Seizure Network Research Articles

Seizure Detection and Lateralization Using Thalamic Deep Brain Stimulator Recordings.

The lack of reliable seizure detection remains a significant challenge for epilepsy care. A clinical deep brain stimulation (DBS) system provides constrained ambulatory brain recordings; however, limited data exist on the use of DBS recordings for seizure detection and lateralization. We present the case of an 18-year-old patient with drug-resistant focal epilepsy, who had seizure detection and lateralization by DBS recordings. Prior stereotactic-EEG, including a thalamus lead, identified independent left orbitofrontal and mesial temporal onset seizures. Notably, low-frequency thalamic ictal power was significantly elevated relative to baseline awake and sleep states. The patient was subsequently implanted with an anterior nucleus of the thalamus DBS system. Postimplantation, low-frequency power-in-band (5.3-10.3 Hz) recordings were initiated. Nursing staff identified four typical clinical seizures during the inpatient DBS recording period. Thalamic DBS trends contained relative peaks that were coincident with each nurse-reported seizure. Peri-ictal power was uniformly maximal ipsilateral to the seizure network. This case demonstrates the feasibility of seizure detection and lateralization by a thalamic DBS system for some individuals, and suggests DBS sensing parameter selection may be guided by thalamic stereotactic EEG. Further research is necessary to assess the generalizability of DBS seizure detection across individuals and diverse seizure networks.

Multinuclear thalamic targeting with human stereotactic electroencephalography: surgical technique and nuances.

The authors recently demonstrated the utility of a novel multinuclear thalamic stereotactic electroencephalography (sEEG) approach to identify personalized seizure propagation networks through the human thalamus. In this study, they detail their strategy to efficiently sample the thalamus. The authors previously showed that a multilead orthogonal transsylvian approach allows lateral-medial sampling of bilateral anterior nuclei of the thalamus (ANTs), mediodorsal (MD) nuclei, and pulvinar (PLV) nuclei, with simultaneous capture of the opercular and insular regions. They also described a novel trans-massa intermedia trajectory to sample bilateral MD nuclei with a single electrode. For a second approach to multinuclear thalamic sampling, they designed a novel long-axis trajectory for posterior-to-anterior sampling of the lateral PLV nucleus, lateral MD nucleus, and ANT with a single electrode. Superficially, this trajectory samples from the posterior inferior temporal gyrus and then the posterior hippocampus, known as seizure network nodes. Concurrent with this long-axis trajectory, the centromedian nucleus can also be targeted with the orthogonal approach, minimizing the number of electrodes required to sample all 8 of the most relevant nuclei (4 on each side). The multinuclear thalamic sampling approaches resulted in no complications in a series of 34 patients. This study provides a strategy and specific implementation details for these approaches to identify the thalamic seizure networks that are increasingly important in the surgical treatment of epilepsy.

Local and Remote Chemogenetic Suppression of Hippocampal Seizures in Rats.

Innovative treatments of refractory epilepsy are widely desired, for which chemogenetic technology can provide region- and cell-type-specific modulation with relative noninvasiveness. We aimed to explore the specific applications of chemogenetics for locally and remotely networks controlling hippocampal seizures. A virus coding for a modified human Gi-coupled M4 muscarinic receptor (hM4Di) on pyramidal cells was injected into either the right hippocampal CA3 or the bilateral anterior nucleus of the thalamus (ANT) in rats. After one month, seizures were induced by 4-aminopyridine (4-AP) injection into the right CA3. Simultaneously, clozapine-N-oxide (CNO) (2.5 mg/kg) or clozapine (0.1 mg/kg), the specific ligands acting on hM4Di, were injected intraperitoneally. We also set up hM4Di control and clozapine control groups to eliminate the influence of viral transfection and the ligand alone on the experimental results. For both local and remote controls, the mean seizure duration was significantly reduced upon ligand application in the experimental groups. Seizure frequency, on the other hand, only showed a significant decrease in local control, with a lower frequency in the clozapine group than in the CNO group. Both the effects of CNO and clozapine were time-dependent, and clozapine was faster than CNO in local seizure control. This study shows the potency of chemogenetics to attenuate hippocampal seizures locally or remotely by activating the transfected hM4Di receptor with CNO or clozapine. ANT is suggested as a potentially safe chemogenetic application target in the epileptic network for focal hippocampal seizures.

Ictal and interictal epileptic networks of 34 patients with Hypothalamic Hamartoma on scalp electroencephalography.

To investigate ictal and interictal cortical involvement in epilepsy associated with hypothalamic hamartoma. We conducted a retrospective study of 34 patients with epilepsy and hypothalamic hamartoma, using data from long-term video-EEG-monitoring. We analyzed onset and propagation of ictal and interictal scalp EEG and visualized the resulting networks of cortical involvement. According to clinical and EEG criteria we grouped patients in: (1) focal disease, (2) focal advanced disease, (3) extended disease. We compared networks between these groups and different seizure types. Eight patients underwent several video-EEGs, and we analyzed all to investigate epilepsy progression. Epileptic activity mainly involved frontal and temporal cortex regions. Involvement of frontal regions was more common in advanced stages of the disease, and strong fronto-temporal connections were observed in the ictal networks of patients in intermediate stages (25.0% (left) and 35.7% (right) of seizures with EEG correlate). Occurrence and timing of EEG-correlate significantly depended on the seizure type (Chi-2-test, p<<0.001). In patients with several EEGs, seizure activity increased by +0.67 seizures/day/month (mean). There were significant differences between patients with normal and impaired cognitive function, with the latter showing pronounced ictal involvement of fronto-temporal cortex areas (p<0.001). Overall, in epilepsy due to hypothalamic hamartoma, cortical involvement focuses on frontal and temporal regions and varies systematically with the stage of the disease, different seizure types and presence of impaired cognitive function. We propose that these data may help improve our general understanding of epileptogenesis and potentially provide insights for the surgical therapy of hypothalamic hamartomas.

Seizure freedom using a regional approach to responsive neurostimulation for multifocal drug-resistant epilepsy: illustrative case.

Responsive neurostimulation (RNS) has emerged as an effective neuromodulatory intervention for patients with medically refractory epilepsy who are not candidates for resective or ablative surgery. However, in patients with multifocal seizures arising from a widely distributed network, optimizing lead placement can be challenging. Here, the authors present the case of a patient with drug-resistant multifocal, nonlateralizing seizures and multiple developmental brain lesions who underwent phase II monitoring with stereoelectroencephalography electrodes targeting the lesion and surrounding cortex as well as the centromedian thalamus. Neurophysiological signals observed during recorded events implicated a seizure network within the left perisylvian polymicrogyria, involving the left parietal operculum, insula, and centromedian thalamic regions rather than a single focus. Using a regional RNS approach to modulate this network, the patient improved from 5 seizures a day to freedom from disabling seizures shortly after lead implantation despite low stimulation parameters. This has implications for understanding the timescale of adaptive mechanisms that occur in response to stimulation and supports the use of RNS as a surgical treatment for drug-resistant epilepsy. https://thejns.org/doi/10.3171/CASE24369.

Pre- and post-therapy functional MRI connectivity in severe acute brain injury with suppression of consciousness: a comparative analysis to epilepsy features.

Severe acute brain injury (SABI) with suppressed consciousness is a major societal burden, with early prognosis being crucial for life-and-death treatment decisions. Resting-state functional MRI (rs-fMRI) is promising for prognosis and identifying epileptogenic activity in SABI. While established for SABI prognosis and seizure networks (SzNET) identification in epilepsy, the rs-fMRI use for SzNET detection in SABI is limited. This study compared evolution of SzNET and resting-state networks (RSN) pre-to-post treatment in SABI and epilepsy, hypothesizing that changes would align with clinical evolution. Therapies included epilepsy surgery for the epilepsy group and antiseizure medication for the SABI group. Independent component analysis (ICA) was used to identify SzNET and RSNs in all rs-fMRI. High-frequency BOLD (HF-BOLD), an ICA power spectrum-based index, quantified RSN and SzNET changes by the patient. Confidence intervals measured HF-BOLD changes pre-to-post-therapy. Baseline HF-BOLD and HF-BOLD changes were compared using linear-mixed models and interaction tests. Five SABI and ten epilepsy patients were included. SzNET were identified in all SABI's pre-therapy rs-fMRI. The clinical changes in SABI and epilepsy were consistent with rs-fMRI findings across groups. HF-BOLD reduced in the epilepsy group RSN post-therapy (-0.78, 95% CI -3.42 to -0.33), but the evidence was insufficient to determine an HF-BOLD reduction in SABI patients or SzNET. The HF-BOLD change trend in pre-to-post epilepsy surgery scans paralleled the clinical improvement, suggesting that the power spectrum may quantify the degree of abnormality on ICA-derived networks. Despite limitations such as small sample sizes, this exploratory study provides valuable insights into network dysfunction in SABI and epilepsy.

Modeling seizure networks in neuron-glia cultures using microelectrode arrays.

Epilepsy is a common neurological disorder, affecting over 65 million people worldwide. Unfortunately, despite resective surgery, over 30 of patients with drug-resistant epilepsy continue to experience seizures. Retrospective studies considering connectivity using intracranial electrocorticography (ECoG) obtained during neuromonitoring have shown that treatment failure is likely driven by failure to consider critical components of the seizure network, an idea first formally introduced in 2002. However, current studies only capture snapshots in time, precluding the ability to consider seizure network development. Over the past few years, multiwell microelectrode arrays have been increasingly used to study neuronal networks in vitro. As such, we sought to develop a novel in vitro MEA seizure model to allow for study of seizure networks. Specifically, we used 4-aminopyridine (4-AP) to capture hyperexcitable activity, and then show increased network changes after 2days of chronic treatment. We characterize network changes using functional connectivity measures and a novel technique using dimensionality reduction. We find that 4-AP successfully captures persistently elevated mean firing rate and significant changes in underlying connectivity patterns. We believe this affords a robust in vitro seizure model from which longitudinal network changes can be studied, laying groundwork for future studies exploring seizure network development.

Two different seizure networks on the scalp EEG present as ictal eye movements with epileptic nystagmus in a patient with cerebral hyperperfusion syndrome

Two different seizure networks on the scalp EEG present as ictal eye movements with epileptic nystagmus in a patient with cerebral hyperperfusion syndrome

Therapeutic approaches targeting seizure networks.

Epilepsy is one of the most common neurological disorders, affecting over 65 million people worldwide. Despite medical management with anti-seizure medications (ASMs), many patients fail to achieve seizure freedom, with over one-third of patients having drug-resistant epilepsy (DRE). Even with surgical management through resective surgery and/or neuromodulatory interventions, over 50 of patients continue to experience refractory seizures within a year of surgery. Over the past 2decades, studies have increasingly suggested that treatment failure is likely driven by untreated components of a pathological seizure network, a shift in the classical understanding of epilepsy as a focal disorder. However, this shift in thinking has yet to translate to improved treatments and seizure outcomes in patients. Here, we present a narrative review discussing the process of surgical epilepsy management. We explore current surgical interventions and hypothesized mechanisms behind treatment failure, highlighting evidence of pathologic seizure networks. Finally, we conclude by discussing how the network theory may inform surgical management, guiding the identification and targeting of more appropriate surgical regions. Ultimately, we believe that adapting current surgical practices and neuromodulatory interventions towards targeting seizure networks offers new therapeutic strategies that may improve seizure outcomes in patients suffering from DRE.

Network signatures define consciousness state during focal seizures.

Epilepsy is a common neurological disorder affecting 1% of the global population. Loss of consciousness in focal impaired awareness seizures (FIASs) and focal-to-bilateral tonic-clonic seizures (FBTCSs) can be devastating, but the mechanisms are not well understood. Although ictal activity and interictal connectivity changes have been noted, the network states of focal aware seizures (FASs), FIASs, and FBTCSs have not been thoroughly evaluated with network measures ictally. We obtained electrographic data from 74 patients with stereoelectroencephalography (SEEG). Sliding window band power, functional connectivity, and segregation were computed on preictal, ictal, and postictal data. Five-minute epochs of wake, rapid eye movement sleep, and deep sleep were also extracted. Connectivity of subcortical arousal structures was analyzed in a cohort of patients with both SEEG and functional magnetic resonance imaging (fMRI). Given that custom neuromodulation of seizures is predicated on detection of seizure type, a convolutional neural network was used to classify seizure types. We found that in the frontoparietal association cortex, an area associated with consciousness, both consciousness-impairing seizures (FIASs and FBTCSs) and deep sleep had increases in slow wave delta (1-4 Hz) band power. However, when network measures were employed, we found that only FIASs and deep sleep exhibited an increase in delta segregation and a decrease in gamma segregation. Furthermore, we found that only patients with FIASs had reduced subcortical-to-neocortical functional connectivity with fMRI versus controls. Finally, our deep learning network demonstrated an area under the curve of .75 for detecting consciousness-impairing seizures. This study provides novel insights into ictal network measures in FASs, FIASs, and FBTCSs. Importantly, although both FIASs and FBTCSs result in loss of consciousness, our results suggest that ictal network changes in FIASs uniquely resemble those that occur during deep sleep. Our results may inform novel neuromodulation strategies for preservation of consciousness in epilepsy.

Connectivity of the Piriform Cortex and its Implications in Temporal Lobe Epilepsy.

The piriform cortex has been implicated in the initiation, spread and termination of epileptic seizures. This understanding has extended to surgical management of epilepsy, where it has been shown that resection or ablation of the piriform cortex can result in better outcomes. How and why the piriform cortex may play such a crucial role in seizure networks is not well understood. To answer these questions, we investigated the functional and structural connectivity of the piriform cortex in both healthy controls and temporal lobe epilepsy (TLE) patients. We studied a retrospective cohort of 55 drug-resistant unilateral TLE patients and 26 healthy controls who received structural and functional neuroimaging. Using seed-to-voxel connectivity we compared the normative whole-brain connectivity of the piriform to that of the hippocampus, a region commonly involved in epilepsy, to understand the differential contribution of the piriform to the epileptogenic network. We subsequently measured the inter-piriform coupling (IPC) to quantify similarities in the inter-hemispheric cortical functional connectivity profile between the two piriform cortices. We related differences in IPC in TLE back to aberrations in normative piriform connectivity, whole brain functional properties, and structural connectivity. We find that relative to the hippocampus, the piriform is functionally connected to the anterior insula and the rest of the salience ventral attention network (SAN). We also find that low IPC is a sensitive metric of poor surgical outcome (sensitivity: 85.71%, 95% CI: [19.12%, 99.64%]); and differences in IPC within TLE were related to disconnectivity and hyperconnectivity to the anterior insula and the SAN. More globally, we find that low IPC is associated with whole-brain functional and structural segregation, marked by decreased functional small-worldness and fractional anisotropy. Our study presents novel insights into the functional and structural neural network alterations associated with this structure, laying the foundation for future work to carefully consider its connectivity during the presurgical management of epilepsy.

The interictal suppression hypothesis is the dominant differentiator of seizure onset zones in focal epilepsy.

Successful surgical treatment of drug-resistant epilepsy traditionally relies on the identification of seizure onset zones (SOZs). Connectome-based analyses of electrographic data from stereo electroencephalography (SEEG) may empower improved detection of SOZs. Specifically, connectome-based analyses based on the interictal suppression hypothesis posit that when the patient is not having a seizure, SOZs are inhibited by non-SOZs through high inward connectivity and low outward connectivity. However, it is not clear whether there are other motifs that can better identify potential SOZs. Thus, we sought to use unsupervised machine learning to identify network motifs that elucidate SOZs and investigate if there is another motif that outperforms the ISH. Resting-state SEEG data from 81 patients with drug-resistant epilepsy undergoing a pre-surgical evaluation at Vanderbilt University Medical Center were collected. Directed connectivity matrices were computed using the alpha band (8-13 Hz). Principal component analysis (PCA) was performed on each patient's connectivity matrix. Each patient's components were analysed qualitatively to identify common patterns across patients. A quantitative definition was then used to identify the component that most closely matched the observed pattern in each patient. A motif characteristic of the interictal suppression hypothesis (high-inward and low-outward connectivity) was present in all individuals and found to be the most robust motif for identification of SOZs in 64/81 (79%) patients. This principal component demonstrated significant differences in SOZs compared to non-SOZs. While other motifs for identifying SOZs were present in other patients, they differed for each patient, suggesting that seizure networks are patient specific, but the ISH is present in nearly all networks. We discovered that a potentially suppressive motif based on the interictal suppression hypothesis was present in all patients, and it was the most robust motif for SOZs in 79% of patients. Each patient had additional motifs that further characterized SOZs, but these motifs were not common across all patients. This work has the potential to augment clinical identification of SOZs to improve epilepsy treatment.

Combined neuromodulation and resection for functional cortex epilepsy: a case series.

Medically refractory epilepsy (MRE) often requires resection of the seizure onset zone (SOZ) for effective treatment. However, when the SOZ is in functional cortex (FC), achieving complete and safe resection becomes difficult, due to the seizure network overlap with function. The authors aimed to assess the safety and outcomes of a combined approach involving partial resection combined with focal neuromodulation for FC refractory epilepsy. The authors performed a retrospective analysis of individuals diagnosed with MRE who underwent surgical intervention from January 2015 to December 2022. Patients whose SOZ was located in FC and were treated with resection combined with simultaneous implantation of a focal neuromodulation device (responsive neurostimulation [RNS] device) with more than 12 months of follow-up data were included. All patients underwent a standard epilepsy preoperative assessment including intracranial electroencephalography and extraoperative stimulation mapping. Resections were performed under general anesthesia, followed by the concurrent implantation of an RNS device. Seven patients (4 males, median age 32.3 years, all right-handed) were included. The median interval from seizure onset to surgery was 17.4 years. The epileptogenic network included sensorimotor areas (cases 2, 3, and 6), visual cortex (case 1), language areas (cases 4 and 7), and the insula (case 5). The median follow-up was 3 years (range 1-5.8 years). No significant changes in neuropsychological tests were reported. One permanent nondisabling planned neurological deficit (left inferior quadrantanopia) was observed. Six patients had stimulation activated at a median of 4.7 months after resection. All patients achieved good seizure outcomes (5 with Engel class I and 2 with Engel class II outcomes). Maximal safe resection combined with focal neuromodulation presents a promising alternative to stand-alone resections for MRE epileptogenic zones overlapping with functional brain. This combined approach prioritizes the preservation of function while improving seizure outcomes.

Brain lesions causing parkinsonism versus seizures map to opposite brain networks.

Recent epidemiological studies propose an association between parkinsonism and seizures, but the direction of this association is unclear. Focal brain lesions causing new-onset parkinsonism versus seizures may provide a unique perspective on the causal relationship between the two symptoms and involved brain networks. We studied lesions causing parkinsonism versus lesions causing seizures and used the human connectome to identify their connected brain networks. Brain networks for parkinsonism and seizures were compared using spatial correlations on a group and individual lesion level. Lesions not associated with either symptom were used as controls. Lesion locations from 29 patients with parkinsonism were connected to a brain network with the opposite spatial topography (spatial r = -0.85) compared to 347 patients with lesions causing seizures. A similar inverse relationship was found when comparing the connections that were most specific on a group level (spatial r = -0.51) and on an individual lesion level (average spatial r = -0.042; P < 0.001). The substantia nigra was found to be most positively correlated to the parkinsonism network but most negatively correlated to the seizure network (spatial r > 0.8). Brain lesions causing parkinsonism versus seizures map to opposite brain networks, providing neuroanatomical insight into conflicting epidemiological evidence.

483 Network Analysis of the Thalamic RNS in Patients With Drug Resistant Epilepsy: Insights to Improve Surgical Targeting

INTRODUCTION: Approximately 30% of epilepsy patients are refractory to pharmacotherapy. Patients with drug-resistant epilepsy (DRE) with seizure foci located bilaterally or in the eloquent cortex may be ineligible for resective surgery. For such cases, responsive neurostimulation (RNS) is a viable treatment strategy. METHODS: Retrospective analysis of 23 patients treated with thalamic RNS of the centromedian (CM) and anterior nuclei of the thalamus (ANT) from 2015-2022. Clinical features and seizure outcomes were recorded. RNS electrodes were used to model the electrical field using the parameters at last follow up. Patient-specific probabilistic tractography was used to define the network of the seizure onset zone (SOZ) and its thalamic involvement. Each patient’s probabilistic map was used to define the area of highest connectivity of the thalamus with the seizure network. Each of these patient-specific thalamic areas demonstrating highest connectivity with the seizure network were correlated with electrode position, stimulation modeling, and seizure outcomes. RESULTS: Seizure network from neocortical areas were highly connected to the CM and from limbic cortical areas to the ANT, MD, and parafascicularis nuclei. Results of the correlation analysis between connectivity, stimulation modelling of the RNS electrode, and seizure outcomes will be presented along with illustrative cases of patient-specific targeting using tractography for RNS placement. CONCLUSIONS: Probabilistic tractography is useful to define the networks associated with improved seizure control in thalamic RNS. The identification of these networks prior to surgery could help to identify specific corticothalamic connections and their anatomical trajectories to optimize the implantation of the leads for better and more predictable seizure control.

Novel Surgical Approaches in Childhood Epilepsy: Laser, Brain Stimulation, and Focused Ultrasound.

Pediatric epilepsy has a worldwide prevalence of approximately 1% (Berg et al., Handb Clin Neurol 111:391-398, 2013) and is associated with not only lower quality of life but also long-term deficits in executive function, significant psychosocial stressors, poor cognitive outcomes, and developmental delays (Schraegle and Titus, Epilepsy Behav 62:20-26, 2016; Puka and Smith, Epilepsia 56:873-881, 2015). With approximately one-third of patients resistant to medical control, surgical intervention can offer a cure or palliation to decrease the disease burden and improve neurological development. Despite its potential, epilepsy surgery is drastically underutilized. Even today only 1% of the millions of epilepsy patients are referred annually for neurosurgical evaluation, and the average delay between diagnosis of Drug Resistant Epilepsy (DRE) and surgical intervention is approximately 20years in adults and 5years in children (Solli et al., Epilepsia 61:1352-1364, 2020). It is still estimated that only one-third of surgical candidates undergo operative intervention (Pestana Knight et al., Epilepsia 56:375, 2015). In contrast to the stable to declining rates of adult epilepsy surgery (Englot et al., Neurology 78:1200-1206, 2012; Neligan et al., Epilepsia 54:e62-e65, 2013), rates of pediatric surgery are rising (Pestana Knight et al., Epilepsia 56:375, 2015). Innovations in surgical approaches to epilepsy not only minimize potential complications but also expand the definition of a surgical candidate. In this chapter, three alternatives to classical resection are presented. First, laser ablation provides a minimally invasive approach to focal lesions. Next, both central and peripheral nervous system stimulation can interrupt seizure networks without creating permanent lesions. Lastly, focused ultrasound is discussed as a potential new avenue not only for ablation but also modulation of small, deep foci within seizure networks. A better understanding of the potential surgical options can guide patients and providers to explore all treatment avenues.

Seizure Pathways Changes at the Subject-Specific Level via Dynamic Step Effective Network Analysis.

The variability in the propagation pathway in epilepsy is a main factor contributing to surgical treatment failure. Ways to accurately capture the brain propagation network and quantitatively assess its evolution remain poorly described. This work aims to develop a dynamic step effective network (dSTE) to obtain the propagation path network of multiple seizures in the same patient and explore the degree of dissimilarity. Multichannel stereo-electroencephalography (sEEG) signals were acquired with ictal processes involving continuous changes in information propagation. We utilized high-order dynamic brain networks to obtain propagation networks through different levels of linking steps. We proposed a dissimilarity index based on singular value decomposition to quantitatively compare seizure pathways. Simulated data were generated through The Virtual Brain, and the reliability of this method was verified through ablation experiments. By applying the proposed method to two datasets consisting of 29 patients total, the evolution processes of each patient's seizure networks was obtained, and the within-patient dissimilarities were quantitatively compared. Finally, three types of brain network connectivity patterns were found. Type I patients have a good prognosis, while type III patients are prone to postoperative recurrence. This method captures the evolution of seizure propagation networks and assesses their dissimilarity more reliably than existing methods, demonstrating good robustness for studying the propagation path differences for multiple seizures in epilepsy patients. The three different patterns will be important considerations when planning epilepsy surgery under sEEG guidance.

SEEG-based epileptic seizure network modeling and analysis for pre-surgery evaluation

Stereo-electroencephalography is a minimally invasive technique for patients with refractory epilepsy pursuing surgery to reduce or control seizures. Electrodes are implanted based on pre-surgery evaluations and can collect deep brain activities for surgery decisions. This paper presents a methodology to analyze stereo-electroencephalography and assist clinicians by recommending the optimal surgical option and target areas for focal epilepsy patients. A seizure network (graph) model is proposed to characterize the spatial distribution and temporal changes of ictal events. The network nodes and edges correspond to specific epileptogenic regions and propagation/impact pathways (weighted by directed transfer function), respectively. We then employ a K-means clustering strategy to group nodes into a few clusters, from which the target surgical areas can be identified. Ten patients with different types of focal seizures were thoroughly analyzed. Promising consistency between results of our method’s recommendations, clinical decisions and surgery outcomes were observed.

Novel perturbation mechanism underlying the network fragility evolution

Studies have shown that fragility is an effective marker for seizures and seizure onset zone (SOZ). Through analysis and simulation of a probabilistic neural network under different inputs, the regularization mechanism of external input perturbations on the fragility is explored. It is theoretically found that the fragility of a perturbed node within seizure network is inversely associated with the received perturbation input, while the fragility of the other unperturbed nodes always oppositely changes with this perturbed node. By terming the node with high fragility as the fragile node (FN), it is interestingly shown that the FN would evolve to the node with the smallest input. Then, the network fragility is further investigated. Results show that the non-uniform perturbation inputs can more easily impact the network fragility. In addition, noise-induced variations of network connection can degrade the network fragility to some extent. Finally, the real data from a patient with epilepsy have verified the universality of the above obtained findings. These results may provide possible insights into stimulation strategies for seizure control in clinic.

High-rate leading spikes in propagating spike sequences predict seizure outcome in surgical patients with temporal lobe epilepsy.

Inter-ictal spikes aid in the diagnosis of epilepsy and in planning surgery of medication-resistant epilepsy. However, the localizing information from spikes can be unreliable because spikes can propagate, and the burden of spikes, often assessed as a rate, does not always correlate with the seizure onset zone or seizure outcome. Recent work indicates identifying where spikes regularly emerge and spread could localize the seizure network. Thus, the current study sought to better understand where and how rates of single and coupled spikes, and especially brain regions with high-rate and leading spike of a propagating sequence, informs the extent of the seizure network. In 37 patients with medication-resistant temporal lobe seizures, who had surgery to treat their seizure disorder, an algorithm detected spikes in the pre-surgical depth inter-ictal EEG. A separate algorithm detected spike propagation sequences and identified the location of leading and downstream spikes in each sequence. We analysed the rate and power of single spikes on each electrode and coupled spikes between pairs of electrodes, and the proportion of sites with high-rate, leading spikes in relation to the seizure onset zone of patients seizure free (n = 19) and those with continuing seizures (n = 18). We found increased rates of single spikes in mesial temporal seizure onset zone (ANOVA, P < 0.001, η2 = 0.138), and increased rates of coupled spikes within, but not between, mesial-, lateral- and extra-temporal seizure onset zone of patients with continuing seizures (P < 0.001; η2 = 0.195, 0.113 and 0.102, respectively). In these same patients, there was a higher proportion of brain regions with high-rate leaders, and each sequence contained a greater number of spikes that propagated with a higher efficiency over a longer distance outside the seizure onset zone than patients seizure free (Wilcoxon, P = 0.0172). The proportion of high-rate leaders in and outside the seizure onset zone could predict seizure outcome with area under curve = 0.699, but not rates of single or coupled spikes (0.514 and 0.566). Rates of coupled spikes to a greater extent than single spikes localize the seizure onset zone and provide evidence for inter-ictal functional segregation, which could be an adaptation to avert seizures. Spike rates, however, have little value in predicting seizure outcome. High-rate spike sites leading propagation could represent sources of spikes that are important components of an efficient seizure network beyond the clinical seizure onset zone, and like the seizure onset zone these, too, need to be removed, disconnected or stimulated to increase the likelihood for seizure control.