acute Seizures held in September 2022.

Personalised virtual brain models in epilepsy

Individuals with drug-resistant focal epilepsy are candidates for surgical treatment as a curative option. Before surgery can take place, the patient must have a presurgical evaluation to establish whether and how surgical treatment might stop their seizures without causing neurological deficits. Virtual brains are a new digital modelling technology that map the brain network of a person with epilepsy, using data derived from MRI. This technique produces a computer simulation of seizures and brain imaging signals, such as those that would be recorded with intracranial EEG. When combined with machine learning, virtual brains can be used to estimate the extent and organisation of the epileptogenic zone (ie, the brain regions related to seizure generation and the spatiotemporal dynamics during seizure onset). Virtual brains could, in the future, be used for clinical decision making, to improve precision in localisation of seizure activity, and for surgical planning, but at the moment these models have some limitations, such as low spatial resolution. As evidence accumulates in support of the predictive power of personalised virtual brain models, and as methods are tested in clinical trials, virtual brains might inform clinical practice in the near future.

Delineating epileptogenic networks using brain imaging data and personalized modeling in drug-resistant epilepsy

Precise estimates of epileptogenic zone networks (EZNs) are crucial for planning intervention strategies to treat drug-resistant focal epilepsy. Here, we present the virtual epileptic patient (VEP), a workflow that uses personalized brain models and machine learning methods to estimate EZNs and to aid surgical strategies. The structural scaffold of the patient-specific whole-brain network model is constructed from anatomical T1 and diffusion-weighted magnetic resonance imaging. Each network node is equipped with a mathematical dynamical model to simulate seizure activity. Bayesian inference methods sample and optimize key parameters of the personalized model using functional stereoelectroencephalography recordings of patients' seizures. These key parameters together with their personalized model determine a given patient's EZN. Personalized models were further used to predict the outcome of surgical intervention using virtual surgeries. We evaluated the VEP workflow retrospectively using 53 patients with drug-resistant focal epilepsy. VEPs reproduced the clinically defined EZNs with a precision of 0.6, where the physical distance between epileptogenic regions identified by VEP and the clinically defined EZNs was small. Compared with the resected brain regions of 25 patients who underwent surgery, VEP showed lower false discovery rates in seizure-free patients (mean, 0.028) than in non-seizure-free patients (mean, 0.407). VEP is now being evaluated in an ongoing clinical trial (EPINOV) with an expected 356 prospective patients with epilepsy.

Consciousness alteration in focal epilepsy is related to loss of signal complexity and information processing

Alteration of awareness is a main feature of focal epileptic seizures. In this work, we studied how the information contained in EEG signals was modified during temporal lobe seizures with altered awareness by using permutation entropy (PE) as a measure of the complexity of the signal. PE estimation was performed in thirty-six seizures of sixteen patients with temporal lobe epilepsy who underwent SEEG recordings. We tested whether altered awareness (based on the Consciousness Seizure Score) was correlated with a loss of signal complexity. We estimated global changes in PE as well as regional changes to gain insight into the mechanisms associated with awareness impairment. Our results reveal a positive correlation between the decrease of entropy and the consciousness score as well as the existence of a threshold on entropy that could discriminate seizures with no alteration of awareness from seizures with profound alteration of awareness. The loss of signal complexity was diffuse, extending bilaterally and to the associative cortices, in patients with profound alteration of awareness and limited to the temporal mesial structures in patients with no alteration of awareness. Thus PE is a promising tool to discriminate between the different subgroups of awareness alteration in TLE.

Combining sodium MRI, proton MR spectroscopic imaging, and intracerebral EEG in epilepsy

Whole brain ionic and metabolic imaging has potential as a powerful tool for the characterization of brain diseases. We combined sodium MRI (²³ Na MRI) and ¹ H-MR Spectroscopic Imaging (¹ H-MRSI), assessing changes within epileptogenic networks in comparison with electrophysiologically normal networks as defined by stereotactic EEG (SEEG) recordings analysis. We applied a multi-echo density adapted 3D projection reconstruction pulse sequence at 7 T (²³ Na-MRI) and a 3D echo-planar spectroscopic imaging sequence at 3 T (¹ H-MRSI) in 19 patients suffering from drug-resistant focal epilepsy who underwent presurgical SEEG. We investigated ²³ Na MRI parameters including total sodium concentration (TSC) and the sodium signal fraction associated with the short component of T₂ * decay (f), alongside the level of metabolites N-acetyl aspartate (NAA), choline compounds (Cho), and total creatine (tCr). All measures were extracted from spherical regions of interest (ROIs) centered between two adjacent SEEG electrode contacts and z-scored against the same ROI in controls. Group comparison showed a significant increase in f only in the epileptogenic zone (EZ) compared to controls and compared to patients' propagation zone (PZ) and non-involved zone (NIZ). TSC was significantly increased in all patients' regions compared to controls. Conversely, NAA levels were significantly lower in patients compared to controls, and lower in the EZ compared to PZ and NIZ. Multiple regression analyzing the relationship between sodium and metabolites levels revealed significant relations in PZ and in NIZ but not in EZ. Our results are in agreement with the energetic failure hypothesis in epileptic regions associated with widespread tissue reorganization.

Signal processing and computational modeling for interpretation of SEEG-recorded interictal epileptiform discharges in epileptogenic and non-epileptogenic zones

OBJECTIVE

In partial epilepsies, interictal epileptiform discharges (IEDs) are paroxysmal events observed in epileptogenic and non-epileptogenic zones. IEDs' generation and recurrence are subject to different hypotheses: they appear through glutamatergic and GABAergic processes; they may trigger seizures or prevent seizure propagation. This paper focuses on a specific class of IEDs, spike-waves (SWs), characterized by a short-duration spike followed by a longer duration wave, both of the same polarity. Signal analysis and neurophysiological mathematical models are used to interpret puzzling IED generation.

APPROACH

Interictal activity was recorded by intracranial stereo-electroencephalography (SEEG) electrodes in five different patients. SEEG experts identified the epileptic and non-epileptic zones in which IEDs were detected. After quantifying spatial and temporal features of the detected IEDs, the most significant features for classifying epileptic and non-epileptic zones were determined. A neurophysiologically-plausible mathematical model was then introduced to simulate the IEDs and understand the underlying differences observed in epileptic and non-epileptic zone IEDs.

MAIN RESULTS

Two classes of SWs were identified according to subtle differences in morphology and timing of the spike and wave component. Results showed that type-1 SWs were generated in epileptogenic regions also involved at seizure onset, while type-2 SWs were produced in the propagation or non-involved areas. The modeling study indicated that synaptic kinetics, cortical organization, and network interactions determined the morphology of the simulated SEEG signals. Modeling results suggested that the IED morphologies were linked to the degree of preserved inhibition.

SIGNIFICANCE

This work contributes to the understanding of different mechanisms generating IEDs in epileptic networks. The combination of signal analysis and computational models provides an efficient framework for exploring IEDs in partial epilepsies and classifying epileptogenic and non-epileptogenic zones.

A personalizable autonomous neural mass model of epileptic seizures

Work in the last two decades has shown that neural mass models (NMM) can realistically reproduce and explain epileptic seizure transitions as recorded by electrophysiological methods (EEG, SEEG). In previous work, advances were achieved by increasing excitation and heuristically varying network inhibitory coupling parameters in the models. Based on these early studies, we provide a laminar NMM capable of realistically reproducing the electrical activity recorded by SEEG in the epileptogenic zone during interictal to ictal states. With the exception of the external noise input into the pyramidal cell population, the model dynamics are autonomous. By setting the system at a point close to bifurcation, seizure-like transitions are generated, including pre-ictal spikes, low voltage fast activity, and ictal rhythmic activity. A novel element in the model is a physiologically motivated algorithm for chloride dynamics: the gain of GABAergic post-synaptic potentials is modulated by the pathological accumulation of chloride in pyramidal cells due to high inhibitory input and/or dysfunctional chloride transport. In addition, in order to simulate SEEG signals for comparison with real seizure recordings, the NMM is embedded first in a layered model of the neocortex and then in a realistic physical model. We compare modeling results with data from four epilepsy patient cases. By including key pathophysiological mechanisms, the proposed framework captures succinctly the electrophysiological phenomenology observed in ictal states, paving the way for robust personalization methods based on NMMs.

Virtual Epileptic Patient brain modeling: relationships with seizure onset and surgical outcome

Objective

The virtual epileptic patient (VEP) is a large‐scale brain modeling method based on virtual brain technology, using stereoelectroencephalography (SEEG), anatomical data (magnetic resonance imaging [MRI] and connectivity), and a computational neuronal model to provide computer simulations of a patient's seizures. VEP has potential interest in the presurgical evaluation of drug‐resistant epilepsy by identifying regions most likely to generate seizures. We aimed to assess the performance of the VEP approach in estimating the epileptogenic zone and in predicting surgical outcome.

Methods

VEP modeling was retrospectively applied in a cohort of 53 patients with pharmacoresistant epilepsy and available SEEG, T1‐weighted MRI, and diffusion‐weighted MRI. Precision recall was used to compare the regions identified as epileptogenic by VEP (EZ_VEP) to the epileptogenic zone defined by clinical analysis incorporating the Epileptogenicity Index (EI) method (EZ_C). In 28 operated patients, we compared the VEP results and clinical analysis with surgical outcome.

Results

VEP showed a precision of 64% and a recall of 44% for EZ_VEP detection compared to EZ_C. There was a better concordance of VEP predictions with clinical results, with higher precision (77%) in seizure‐free compared to non‐seizure‐free patients. Although the completeness of resection was significantly correlated with surgical outcome for both EZ_C and EZ_VEP, there was a significantly higher number of regions defined as epileptogenic exclusively by VEP that remained nonresected in non‐seizure‐free patients.

Significance

VEP is the first computational model that estimates the extent and organization of the epileptogenic zone network. It is characterized by good precision in detecting epileptogenic regions as defined by a combination of visual analysis and EI. The potential impact of VEP on improving surgical prognosis remains to be exploited. Analysis of factors limiting the performance of the actual model is crucial for its further development.

Epileptogenic networks in drug-resistant epilepsy with amygdala enlargement: Assessment with stereo-EEG and 7 T MRI

OBJECTIVE

Amygdala enlargement is increasingly described in association with temporal lobe epilepsies. Its significance, however, remains uncertain both in terms of etiology and its link with psychiatric disorders and of its involvement in the epileptogenic zone. We assessed the epileptogenic networks underlying drug-resistant epilepsy with amygdala enlargement and investigated correlations between clinical features, epileptogenicity and morphovolumetric amygdala characteristics.

METHODS

We identified 12 consecutive patients suffering from drug-resistant epilepsy with visually suspected amygdala enlargement and available stereoelectroencephalographic recording. The epileptogenic zone was defined using the Connectivity Epileptogenicity Index. Morphovolumetric measurements were performed using automatic segmentation and co-registration on the 7TAMIbrain Amygdala atlas.

RESULTS

The epileptogenic zone involved the enlarged amygdala in all but three cases and corresponded to distributed, temporal-insular, temporal-insular-prefrontal or prefrontal-temporal networks in ten cases, while only two were temporo-mesial networks. Morphovolumetrically, amygdala enlargement was bilateral in 75% of patients. Most patients presented psychiatric comorbidities (anxiety, depression, posttraumatic stress disorder). The level of depression defined by screening questionnaire was positively correlated with the extent of amygdala enlargement.

CONCLUSIONS

Drug-resistant epilepsy with amygdala enlargement is heterogeneous; most cases implied "temporal plus" networks.

SIGNIFICANCE

The enlarged amygdala could reflect an interaction of stress-mediated limbic network alterations and mechanisms of epileptogenesis.

Changes in epileptogenicity biomarkers after stereotactic thermocoagulation

OBJECTIVE

Stereo-electroencephalography (SEEG)-guided radiofrequency thermocoagulation (RF-TC) aims at modifying epileptogenic networks to reduce seizure frequency. High-frequency oscillations (HFOs), spikes, and cross-rate are quantifiable epileptogenic biomarkers. In this study, we sought to evaluate, using SEEG signals recorded before and after thermocoagulation, whether a variation in these markers is related to the therapeutic effect of this procedure and to the outcome of surgery.

METHODS

Interictal segments of SEEG signals were analyzed in 38 patients during presurgical evaluation. We used an automatized method to quantify the rate of spikes, rate of HFOs, and cross-rate (a measure combining spikes and HFOs) before and after thermocoagulation. We analyzed the differences both at an individual level with a surrogate approach and at a group level with analysis of variance. We then evaluated the correlation between these variations and the clinical response to RF-TC and to subsequent resective surgery.

RESULTS

After thermocoagulation, 19 patients showed a clinical improvement. At the individual level, clinically improved patients more frequently had a reduction in spikes and cross-rate in the epileptogenic zone than patients without clinical improvement (p = .002, p = .02). At a group level, there was a greater decrease of HFOs in epileptogenic and thermocoagulated zones in patients with clinical improvement (p < .05) compared to those with no clinical benefit. Eventually, a significant decrease of all the markers after RF-TC was found in patients with a favorable outcome of resective surgery (spikes, p = .026; HFOs, p = .03; cross-rate, p = .03).

SIGNIFICANCE

Quantified changes in the rate of spikes, rate of HFOs, and cross-rate can be observed after thermocoagulation, and the reduction of these markers correlates with a favorable clinical outcome after RF-TC and with successful resective surgery. This may suggest that interictal biomarker modifications after RF-TC can be clinically used to predict the effectiveness of the thermocoagulation procedure and the outcome of resective surgery.

Repair capacity for platinum-DNA adducts determines the severity of cisplatin-induced peripheral neuropathy

The pronounced neurotoxicity of the potent antitumor drug cisplatin frequently results in the onset of peripheral polyneuropathy (PNP), which is assumed to be initially triggered by platination products in the nuclear DNA of affected tissues. To further elucidate the molecular mechanisms, we analyzed in a mouse model the formation and processing of the main cisplatin-induced DNA adduct (guanine-guanine intrastrand cross-link) in distinct neuronal cell types by adduct-specific monoclonal antibodies. Comparison of the adduct kinetics in cisplatin-injected mice either proficient or deficient for nucleotide excision repair (NER) functions revealed the essential role of this DNA repair pathway in protecting differentiated cells of the nervous system from excessive formation of such lesions. Hence, chronic exposure to cisplatin resulted in an accelerated accumulation of unrepaired intrastrand cross-links in neuronal cells of mice with dysfunctional NER. The augmented adduct levels in dorsal root ganglion (DRG) cells of those animals coincided with an earlier onset of PNP-like functional disturbance of their sensory nervous system. Independently from the respective repair phenotype, the amount of persisting DNA cross-links in DRG neurons at a given cumulative dose was significantly correlated to the degree of sensory impairment as measured by electroneurography. Collectively, these findings suggest a new model for the processing of cisplatin adducts in primary neuronal cells and accentuate the crucial role of effectual DNA repair capacity in the target cells for the individual risk of therapy-induced PNP.