Towards network-guided neuromodulation for epilepsy

Simultaneous EEG-fMRI Investigation of Rhythm-Dependent Thalamo-Cortical Circuits Alteration in Schizophrenia

Schizophrenia is accompanied by aberrant interactions of intrinsic brain networks. However, the modulatory effect of electroencephalography (EEG) rhythms on the functional connectivity (FC) in schizophrenia remains unclear. This study aims to provide new insight into network communication in schizophrenia by integrating FC and EEG rhythm information. After collecting simultaneous resting-state EEG-functional magnetic resonance imaging data, the effect of rhythm modulations on FC was explored using what we term "dynamic rhythm information." We also investigated the synergistic relationships among three networks under rhythm modulation conditions, where this relationship presents the coupling between two brain networks with other networks as the center by the rhythm modulation. This study found FC between the thalamus and cortical network regions was rhythm-specific. Further, the effects of the thalamus on the default mode network (DMN) and salience network (SN) were less similar under alpha rhythm modulation in schizophrenia patients than in controls ([Formula: see text]). However, the similarity between the effects of the central executive network (CEN) on the DMN and SN under gamma modulation was greater ([Formula: see text]), and the degree of coupling was negatively correlated with the duration of disease ([Formula: see text], [Formula: see text]). Moreover, schizophrenia patients exhibited less coupling with the thalamus as the center and greater coupling with the CEN as the center. These results indicate that modulations in dynamic rhythms might contribute to the disordered functional interactions seen in schizophrenia.

Thalamic stereoelectroencephalography for neuromodulation target selection: Proof of concept and review of literature of pulvinar direct electrical stimulation

In patients with drug-resistant epilepsy (DRE) who are not candidates for resective surgery, various thalamic nuclei, including the anterior, centromedian, and pulvinar nuclei, have been extensively investigated as targets for neuromodulation. However, the therapeutic effects of different targets for thalamic neuromodulation on various types of epilepsy are not well understood. Here, we present a 32-year-old patient with multifocal bilateral temporoparieto-occipital epilepsy and bilateral malformations of cortical development (MCDs) who underwent bilateral stereoelectroencephalographic (SEEG) recordings of the aforementioned three thalamic nuclei bilaterally. The change in the rate of interictal epileptiform discharges (IEDs) from baseline were compared in temporal, central, parietal, and occipital regions after direct electrical stimulation (DES) of each thalamic nucleus. A significant decrease in the rate of IEDs (33% from baseline) in the posterior quadrant regions was noted in the ipsilateral as well as contralateral hemisphere following DES of the pulvinar. A scoping review was also performed to better understand the current standpoint of pulvinar thalamic stimulation in the treatment of DRE. The therapeutic effect of neuromodulation can differ among thalamic nuclei targets and epileptogenic zones (EZs). In patients with multifocal EZs with extensive MCDs, personalized thalamic targeting could be achieved through DES with thalamic SEEG electrodes.

Utility of intracranial EEG networks depends on re-referencing and connectivity choice

Studies of intracranial EEG networks have been used to reveal seizure generators in patients with drug-resistant epilepsy. Intracranial EEG is implanted to capture the epileptic network, the collection of brain tissue that forms a substrate for seizures to start and spread. Interictal intracranial EEG measures brain activity at baseline, and networks computed during this state can reveal aberrant brain tissue without requiring seizure recordings. Intracranial EEG network analyses require choosing a reference and applying statistical measures of functional connectivity. Approaches to these technical choices vary widely across studies, and the impact of these technical choices on downstream analyses is poorly understood. Our objective was to examine the effects of different re-referencing and connectivity approaches on connectivity results and on the ability to lateralize the seizure onset zone in patients with drug-resistant epilepsy. We applied 48 pre-processing pipelines to a cohort of 125 patients with drug-resistant epilepsy recorded with interictal intracranial EEG across two epilepsy centres to generate intracranial EEG functional connectivity networks. Twenty-four functional connectivity measures across time and frequency domains were applied in combination with common average re-referencing or bipolar re-referencing. We applied an unsupervised clustering algorithm to identify groups of pre-processing pipelines. We subjected each pre-processing approach to three quality tests: (i) the introduction of spurious correlations; (ii) robustness to incomplete spatial sampling; and (iii) the ability to lateralize the clinician-defined seizure onset zone. Three groups of similar pre-processing pipelines emerged: common average re-referencing pipelines, bipolar re-referencing pipelines and relative entropy-based connectivity pipelines. Relative entropy and common average re-referencing networks were more robust to incomplete electrode sampling than bipolar re-referencing and other connectivity methods (Friedman test, Dunn-Šidák test P < 0.0001). Bipolar re-referencing reduced spurious correlations at non-adjacent channels better than common average re-referencing (Δ mean from machine ref = -0.36 versus -0.22) and worse in adjacent channels (Δ mean from machine ref = -0.14 versus -0.40). Relative entropy-based network measures lateralized the seizure onset hemisphere better than other measures in patients with temporal lobe epilepsy (Benjamini-Hochberg-corrected P < 0.05, Cohen's d: 0.60-0.76). Finally, we present an interface where users can rapidly evaluate intracranial EEG pre-processing choices to select the optimal pre-processing methods tailored to specific research questions. The choice of pre-processing methods affects downstream network analyses. Choosing a single method among highly correlated approaches can reduce redundancy in processing. Relative entropy outperforms other connectivity methods in multiple quality tests. We present a method and interface for researchers to optimize their pre-processing methods for deriving intracranial EEG brain networks.

Keap1/Nrf2 signaling pathway participating in the progression of epilepsy via regulation of oxidative stress and ferroptosis in neurons

OBJECTIVE

This study aims to analyze the relationship between the Kelch-like ECH-associated protein 1 (Keap1)/Nuclear factor-erythroid 2-related factor 2 (Nrf2) and Epilepsy (EP), as well as its mechanism of action.

METHODS

Thirty Wistar rats were divided into a control group (without treatment), a model group (EP modeling), and an inhibition group (EP modeling + intervention by Keap1/Nrf2 signaling pathway inhibitor ATRA) and subject to Morris water maze experiment. Then, the expression of Oxidative Stress (OS) markers, ferroptosis-associated proteins and Keap1/Nrf2 pathway in rat hippocampus was measured. In addition, rat hippocampal neuronal cell HT22 was purchased and treated accordingly based on the results of grouping, and cell proliferation and apoptosis in the three groups were determined.

RESULTS

Compared with rats in the model group, those in the inhibition group showed shorter escape latency and an increased number of platform crossings (p < 0.05). Significant OS and neuron ferroptosis, increased apoptosis rate, elevated Keap1 expression, and decreased Nrf2 expression were observed in the model group compared to the control group (p < 0.05). The inhibition group exhibited notably improved OS and ferroptosis, as well as enhanced neuronal viability (p < 0.05).

CONCLUSION

Inhibition of the Keap1/Nrf2 pathway can reverse the OS and neuron viability in EP rats.

Virtual brain twins: from basic neuroscience to clinical use

Virtual brain twins are personalized, generative and adaptive brain models based on data from an individual's brain for scientific and clinical use. After a description of the key elements of virtual brain twins, we present the standard model for personalized whole-brain network models. The personalization is accomplished using a subject's brain imaging data by three means: (1) assemble cortical and subcortical areas in the subject-specific brain space; (2) directly map connectivity into the brain models, which can be generalized to other parameters; and (3) estimate relevant parameters through model inversion, typically using probabilistic machine learning. We present the use of personalized whole-brain network models in healthy ageing and five clinical diseases: epilepsy, Alzheimer's disease, multiple sclerosis, Parkinson's disease and psychiatric disorders. Specifically, we introduce spatial masks for relevant parameters and demonstrate their use based on the physiological and pathophysiological hypotheses. Finally, we pinpoint the key challenges and future directions.

Adequate control of seizures in a case of lead migration and neuromodulation of the posterior Sylvian junction: A case report

Background

This report aims to describe the neuromodulation effect on seizure control in a patient with a left hippocampal migrated electrode to the Posterior Sylvian Junction (PSJ) during a follow-up of 17 years.

Case Description

We report a case of a female patient with drug-resistant epilepsy who initiated at seven years old and underwent a stereotactic frame-based insertion of a left hippocampal electrode for deep brain stimulation (DBS). Posterior migration of the electrode was identified at PSJ by postoperative magnetic resonance imaging one month after surgery. A consistent seizure reduction (Engel IC) was obtained with 2v-120 uS-145 Hz, contacts 0-3 negative, casing positive DBS parameters and maintained to this day. Patient data were collected from electronic medical records preceded by obtaining an informed consent for research and publication purposes. Stimulation parameter adjustments were confirmed with the digital records of the local device provider (Medtronic).

Results

PSJ is a connectivity confluence point of white matter pathways in the posterior quadrant of the hemispheres. White mater DBS could be considered for research as a potential complementary target for neuromodulation of refractory epilepsy.

Striatum- and Cerebellum-Modulated Epileptic Networks Varying Across States with and without Interictal Epileptic Discharges

Idiopathic generalized epilepsy (IGE) is characterized by cryptogenic etiology and the striatum and cerebellum are recognized as modulators of epileptic network. We collected simultaneous electroencephalogram and functional magnetic resonance imaging data from 145 patients with IGE, 34 of whom recorded interictal epileptic discharges (IEDs) during scanning. In states without IEDs, hierarchical connectivity was performed to search core cortical regions which might be potentially modulated by striatum and cerebellum. Node-node and edge-edge moderation models were constructed to depict direct and indirect moderation effects in states with and without IEDs. Patients showed increased hierarchical connectivity with sensorimotor cortices (SMC) and decreased connectivity with regions in the default mode network (DMN). In the state without IEDs, striatum, cerebellum, and thalamus were linked to weaken the interactions of regions in the salience network (SN) with DMN and SMC. In periods with IEDs, overall increased moderation effects on the interaction between regions in SN and DMN, and between regions in DMN and SMC were observed. The thalamus and striatum were implicated in weakening interactions between regions in SN and SMC. The striatum and cerebellum moderated the cortical interaction among DMN, SN, and SMC in alliance with the thalamus, contributing to the dysfunction in states with and without IEDs in IGE. The current work revealed state-specific modulation effects of striatum and cerebellum on thalamocortical circuits and uncovered the potential core cortical targets which might contribute to develop new clinical neuromodulation techniques.

The role of psychology and neuropsychology in pediatric epilepsy surgery evaluation

Epilepsy is one of the most common neurological problems affecting 470,000 children in the United States. While most youth will achieve seizure freedom using medication, up to a third will continue to have seizures and are therefore considered to have drug-resistant epilepsy (DRE). Children and adolescents with epilepsy are at higher risk of behavioral, cognitive, and emotional disorders. Youth with DRE are at even greater risk of behavioral and emotional problems impacting quality of life and may need to pursue surgical interventions, including resective surgery or device implantation. Due to advances in the evaluation of candidates and surgical options, epilepsy surgery is more effective and has become second-line treatment for youth with DRE. This paper highlights the importance of exploring, assessing, and treating psychological and neuropsychological factors throughout the three phases of the epilepsy surgery process and ways pediatricians can support youth and families.

Generalisability of epileptiform patterns across time and patients

The complexity of localising the epileptogenic zone (EZ) contributes to surgical resection failures in achieving seizure freedom. The distinct patterns of epileptiform activity during interictal and ictal phases, varying across patients, often lead to suboptimal localisation using electroencephalography (EEG) features. We posed two key questions: whether neural signals reflecting epileptogenicity generalise from interictal to ictal time windows within each patient, and whether epileptiform patterns generalise across patients. Utilising an intracranial EEG dataset from 55 patients, we extracted a large battery of simple to complex features from stereo-EEG (SEEG) and electrocorticographic (ECoG) neural signals during interictal and ictal windows. Our features (n = 34) quantified many aspects of the signals including statistical moments, complexities, frequency-domain and cross-channel network attributes. Decision tree classifiers were then trained and tested on distinct time windows and patients to evaluate the generalisability of epileptogenic patterns across time and patients, respectively. Evidence strongly supported generalisability from interictal to ictal time windows across patients, particularly in signal power and high-frequency network-based features. Consistent patterns of epileptogenicity were observed across time windows within most patients, and signal features of epileptogenic regions generalised across patients, with higher generalisability in the ictal window. Signal complexity features were particularly contributory in cross-patient generalisation across patients. These findings offer insights into generalisable features of epileptic neural activity across time and patients, with implications for future automated approaches to supplement other EZ localisation methods.

Personalized strategies of neurostimulation: from static biomarkers to dynamic closed-loop assessment of neural function

Despite considerable advancement of first choice treatment (pharmacological, physical therapy, etc.) over many decades, neurological disorders still represent a major portion of the worldwide disease burden. Particularly concerning, the trend is that this scenario will worsen given an ever expanding and aging population. The many different methods of brain stimulation (electrical, magnetic, etc.) are, on the other hand, one of the most promising alternatives to mitigate the suffering of patients and families when conventional treatment fall short of delivering efficacious treatment. With applications in virtually all neurological conditions, neurostimulation has seen considerable success in providing relief of symptoms. On the other hand, a large variability of therapeutic outcomes has also been observed, particularly in the usage of non-invasive brain stimulation (NIBS) modalities. Borrowing inspiration and concepts from its pharmacological counterpart and empowered by unprecedented neurotechnological advancement, the neurostimulation field has seen in recent years a widespread of methods aimed at the personalization of its parameters, based on biomarkers of the individuals being treated. The rationale is that, by taking into account important factors influencing the outcome, personalized stimulation can yield a much-improved therapy. Here, we review the literature to delineate the state-of-the-art of personalized stimulation, while also considering the important aspects of the type of informing parameter (anatomy, function, hybrid), invasiveness, and level of development (pre-clinical experimentation versus clinical trials). Moreover, by reviewing relevant literature on closed loop neuroengineering solutions in general and on activity dependent stimulation method in particular, we put forward the idea that improved personalization may be achieved when the method is able to track in real time brain dynamics and adjust its stimulation parameters accordingly. We conclude that such approaches have great potential of promoting the recovery of lost functions and enhance the quality of life for patients.

Thalamic stimulation induced changes in effective connectivity

Deep brain stimulation (DBS) is a viable treatment for a variety of neurological conditions, however, the mechanisms through which DBS modulates large-scale brain networks are unresolved. Clinical effects of DBS are observed over multiple timescales. In some conditions, such as Parkinson's disease and essential tremor, clinical improvement is observed within seconds. In many other conditions, such as epilepsy, central pain, dystonia, neuropsychiatric conditions or Tourette syndrome, the DBS related effects are believed to require neuroplasticity or reorganization and often take hours to months to observe. To optimize DBS parameters, it is therefore essential to develop electrophysiological biomarkers that characterize whether DBS settings are successfully engaging and modulating the network involved in the disease of interest. In this study, 10 individuals with drug resistant epilepsy undergoing intracranial stereotactic EEG including a thalamus electrode underwent a trial of repetitive thalamic stimulation. We evaluated thalamocortical effective connectivity using single pulse electrical stimulation, both at baseline and following a 145 Hz stimulation treatment trial. We found that when high frequency stimulation was delivered for >1.5 hours, the evoked potentials measured from remote regions were significantly reduced in amplitude and the degree of modulation was proportional to the strength of baseline connectivity. When stimulation was delivered for shorter time periods, results were more variable. These findings suggest that changes in effective connectivity in the network targeted with DBS accumulate over hours of DBS. Stimulation evoked potentials provide an electrophysiological biomarker that allows for efficient data-driven characterization of neuromodulation effects, which could enable new objective approaches for individualized DBS optimization.

Role of Functional neurosurgery in Improving Patient Outcomes in Epilepsy, Movement Disorders, and Chronic Pain

Functional neurosurgery encompasses surgical procedures geared towards treating movement disorders (such as Parkinson's disease and essential tremor), drug-resistant epilepsy, and various types of pain disorders. It is one of the most rapidly expanding fields within neurosurgery and utilizes both traditional open surgical methods such as open temporal lobectomy for epilepsy as well as neuromodulation-based treatments such as implanting brain or nerve stimulation devices. This review outlines the role functional neurosurgery plays in treatment of epilepsy, movement disorders, and pain, and how it is being implemented at the University of Missouri by the Department of Neurosurgery.

Current advances in rodent drug-resistant temporal lobe epilepsy models: Hints from laboratory studies

Anti-seizure drugs (ASDs) are the first choice for the treatment of epilepsy, but there is still one-third of patients with epilepsy (PWEs) who are resistant to two or more appropriately chosen ASDs, named drug-resistant epilepsy (DRE). Temporal lobe epilepsy (TLE), a common type of epilepsy usually associated with hippocampal sclerosis (HS), shares the highest proportion of drug resistance (approximately 70%). In view of the key role of the temporal lobe in memory, emotion, and other physiological functions, patients with drug-resistant temporal lobe epilepsy (DR-TLE) are often accompanied by serious complications, and surgical procedures also yield extra considerations. The exact mechanisms for the genesis of DR-TLE remain unillustrated, which makes it hard to manage patients with DR-TLE in clinical practice. Animal models of DR-TLE play an irreplaceable role in both understanding the mechanism and searching for new therapeutic strategies or drugs. In this review article, we systematically summarized different types of current DR-TLE models, and then recent advances in mechanism investigations obtained in these models were presented, especially with the development of advanced experimental techniques and tools. We are deeply encouraged that novel strategies show great therapeutic potential in those DR-TLE models. Based on the big steps reached from the bench, a new light has been shed on the precise management of DR-TLE.

Bioelectronic Medicine: a multidisciplinary roadmap from biophysics to precision therapies

Bioelectronic Medicine stands as an emerging field that rapidly evolves and offers distinctive clinical benefits, alongside unique challenges. It consists of the modulation of the nervous system by precise delivery of electrical current for the treatment of clinical conditions, such as post-stroke movement recovery or drug-resistant disorders. The unquestionable clinical impact of Bioelectronic Medicine is underscored by the successful translation to humans in the last decades, and the long list of preclinical studies. Given the emergency of accelerating the progress in new neuromodulation treatments (i.e., drug-resistant hypertension, autoimmune and degenerative diseases), collaboration between multiple fields is imperative. This work intends to foster multidisciplinary work and bring together different fields to provide the fundamental basis underlying Bioelectronic Medicine. In this review we will go from the biophysics of the cell membrane, which we consider the inner core of neuromodulation, to patient care. We will discuss the recently discovered mechanism of neurotransmission switching and how it will impact neuromodulation design, and we will provide an update on neuronal and glial basis in health and disease. The advances in biomedical technology have facilitated the collection of large amounts of data, thereby introducing new challenges in data analysis. We will discuss the current approaches and challenges in high throughput data analysis, encompassing big data, networks, artificial intelligence, and internet of things. Emphasis will be placed on understanding the electrochemical properties of neural interfaces, along with the integration of biocompatible and reliable materials and compliance with biomedical regulations for translational applications. Preclinical validation is foundational to the translational process, and we will discuss the critical aspects of such animal studies. Finally, we will focus on the patient point-of-care and challenges in neuromodulation as the ultimate goal of bioelectronic medicine. This review is a call to scientists from different fields to work together with a common endeavor: accelerate the decoding and modulation of the nervous system in a new era of therapeutic possibilities.

Localizing seizure onset zone by a cortico-cortical evoked potentials-based machine learning approach in focal epilepsy

OBJECTIVE

We aimed to develop a new approach for identifying the localization of the seizure onset zone (SOZ) based on corticocortical evoked potentials (CCEPs) and to compare the connectivity patterns in patients with different clinical phenotypes.

METHODS

Fifty patients who underwent stereoelectroencephalography and CCEP procedures were included. Logistic regression was used in the model, and six CCEP metrics were input as features: root mean square of the first peak (N1RMS) and second peak (N2RMS), peak latency, onset latency, width duration, and area.

RESULTS

The area under the curve (AUC) for localizing the SOZ ranged from 0.88 to 0.93. The N1RMS values in the hippocampus sclerosis (HS) group were greater than that of the focal cortical dysplasia (FCD) IIa group (p < 0.001), independent of the distance between the recorded and stimulated sites. The sensitivity of localization was higher in the seizure-free group than in the non-seizure-free group (p = 0.036).

CONCLUSIONS

This new method can be used to predict the SOZ localization in various focal epilepsy phenotypes.

SIGNIFICANCE

This study proposed a machine-learning approach for localizing the SOZ. Moreover, we examined how clinical phenotypes impact large-scale abnormality of the epileptogenic networks.

On-demand low-frequency stimulation for seizure control: efficacy and behavioural implications

Mesial temporal lobe epilepsy (MTLE), the most common form of focal epilepsy in adults, is often refractory to medication and associated with hippocampal sclerosis. Deep brain stimulation represents an alternative treatment option for drug-resistant patients who are ineligible for resective brain surgery. In clinical practice, closed-loop stimulation at high frequencies is applied to interrupt ongoing seizures, yet has (i) a high incidence of false detections; (ii) the drawback of delayed seizure-suppressive intervention; and (iii) limited success in sclerotic tissue. As an alternative, low-frequency stimulation (LFS) has been explored recently in patients with focal epilepsies. In preclinical epilepsy models, hippocampal LFS successfully prevented seizures when applied continuously. Since it would be advantageous to reduce the stimulation load, we developed a protocol for on-demand LFS. Given the importance of the hippocampus for navigation and memory, we investigated potential consequences of LFS on hippocampal function. To this end, we used the intrahippocampal kainate mouse model, which recapitulates the key features of MTLE, including spontaneous seizure activity and hippocampal sclerosis. Specifically, our online detection algorithm monitored epileptiform activity in hippocampal local field potential recordings and identified short epileptiform bursts preceding focal seizure clusters, triggering hippocampal LFS to stabilize the network state. To probe behavioural performance, we tested the acute influence of LFS on anxiety-like behaviour in the light-dark box test, spatial and non-spatial memory in the object location memory and novel object recognition test, as well as spatial navigation and long-term memory in the Barnes maze. On-demand LFS was almost as effective as continuous LFS in preventing focal seizure clusters but with a significantly lower stimulation load. When we compared the behavioural performance of chronically epileptic mice to healthy controls, we found that both groups were equally mobile, but epileptic mice displayed an increased anxiety level, altered spatial learning strategy and impaired memory performance. Most importantly, with the application of hippocampal LFS before behavioural training and test sessions, we could rule out deleterious effects on cognition and even show an alleviation of deficits in long-term memory recall in chronically epileptic mice. Taken together, our findings may provide a promising alternative to current therapies, overcoming some of their major limitations, and inspire further investigation of LFS for seizure control in focal epilepsy syndromes.

The time-evolving epileptic brain network: concepts, definitions, accomplishments, perspectives

Epilepsy is now considered a network disease that affects the brain across multiple levels of spatial and temporal scales. The paradigm shift from an epileptic focus-a discrete cortical area from which seizures originate-to a widespread epileptic network-spanning lobes and hemispheres-considerably advanced our understanding of epilepsy and continues to influence both research and clinical treatment of this multi-faceted high-impact neurological disorder. The epileptic network, however, is not static but evolves in time which requires novel approaches for an in-depth characterization. In this review, we discuss conceptual basics of network theory and critically examine state-of-the-art recording techniques and analysis tools used to assess and characterize a time-evolving human epileptic brain network. We give an account on current shortcomings and highlight potential developments towards an improved clinical management of epilepsy.

Neurostimulation for Generalized Epilepsy: Should Therapy be Syndrome-specific?

Current applications of neurostimulation for generalized epilepsy use a one-target-fits-all approach that is agnostic to the specific epilepsy syndrome and seizure type being treated. The authors describe similarities and differences between the 2 "archetypes" of generalized epilepsy-Lennox-Gastaut syndrome and Idiopathic Generalized Epilepsy-and review recent neuroimaging evidence for syndrome-specific brain networks underlying seizures. Implications for stimulation targeting and programming are discussed using 5 clinical questions: What epilepsy syndrome does the patient have? What brain networks are involved? What is the optimal stimulation target? What is the optimal stimulation paradigm? What is the plan for adjusting stimulation over time?

Deep Brain Stimulation for Children with Generalized Epilepsy

Intracranial neuromodulation is an evolving therapy for patients with drug-resistant epilepsy (DRE). Deep brain stimulation (DBS) is now available as a therapy for patients with DRE and focal-onset seizures in select health care systems; however, there remains a substantial need of efficacy data before DBS can be more widely adopted into routine clinical practice. This review and commentary focuses on a particular shifting paradigm: DBS as a therapy for children with generalized-onset seizures.

Imaging and Stereotactic Electroencephalography Functional Networks to Guide Epilepsy Surgery

Epilepsy surgery is a potentially curative treatment of drug-resistant epilepsy that has remained underutilized both due to inadequate referrals and incomplete localization hypotheses. The complexity of patients evaluated for epilepsy surgery has increased, thus new approaches are necessary to treat these patients. The paradigm of epilepsy surgery has evolved to match this challenge, now considering the entire seizure network with the goal of disrupting it through resection, ablation, neuromodulation, or a combination. The network paradigm has the potential to aid in identification of the seizure network as well as treatment selection.

Utility of Chronic Intracranial Electroencephalography in Responsive Neurostimulation Therapy

Responsive neurostimulation (RNS) therapy is an effective treatment for reducing seizures in some patients with focal epilepsy. Utilizing a chronically implanted device, RNS involves monitoring brain activity signals for user-defined patterns of seizure activity and delivering electrical stimulation in response. Devices store chronic data including counts of detected activity patterns and brief recordings of intracranial electroencephalography signals. Data platforms for reviewing stored chronic data retrospectively may be used to evaluate therapy performance and to fine-tune detection and stimulation settings. New frontiers in RNS research can leverage raw chronic data to reverse engineer neurostimulation mechanisms and improve therapy effectiveness.

Evolution of Stereo-Electroencephalography at Massachusetts General Hospital

The practice of invasive monitoring for presurgical epilepsy workup has evolved at Massachusetts General Hospital (MGH) in parallel to the evolution in the field's understanding of epilepsy as a network disorder. Implantations have shifted from an emphasis on singularly finding single foci for the purpose of resection to a network-hypothesis-driven approach aiming to delineate patients' seizure networks with the goal of developing surgical interventions that disrupt critical nodes of these networks. Here, the authors review all invasive monitoring cases at MGH from April 2016 through June 2023 to describe how this paradigm shift has taken form.

Epilepsy Networks and Their Surgical Relevance

Surgical epilepsy is a rapidly evolved field. As the understanding and concepts of epilepsy shift towards a network disorder, surgical outcomes may shed light on numerous components of these systems. This review documents the evolution of the understanding of epilepsy networks and examines the data generated by resective, ablative, neuromodulation, and invasive monitoring surgeries in epilepsy patients. As these network tools are better integrated into epilepsy practice, they may eventually inform surgical decisions and improve clinical outcomes.

Effect of intracranial electrical stimulation on dynamic functional connectivity in medically refractory epilepsy

Objective

The objective of this study was to explore the distributed network effects of intracranial electrical stimulation in patients with medically refractory epilepsy using dynamic functional connectivity (dFC) and graph indicators.

Methods

The time-varying connectivity patterns of dFC (state-based metrics) as well as topological properties of static functional connectivity (sFC) and dFC (graph indicators) were assessed before and after the intracranial electrical stimulation. The sliding window method and k-means clustering were used for the analysis of dFC states, which were characterized by connectivity strength, occupancy rate, dwell time, and transition. Graph indicators for sFC and dFC were obtained using group statistical tests.

Results

DFCs were clustered into two connectivity configurations: a strongly connected state (state 1) and a sparsely connected state (state 2). After electrical stimulation, the dwell time and occupancy rate of state 1 decreased, while that of state 2 increased. Connectivity strengths of both state 1 and state 2 decreased. For graph indicators, the clustering coefficient, k-core, global efficiency, and local efficiency of patients showed a significant decrease, but the brain networks of patients exhibited higher modularity after electrical stimulation. Especially, for state 1, there was a significant decrease in functional connectivity strength after stimulation within and between the frontal lobe and temporary lobe, both of which are associated with the seizure onset.

Conclusion

Our findings demonstrated that intracranial electrical stimulation significantly changed the time-varying connectivity patterns and graph indicators of the brain in patients with medically refractory epilepsy. Specifically, the electrical stimulation decreased functional connectivity strength in both local-level and global-level networks. This might provide a mechanism of understanding for the distributed network effects of intracranial electrical stimulation and extend the knowledge of the pathophysiological network of medically refractory epilepsy.

Chronic subthreshold cortical stimulation: A promising therapy for motor cortex seizures

Chronic subthreshold cortical stimulation (CSCS) is a form of neurostimulation consisting of continuous or cyclic, open-loop, subthreshold electrical stimulation of a well-defined epileptogenic zone (EZ). CSCS has seen limited clinical use but could be a safe and effective long-term treatment of focal drug resistant epilepsy, in particular when the EZ is located in the motor cortex. We present a case of a 49-year-old woman suffering from debilitating focal motor seizures. Treatment with CSCS resulted in significant clinical improvement, enabling her to walk unaided for the first time in years.

Connectome-based approaches in pediatric epilepsy surgery: "State-of-the art" and future perspectives

Modern epilepsy science has overcome the traditional interpretation of a strict region-specific origin of epilepsy, highlighting the involvement of wider patterns of altered neuronal circuits. In selected cases, surgery may constitute a valuable option to achieve both seizure freedom and neurocognitive improvement. Although epilepsy is now considered as a brain network disease, the most relevant literature concerning the "connectome-based" epilepsy surgery mainly refers to adults, with a limited number of studies dedicated to the pediatric population. In this review, the Authors summarized the main current available knowledge on the relevance of WM surgical anatomy in epilepsy surgery, the post-surgical modifications of brain structural connectivity and the related clinical impact of such modifications within the pediatric context. In the last part, possible implications and future perspectives of this approach have been discussed, especially concerning the optimization of surgical strategies and the predictive value of the epilepsy network analysis for planning tailored approaches, with the final aim of improving case selection, presurgical planning, intraoperative management, and postoperative results.

Stimulation to probe, excite, and inhibit the epileptic brain

Direct cortical stimulation has been applied in epilepsy for nearly a century and has experienced a renaissance, given unprecedented opportunities to probe, excite, and inhibit the human brain. Evidence suggests stimulation can increase diagnostic and therapeutic utility in patients with drug-resistant epilepsies. However, choosing appropriate stimulation parameters is not a trivial issue, and is further complicated by epilepsy being characterized by complex brain state dynamics. In this article derived from discussions at the ICTALS 2022 Conference (International Conference on Technology and Analysis for Seizures), we succinctly review the literature on cortical stimulation applied acutely and chronically to the epileptic brain for localization, monitoring, and therapeutic purposes. In particular, we discuss how stimulation is used to probe brain excitability, discuss evidence on the usefulness of stimulation to trigger and stop seizures, review therapeutic applications of stimulation, and finally discuss how stimulation parameters are impacted by brain dynamics. Although research has advanced considerably over the past decade, there are still significant hurdles to optimizing use of this technique. For example, it remains unclear to what extent short timescale diagnostic biomarkers can predict long-term outcomes and to what extent these biomarkers add information to already existing biomarkers from passive electroencephalographic recordings. Further questions include the extent to which closed loop stimulation offers advantages over open loop stimulation, what the optimal closed loop timescales may be, and whether biomarker-informed stimulation can lead to seizure freedom. The ultimate goal of bioelectronic medicine remains not just to stop seizures but rather to cure epilepsy and its comorbidities.

Unearthing the mechanisms of responsive neurostimulation for epilepsy

Responsive neurostimulation (RNS) is an effective therapy for people with drug-resistant focal epilepsy. In clinical trials, RNS therapy results in a meaningful reduction in median seizure frequency, but the response is highly variable across individuals, with many receiving minimal or no benefit. Understanding why this variability occurs will help improve use of RNS therapy. Here we advocate for a reexamination of the assumptions made about how RNS reduces seizures. This is now possible due to large patient cohorts having used this device, some long-term. Two foundational assumptions have been that the device's intracranial leads should target the seizure focus/foci directly, and that stimulation should be triggered only in response to detected epileptiform activity. Recent studies have called into question both hypotheses. Here, we discuss these exciting new studies and suggest future approaches to patient selection, lead placement, and device programming that could improve clinical outcomes.

Revisiting the concept of drug-resistant epilepsy: A TASK1 report of the ILAE/AES Joint Translational Task Force

Despite progress in the development of anti-seizure medications (ASMs), one third of people with epilepsy have drug-resistant epilepsy (DRE). The working definition of DRE, proposed by the International League Against Epilepsy (ILAE) in 2010, helped identify individuals who might benefit from presurgical evaluation early on. As the incidence of DRE remains high, the TASK1 workgroup on DRE of the ILAE/American Epilepsy Society (AES) Joint Translational Task Force discussed the heterogeneity and complexity of its presentation and mechanisms, the confounders in drawing mechanistic insights when testing treatment responses, and barriers in modeling DRE across the lifespan and translating across species. We propose that it is necessary to revisit the current definition of DRE, in order to transform the preclinical and clinical research of mechanisms and biomarkers, to identify novel, effective, precise, pharmacologic treatments, allowing for earlier recognition of drug resistance and individualized therapies.

The evolution of antiseizure medication therapy selection in adults: Is artificial intelligence -assisted antiseizure medication selection ready for prime time?

Antiseizure medications (ASMs) are the mainstay of symptomatic epilepsy treatment. The primary goal of pharmacotherapy with ASMs in epilepsy is to achieve complete seizure remission while minimizing therapy-related adverse events. Over the years, more ASMs have been introduced, with approximately 30 now in everyday use. With such a wide variety, much guidance is needed in choosing ASMs for initial therapy, subsequent replacement monotherapy, or adjunctive therapy. The specific ASMs are typically tailored by the patient's related factors, including epilepsy syndrome, age, sex, comorbidities, and ASM characteristics, including the spectrum of efficacy, pharmacokinetic properties, safety, and tolerability. Weighing these key clinical variables requires experience and expertise that may be limited. Furthermore, with this approach, patients may endure multiple trials of ineffective treatments before the most appropriate ASM is found. A more reliable way to predict response to different ASMs is needed so that the most effective and tolerated ASM can be selected. Soon, alternative approaches, such as deep machine learning (ML), could aid the individualized selection of the first and subsequent ASMs. The recognition of epilepsy as a network disorder and the integration of personalized epilepsy networks in future ML platforms can also facilitate the prediction of ASM response. Augmenting the conventional approach with artificial intelligence (AI) opens the door to personalized pharmacotherapy in epilepsy. However, more work is needed before these models are ready for primetime clinical practice.

The Utility of Responsive Neurostimulation for the Treatment of Pediatric Drug-Resistant Epilepsy

Drug-resistant epilepsy (DRE) has a strongly negative impact on quality of life, as well as the development of pediatric patients. Surgical treatments have evolved over time, including more invasive craniotomies for resection or disconnection. More recently, neuromodulation techniques have been employed as a less invasive option for patients. Responsive neurostimulation (RNS) is the first closed-loop technology that allows for both treatment and device data collection, which allows for an internal assessment of the efficacy of treatment. This novel technology has been approved in adults and has been used off label in pediatrics. This review seeks to describe this technology, its history, and future directions.

Structural connections of the centromedian nucleus of thalamus and their relevance for neuromodulation in generalized drug-resistant epilepsy: insight from a tractography study

Background

Epilepsy is a widespread neurologic disorder and almost one-third of patients suffer from drug-resistant epilepsy (DRE). Neuromodulation targeting the centromediannucleus of the thalamus (CM) has been showing promising results for patients with generalized DRE who are not surgical candidates. Recently, the effect of CM- deep brain stimulation (DBS) in DRE patients was investigated in the Electrical Stimulation of Thalamus for Epilepsy of Lennox-Gastaut phenotype (ESTEL) trial, a monocentric randomized-controlled study. The same authors described a 'cold-spot' and a 'sweet-spot', which are defined as the volume of stimulation in the thalamus yielding the least and the best clinical response, respectively. However, it remains unclear which structural connections may contribute to the anti-seizure effect of the stimulation.

Objective

We investigated the differences in structural connectivity among CM, the sweet-spot and the cold-spot. Furthermore, we tried to validate our results in a cohort of DRE patients who underwent CM-DBS or CM-RNS (responsive neurostimulation). We hypothesized that the sweet-spot would share similar structural connectivity with responder patients.

Methods

By using the software FMRIB Software Library (FSL), probabilistic tractography was performed on 100 subjects from the Human Connectome Project to calculate the probability of connectivity of the whole CM, the sweet-spot and the cold-spot to 45 cortical and subcortical areas. Results among the three seeds were compared with multivariate analysis of variance (MANOVA). Similarly, the structural connectivity of volumes of tissue activated (VTAs) from eight DRE patients was investigated. Patients were divided into responders and non-responders based on the degree of reduction in seizure frequency, and the mean probabilities of connectivity were similarly compared between the two groups.

Results

The sweet-spot demonstrated a significantly higher probability of connectivity (p < 0.001) with the precentral gyrus, superior frontal gyrus, and the cerebellum than the whole CM and the cold-spot. Responder patients displayed a higher probability of connectivity with both ipsilateral (p = 0.011) and contralateral cerebellum (p = 0.04) than the non-responders.

Conclusion

Cerebellar connections seem to contribute to the beneficial effects of CM-neuromodulation in patients with drug-resistant generalized epilepsy.

A Comprehensive Review of Emerging Trends and Innovative Therapies in Epilepsy Management

Epilepsy is a complex neurological disorder affecting millions worldwide, with a substantial number of patients facing drug-resistant epilepsy. This comprehensive review explores innovative therapies for epilepsy management, focusing on their principles, clinical evidence, and potential applications. Traditional antiseizure medications (ASMs) form the cornerstone of epilepsy treatment, but their limitations necessitate alternative approaches. The review delves into cutting-edge therapies such as responsive neurostimulation (RNS), vagus nerve stimulation (VNS), and deep brain stimulation (DBS), highlighting their mechanisms of action and promising clinical outcomes. Additionally, the potential of gene therapies and optogenetics in epilepsy research is discussed, revealing groundbreaking findings that shed light on seizure mechanisms. Insights into cannabidiol (CBD) and the ketogenic diet as adjunctive therapies further broaden the spectrum of epilepsy management. Challenges in achieving seizure control with traditional therapies, including treatment resistance and individual variability, are addressed. The importance of staying updated with emerging trends in epilepsy management is emphasized, along with the hope for improved therapeutic options. Future research directions, such as combining therapies, AI applications, and non-invasive optogenetics, hold promise for personalized and effective epilepsy treatment. As the field advances, collaboration among researchers of natural and synthetic biochemistry, clinicians from different streams and various forms of medicine, and patients will drive progress toward better seizure control and a higher quality of life for individuals living with epilepsy.

A multicenter retrospective study of patients treated in the thalamus with responsive neurostimulation

Introduction

For drug resistant epilepsy patients who are either not candidates for resective surgery or have already failed resective surgery, neuromodulation is a promising option. Neuromodulatory approaches include responsive neurostimulation (RNS), deep brain stimulation (DBS), and vagal nerve stimulation (VNS). Thalamocortical circuits are involved in both generalized and focal onset seizures. This paper explores the use of RNS in the centromedian nucleus of the thalamus (CMN) and in the anterior thalamic nucleus (ANT) of patients with drug resistant epilepsy.

Methods

This is a retrospective multicenter study from seven different epilepsy centers in the United States. Patients that had unilateral or bilateral thalamic RNS leads implanted in the CMN or ANT for at least 6 months were included. Primary objectives were to describe the implant location and determine changes in the frequency of disabling seizures at 6 months, 1 year, 2 years, and > 2 years. Secondary objectives included documenting seizure free periods, anti-seizure medication regimen changes, stimulation side effects, and serious adverse events. In addition, the global clinical impression scale was completed.

Results

Twelve patients had at least one lead placed in the CMN, and 13 had at least one lead placed in the ANT. The median baseline seizure frequency was 15 per month. Overall, the median seizure reduction was 33% at 6 months, 55% at 1 year, 65% at 2 years, and 74% at >2 years. Seizure free intervals of at least 3 months occurred in nine patients. Most patients (60%, 15/25) did not have a change in anti-seizure medications post RNS placement. Two serious adverse events were recorded, one related to RNS implantation. Lastly, overall functioning seemed to improve with 88% showing improvement on the global clinical impression scale.

Discussion

Meaningful seizure reduction was observed in patients who suffer from drug resistant epilepsy with unilateral or bilateral RNS in either the ANT or CMN of the thalamus. Most patients remained on their pre-operative anti-seizure medication regimen. The device was well tolerated with few side effects. There were rare serious adverse events. Most patients showed an improvement in global clinical impression scores.

Extent of piriform cortex resection in children with temporal lobe epilepsy

OBJECTIVE

A greater extent of resection of the temporal portion of the piriform cortex (PC) has been shown to be associated with higher likelihood of seizure freedom in adults undergoing anterior temporal lobe resection (ATLR) for drug-resistant temporal lobe epilepsy (TLE). There have been no such studies in children, therefore this study aimed to investigate this association in a pediatric cohort.

METHODS

A retrospective, neuroimaging cohort study of children with TLE who underwent ATLR between 2012 and 2021 was undertaken. The PC, hippocampal and amygdala volumes were measured on the preoperative and postoperative T1-weighted MRI. Using these volumes, the extent of resection per region was compared between the seizure-free and not seizure-free groups.

RESULTS

In 50 children (median age 9.5 years) there was no significant difference between the extent of resection of the temporal PC in the seizure-free (median = 50%, n = 33/50) versus not seizure-free (median = 40%, n = 17/50) groups (p = 0.26). In a sub-group of 19 with ipsilateral hippocampal atrophy (quantitatively defined by ipsilateral-to-contralateral asymmetry), the median extent of temporal PC resection was greater in children who were seizure-free (53%) versus those not seizure-free (19%) (p = 0.009).

INTERPRETATION

This is the first study demonstrating that, in children with TLE and hippocampal atrophy, more extensive temporal PC resection is associated with a greater chance of seizure freedom-compatible with an adult series in which 85% of patients had hippocampal sclerosis. In a combined group of children with and without hippocampal atrophy, the extent of PC resection was not associated with seizure outcome, suggesting different epileptogenic networks within this cohort.

Focal to bilateral tonic-clonic seizures predict pharmacoresistance in focal cortical dysplasia-related epilepsy

OBJECTIVE

Focal cortical dysplasia (FCD) is the most common etiology of surgically-remediable epilepsy in children. Eighty-seven percent of patients with FCD develop epilepsy (75% is pharmacoresistant epilepsy [PRE]). Focal to bilateral tonic-clonic (FTBTC) seizures are associated with worse surgical outcomes. We hypothesized that children with FCD-related epilepsy with FTBTC seizures are more likely to develop PRE due to lesion interaction with restricted cortical neural networks.

METHODS

Patients were selected retrospectively from radiology and surgical databases from Children's National Hospital.

INCLUSION CRITERIA

3T magnetic resonance imaging (MRI)-confirmed FCD from January 2011 to January 2020; ages 0 days to 22 years at MRI; and 18 months of documented follow-up. FCD dominant network (Yeo 7-network parcellation) was determined. Association of FTBTC seizures with epilepsy severity, surgical outcome, and dominant network was tested. Binomial regression was used to evaluate predictors (FTBTC seizures, age at seizure onset, pathology, hemisphere, lobe) of pharmacoresistance and Engel outcome. Regression was used to evaluate predictors (age at seizure onset, pathology, lobe, percentage default mode network [DMN] overlap) of FTBTC seizures.

RESULTS

One hundred seventeen patients had a median age at seizure onset of 3.00 years (interquartile range [IQR] .42-5.59 years). Eighty-three patients had PRE (71%); 34 had pharmacosensitive epilepsy (PSE) (29%). Twenty patients (17%) had FTBTC seizures. Seventy-three patients underwent epilepsy surgery. Multivariate regression showed that FTBTC seizures are associated with an increased risk of PRE (odds ratio [OR] 6.41, 95% confidence interval [CI] 1.21-33.98, p = .02). FCD hemisphere/lobe was not associated with PRE. Percentage DMN overlap predicts FTBTC seizures. Seventy-two percent (n = 52) overall and 53% (n = 9) of patients with FTBTC seizures achieved Engel class I outcome.

SIGNIFICANCE

In a heterogeneous population of surgical and non-operated patients with FCD-related epilepsy, the presence of FTBTC seizures is associated with a tremendous risk of PRE. This finding is a recognizable marker to help neurologists identify those children with FCD-related epilepsy at high risk of PRE and can flag patients for earlier consideration of potentially curative surgery. The FCD-dominant network also contributes to FTBTC seizure clinical expression.

Multisite thalamic recordings to characterize seizure propagation in the human brain

Neuromodulation of the anterior nuclei of the thalamus (ANT) has shown to be efficacious in a subset of patients with refractory focal epilepsy. One important uncertainty is to what extent thalamic subregions other than the ANT could be recruited more prominently in the propagation of focal onset seizures. We designed the current study to simultaneously monitor the engagement of the ANT, mediodorsal (MD) and pulvinar (PUL) nuclei during seizures in patients who could be candidates for thalamic neuromodulation. We studied 11 patients with clinical manifestations of presumed temporal lobe epilepsy (TLE) undergoing invasive stereo-encephalography (sEEG) monitoring to confirm the source of their seizures. We extended cortical electrodes to reach the ANT, MD and PUL nuclei of the thalamus. More than one thalamic subdivision was simultaneously interrogated in nine patients. We recorded seizures with implanted electrodes across various regions of the brain and documented seizure onset zones (SOZ) in each recorded seizure. We visually identified the first thalamic subregion to be involved in seizure propagation. Additionally, in eight patients, we applied repeated single pulse electrical stimulation in each SOZ and recorded the time and prominence of evoked responses across the implanted thalamic regions. Our approach for multisite thalamic sampling was safe and caused no adverse events. Intracranial EEG recordings confirmed SOZ in medial temporal lobe, insula, orbitofrontal and temporal neocortical sites, highlighting the importance of invasive monitoring for accurate localization of SOZs. In all patients, seizures with the same propagation network and originating from the same SOZ involved the same thalamic subregion, with a stereotyped thalamic EEG signature. Qualitative visual reviews of ictal EEGs were largely consistent with the quantitative analysis of the corticothalamic evoked potentials, and both documented that thalamic nuclei other than ANT could have the earliest participation in seizure propagation. Specifically, pulvinar nuclei were involved earlier and more prominently than ANT in more than half of the patients. However, which specific thalamic subregion first demonstrated ictal activity could not be reliably predicted based on clinical semiology or lobar localization of SOZs. Our findings document the feasibility and safety of bilateral multisite sampling from the human thalamus. This may allow more personalized thalamic targets to be identified for neuromodulation. Future studies are needed to determine if a personalized thalamic neuromodulation leads to greater improvements in clinical outcome.

A review of visual sustained attention: neural mechanisms and computational models

Sustained attention is one of the basic abilities of humans to maintain concentration on relevant information while ignoring irrelevant information over extended periods. The purpose of the review is to provide insight into how to integrate neural mechanisms of sustained attention with computational models to facilitate research and application. Although many studies have assessed attention, the evaluation of humans' sustained attention is not sufficiently comprehensive. Hence, this study provides a current review on both neural mechanisms and computational models of visual sustained attention. We first review models, measurements, and neural mechanisms of sustained attention and propose plausible neural pathways for visual sustained attention. Next, we analyze and compare the different computational models of sustained attention that the previous reviews have not systematically summarized. We then provide computational models for automatically detecting vigilance states and evaluation of sustained attention. Finally, we outline possible future trends in the research field of sustained attention.

Adverse Event Profiles of Antiseizure Medications and the Impact of Coadministration on Drug Tolerability in Adults with Epilepsy

BACKGROUND

Antiseizure medication (ASM) as monotherapy or in combination is the treatment of choice for most patients with epilepsy. Therefore, knowledge about the typical adverse events (AEs) for ASMs and other coadministered drugs (CDs) is essential for practitioners and patients. Due to frequent polypharmacy, it is often difficult to clinically assess the AE profiles of ASMs and differentiate the influence of CDs.

OBJECTIVE

This retrospective analysis aimed to determine typical AE profiles for ASMs and assess the impact of CDs on AEs in clinical practice.

METHODS

The Liverpool AE Profile (LAEP) and its domains were used to identify the AE profiles of ASMs based on data from a large German multicenter study (Epi2020). Following established classifications, drugs were grouped according to their mode of action (ASMs) or clinical indication (CDs). Bivariate correlation, multivariate ordinal regression (MORA), and artificial neural network (ANNA) analyses were performed. Bivariate correlation with Fisher's z-transformation was used to compare the correlation strength of LAEP with the Hospital Anxiety and Depression Scale (HADS) and Neurological Disorders Depression Inventory for Epilepsy (NDDI-E) to avoid LAEP bias in the context of antidepressant therapy.

RESULTS

Data from 486 patients were analyzed. The AE profiles of ASM categories and single ASMs matched those reported in the literature. Synaptic vesicle glycoprotein 2A (SV2A) and voltage-gated sodium channel (VGSC) modulators had favorable AE profiles, while brivaracetam was superior to levetiracetam regarding psychobehavioral AEs. MORA revealed that, in addition to seizure frequency, α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid (AMPA) modulators and antidepressants were the only independent predictors of high LAEP values. After Fisher's z-transformation, correlations were significantly lower between LAEP and antidepressants than between LAEP and HADS or NDDI-E. Therefore, a bias in the results toward over interpreting the impact of antidepressants on LAEP was presumed. In the ANNA, perampanel, zonisamide, topiramate, and valproic acid were important nodes in the network, while VGSC and SV2A modulators had low relevance for predicting relevant AEs. Similarly, cardiovascular agents, analgesics, and antipsychotics were important CDs in the ANNA model.

CONCLUSION

ASMs have characteristic AE profiles that are highly reproducible and must be considered in therapeutic decision-making. Therapy using perampanel as an AMPA modulator should be considered cautiously due to its relatively high AE profile. Drugs acting via VGSCs and SV2A receptors are significantly better tolerated than other ASM categories or substances (e.g., topiramate, zonisamide, and valproate). Switching to brivaracetam is advisable in patients with psychobehavioral AEs who take levetiracetam. Because CDs frequently pharmacokinetically interact with ASMs, the cumulative AE profile must be considered.

TRIAL REGISTRATION

DRKS00022024, U1111-1252-5331.

Stop being so superficial: subcortical disconnection and long-term seizure outcomes

This scientific commentary refers to ‘Thalamostriatal disconnection underpins long-term seizure freedom in frontal lobe epilepsy surgery’ by Giampiccolo et al. (https://doi.org/10.1093/brain/awad085).

Thalamostriatal disconnection underpins long-term seizure freedom in frontal lobe epilepsy surgery

Around 50% of patients undergoing frontal lobe surgery for focal drug-resistant epilepsy become seizure free post-operatively; however, only about 30% of patients remain seizure free in the long-term. Early seizure recurrence is likely to be caused by partial resection of the epileptogenic lesion, whilst delayed seizure recurrence can occur even if the epileptogenic lesion has been completely excised. This suggests a coexistent epileptogenic network facilitating ictogenesis in close or distant dormant epileptic foci. As thalamic and striatal dysregulation can support epileptogenesis and disconnection of cortico-thalamostriatal pathways through hemispherotomy or neuromodulation can improve seizure outcome regardless of focality, we hypothesize that projections from the striatum and the thalamus to the cortex may contribute to this common epileptogenic network. To this end, we retrospectively reviewed a series of 47 consecutive individuals who underwent surgery for drug-resistant frontal lobe epilepsy. We performed voxel-based and tractography disconnectome analyses to investigate shared patterns of disconnection associated with long-term seizure freedom. Seizure freedom after 3 and 5 years was independently associated with disconnection of the anterior thalamic radiation and anterior cortico-striatal projections. This was also confirmed in a subgroup of 29 patients with complete resections, suggesting these pathways may play a critical role in supporting the development of novel epileptic networks. Our study indicates that network dysfunction in frontal lobe epilepsy may extend beyond the resection and putative epileptogenic zone. This may be critical in the pathogenesis of delayed seizure recurrence as thalamic and striatal networks may promote epileptogenesis and disconnection may underpin long-term seizure freedom.

Deep brain stimulation for patients with refractory epilepsy: nuclei selection and surgical outcome

Objective

By studying the surgical outcome of deep brain stimulation (DBS) of different target nuclei for patients with refractory epilepsy, we aimed to explore a clinically feasible target nucleus selection strategy.

Methods

We selected patients with refractory epilepsy who were not eligible for resective surgery. For each patient, we performed DBS on a thalamic nucleus [anterior nucleus of the thalamus (ANT), subthalamic nucleus (STN), centromedian nucleus (CMN), or pulvinar nucleus (PN)] selected based on the location of the patient's epileptogenic zone (EZ) and the possible epileptic network involved. We monitored the clinical outcomes for at least 12 months and analyzed the clinical characteristics and seizure frequency changes to assess the postoperative efficacy of DBS on the different target nuclei.

Results

Out of the 65 included patients, 46 (70.8%) responded to DBS. Among the 65 patients, 45 underwent ANT-DBS, 29 (64.4%) responded to the treatment, and four (8.9%) of them reported being seizure-free for at least 1 year. Among the patients with temporal lobe epilepsy (TLE, n = 36) and extratemporal lobe epilepsy (ETLE, n = 9), 22 (61.1%) and 7 (77.8%) responded to the treatment, respectively. Among the 45 patients who underwent ANT-DBS, 28 (62%) had focal to bilateral tonic-clonic seizures (FBTCS). Of these 28 patients, 18 (64%) responded to the treatment. Out of the 65 included patients, 16 had EZ related to the sensorimotor cortex and underwent STN-DBS. Among them, 13 (81.3%) responded to the treatment, and two (12.5%) were seizure-free for at least 6 months. Three patients had Lennox-Gastaut syndrome (LGS)-like epilepsy and underwent CMN-DBS; all of them responded to the treatment (seizure frequency reductions: 51.6%, 79.6%, and 79.5%). Finally, one patient with bilateral occipital lobe epilepsy underwent PN-DBS, reducing the seizure frequency by 69.7%.

Significance

ANT-DBS is effective for patients with TLE or ETLE. In addition, ANT-DBS is effective for patients with FBTCS. STN-DBS might be an optimal treatment for patients with motor seizures, especially when the EZ overlaps the sensorimotor cortex. CMN and PN may be considered modulating targets for patients with LGS-like epilepsy or occipital lobe epilepsy, respectively.

Therapeutic Strategies to Ameliorate Neuronal Damage in Epilepsy by Regulating Oxidative Stress, Mitochondrial Dysfunction, and Neuroinflammation

Epilepsy is a central nervous system disorder involving spontaneous and recurring seizures that affects 50 million individuals globally. Because approximately one-third of patients with epilepsy do not respond to drug therapy, the development of new therapeutic strategies against epilepsy could be beneficial. Oxidative stress and mitochondrial dysfunction are frequently observed in epilepsy. Additionally, neuroinflammation is increasingly understood to contribute to the pathogenesis of epilepsy. Mitochondrial dysfunction is also recognized for its contributions to neuronal excitability and apoptosis, which can lead to neuronal loss in epilepsy. This review focuses on the roles of oxidative damage, mitochondrial dysfunction, NAPDH oxidase, the blood-brain barrier, excitotoxicity, and neuroinflammation in the development of epilepsy. We also review the therapies used to treat epilepsy and prevent seizures, including anti-seizure medications, anti-epileptic drugs, anti-inflammatory therapies, and antioxidant therapies. In addition, we review the use of neuromodulation and surgery in the treatment of epilepsy. Finally, we present the role of dietary and nutritional strategies in the management of epilepsy, including the ketogenic diet and the intake of vitamins, polyphenols, and flavonoids. By reviewing available interventions and research on the pathophysiology of epilepsy, this review points to areas of further development for therapies that can manage epilepsy.

Efficacy of different strategies of responsive neurostimulation on seizure control and their association with acute neurophysiological effects in rats

Responsive neurostimulation (RNS) has shown promising but limited efficacy in the treatment of drug-resistant epilepsy. The clinical utility of RNS is hindered by the incomplete understanding of the mechanism behind its therapeutic effects. Thus, assessing the acute effects of responsive stimulation (AERS) based on intracranial EEG recordings in the temporal lobe epilepsy rat model may provide a better understanding of the potential therapeutic mechanisms underlying the antiepileptic effect of RNS. Furthermore, clarifying the correlation between AERS and seizure severity may help guide the optimization of RNS parameter settings. In this study, RNS with high (130 Hz) and low frequencies (5 Hz) was applied to the subiculum (SUB) and CA1. To quantify the changes induced by RNS, we calculated the AERS during synchronization by Granger causality and analyzed the band power ratio in the classic power band after different stimulations were delivered in the interictal and seizure onset periods, respectively. This demonstrates that only targets combined with an appropriate stimulation frequency could be efficient for seizure control. High-frequency stimulation of CA1 significantly shortened the ongoing seizure duration, which may be causally related to increased synchronization after stimulation. Both high-frequency stimulation of the CA1 and low-frequency stimulation delivered to the SUB reduced seizure frequency, and the reduced seizure risk may correlate with the change in power ratio near the theta band. It indicated that different stimulations may control seizures in diverse manners, perhaps with disparate mechanisms. More focus should be placed on understanding the correlation between seizure severity and synchronization and rhythm around theta bands to simplify the process of parameter optimization.

Cell therapy for neurological disorders: Progress towards an embryonic medial ganglionic eminence progenitor-based treatment

Impairment of development, migration, or function of inhibitory interneurons are key features of numerous circuit-based neurological disorders, such as epilepsy. From a therapeutic perspective, symptomatic treatment of these disorders often relies upon drugs or deep brain stimulation approaches to provide a general enhancement of GABA-mediated inhibition. A more effective strategy to target these pathological circuits and potentially provide true disease-modifying therapy, would be to selectively add new inhibitory interneurons into these circuits. One such strategy, using embryonic medial ganglionic (MGE) progenitor cells as a source of a unique sub-population of interneurons, has already proven effective as a cell transplantation therapy in a variety of preclinical models of neurological disorders, especially in mouse models of acquired epilepsy. Here we will discuss the evolution of this interneuron-based transplantation therapy in acquired epilepsy models, with an emphasis on the recent adaptation of MGE progenitor cells for xenotransplantation into larger mammals.

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.

Altered Cerebro-Cerebellar Effective Connectivity in New-Onset Juvenile Myoclonic Epilepsy

(1) Objective: Resting-state fMRI studies have indicated that juvenile myoclonic epilepsy (JME) could cause widespread functional connectivity disruptions between the cerebrum and cerebellum. However, the directed influences or effective connectivities (ECs) between these brain regions are poorly understood. In the current study, we aimed to evaluate the ECs between the cerebrum and cerebellum in patients with new-onset JME. (2) Methods: Thirty-four new-onset JME patients and thirty-four age-, sex-, and education-matched healthy controls (HCs) were included in this study. We compared the degree centrality (DC) between the two groups to identify intergroup differences in whole-brain functional connectivity. Then, we used a Granger causality analysis (GCA) to explore JME-caused changes in EC between cerebrum regions and cerebellum regions. Furthermore, we applied a correlation analysis to identify associations between aberrant EC and disease severity in patients with JME. (3) Results: Compared to HCs, patients with JME showed significantly increased DC in the left cerebellum posterior lobe (CePL.L), the right inferior temporal gyrus (ITG.R) and the right superior frontal gyrus (SFG.R), and decreased DC in the left inferior frontal gyrus (IFG.L) and the left superior temporal gyrus (STG.L). The patients also showed unidirectionally increased ECs from cerebellum regions to the cerebrum regions, including from the CePL.L to the right precuneus (PreCU.R), from the left cerebellum anterior lobe (CeAL.L) to the ITG.R, from the right cerebellum posterior lobe (CePL.R) to the IFG.L, and from the left inferior semi-lunar lobule of the cerebellum (CeISL.L) to the SFG.R. Additionally, the EC from the CeISL.L to the SFG.R was negatively correlated with the disease severity. (4) Conclusions: JME patients showed unidirectional EC disruptions from the cerebellum to the cerebrum, and the negative correlation between EC and disease severity provides a new perspective for understanding the cerebro-cerebellar neural circuit mechanisms in JME.