Effects of low-frequency repetitive transcranial magnetic stimulation on electroencephalogram and seizure frequency in 15 patients with temporal lobe epilepsy following dipole source localization

BACKGROUND： Low-frequency repetitive transcranial magnetic stimulation （rTMS） has been shown to significantly reduce epileptiform discharges and control clinical seizures in intractable epilepsy patients. The location of epileptic foci and magnetic stimulation sites remain uncertain. The effects of rTMS on electroencephalogram and seizure remain unclear in epileptic patients following dipole source localization. OBJECTIVE： To investigate the effects of low-frequency rTMS on electroencephalogram and seizure in temporal lobe epilepsy patients after dipole source localization. DESIGN, TIME AND SETTING： The randomized, controlled study was performed at the outpatient clinic Department of Neurology, Hospital Affiliated to North Sichuan Medical College from December 2003 to February 2007. PARTICIPANTS： A total of 30 temporal lobe epilepsy patients, comprising 19 males and 11 females, aged 1749 years, presented with epileptiform discharges and were enrolled for this study. Disease course ranged between 1-6 years, with 1-5 seizures per month. Imaging examinations revealed 11 patients with structural changes in the brain. The patients were randomly and equally assigned into drug treatment and transcranial magnetic stimulation （TMS） groups. METHODS： Patients in the drug treatment group were orally treated with carbamazepine. Patients in the TMS group received oral carbamazepine treatment of and TMS. A Maglite-r25 magnetic stimulator （Dantec Dynamics, Denmark） was used to stimulate epileptic foci in the temporal lobe following electroencephalogram dipole localization （1 Hz, 90% threshold intensity, at a stimulation frequency of 500 times, once a day, for 7 days）. MAIN OUTCOME MEASURES： At 30 days after TMS, seizure frequency and rate of epileptiform discharges were observed in patients from both groups. Therapeutic safety was investigated during treatment. RESULTS： Within 30 days of treatment, there were no significant differences in seizure frequency between the TMS group （1.5 ± 0.3） seizures and the drug treatment group [（1.9± 0.4） seizures] （P 〉 0.05）. The rate of epileptiform discharges [27% （4/15）] was significantly less in the TMS group than in the drug treatment group [73% （11/15）] （P 〈 0.05）. During TMS, five patients suffered from transient mild headache, but were completely relieved within 2 hours. CONCLUSION： Low-frequency rTMS exhibited inhibitory effects on epileptiform discharges over a short period of time, and decreased seizure frequency to some degree. Results from the present study suggested that low-frequency rTMS is safe.

Localization of epileptic foci in Children with childhood absence epilepsy by magnetoencephalography combined with synthetic aperture magnetometry

This present study was aimed to investigate the localizable diagnostic value of magnetoencephalography （MEG） combined with synthetic aperture magnetometry （SAM） in childhood absence epilepsy （CAE）. Thirteen CAE patients underwent MEG detection at resting state and after hyperventilation, and then the epileptic loci were located by SAM. In the thirteen CAE patients, epileptic foci were found in five cases （38.5%）, and they were all located in the bilateral frontal lobe, suggesting that the frontal lobe in some CAE patients may serve as the epileptic foci. Our findings indicate that MEG combined with SAM could be of diagnostic value in localizing the epileptic foci in certain CAE patients.

Epilepsy Focus Localization in Patients Utilizing BOLD Differences Related to Regional Metabolic Dynamics

This paper presents a theoretical elaboration aimed to explain the correlation found between a new rs-fMRI modality and electrophysiology and nuclear medicine neuroimaging, performed to localize epileptogenic brain areas. We present in detail the clinical history, and electrophysiological and neuroimaging results of one child with intractable epilepsy, who was submitted for Phase-1 work-up as candidate for epilepsy surgery. The patient underwent a thorough workup including video-telemetry, ictal and interictal nuclear medicine imaging, resting-state fMRI, EEG-fMRI, intracranial electroencephalography (ECoG), deep electrode implantation, and resective surgery. Electrophysiology and neuroimaging findings were concordant with findings provided by the resting-state mean signal. The patient became seizure-free after the resection of the target area. A theoretical discussion is provided that considers the presence of a stable BOLD effect explaining the findings of the observed resting-state mean signal. This stable BOLD is linked to low regional metabolism usually present in the epileptogenic area during interictal periods, coupled with low oxygen extraction. Low oxygen extraction leaves more oxygen for the draining venule and consequently increases the BOLD signal.

Clinical Application of SPECT to the Localization of Corticoepileptogenic Focus of Intractable Epilepsy

This paper presented 51 cases of intractable epilepsy, of which 36 were males, and 15 females,with a mean age of 21. They were all verified through CT/MRI, among which 17 were proved to have lesions on the brain, and 34 to bave no lesion. Before operation all the patients were identified by SPECT and cerebral blood flow imaging (CBF). During the operation they were monitored under subdural strip electrode ECoG for the localization of corticoepileptogenic focus. The results showed that the sensitivity rate of localization with SPECT for corticoepileptogenic focus location was 97.87 %.

Analyzing the Impact of Scene Transitions on Indoor Camera Localization through Scene Change Detection in Real-Time

Real-time indoor camera localization is a significant problem in indoor robot navigation and surveillance systems.The scene can change during the image sequence and plays a vital role in the localization performance of robotic applications in terms of accuracy and speed.This research proposed a real-time indoor camera localization system based on a recurrent neural network that detects scene change during the image sequence.An annotated image dataset trains the proposed system and predicts the camera pose in real-time.The system mainly improved the localization performance of indoor cameras by more accurately predicting the camera pose.It also recognizes the scene changes during the sequence and evaluates the effects of these changes.This system achieved high accuracy and real-time performance.The scene change detection process was performed using visual rhythm and the proposed recurrent deep architecture,which performed camera pose prediction and scene change impact evaluation.Overall,this study proposed a novel real-time localization system for indoor cameras that detects scene changes and shows how they affect localization performance.

Pathogenesis, diagnosis, and treatment of epilepsy: electromagnetic stimulation-mediated neuromodulation therapy and new technologies

Epilepsy is a severe,relapsing,and multifactorial neurological disorder.Studies regarding the accurate diagnosis,prognosis,and in-depth pathogenesis are crucial for the precise and effective treatment of epilepsy.The pathogenesis of epilepsy is complex and involves alterations in variables such as gene expression,protein expression,ion channel activity,energy metabolites,and gut microbiota composition.Satisfactory results are lacking for conventional treatments for epilepsy.Surgical resection of lesions,drug therapy,and non-drug interventions are mainly used in clinical practice to treat pain associated with epilepsy.Non-pharmacological treatments,such as a ketogenic diet,gene therapy for nerve regeneration,and neural regulation,are currently areas of research focus.This review provides a comprehensive overview of the pathogenesis,diagnostic methods,and treatments of epilepsy.It also elaborates on the theoretical basis,treatment modes,and effects of invasive nerve stimulation in neurotherapy,including percutaneous vagus nerve stimulation,deep brain electrical stimulation,repetitive nerve electrical stimulation,in addition to non-invasive transcranial magnetic stimulation and transcranial direct current stimulation.Numerous studies have shown that electromagnetic stimulation-mediated neuromodulation therapy can markedly improve neurological function and reduce the frequency of epileptic seizures.Additionally,many new technologies for the diagnosis and treatment of epilepsy are being explored.However,current research is mainly focused on analyzing patients’clinical manifestations and exploring relevant diagnostic and treatment methods to study the pathogenesis at a molecular level,which has led to a lack of consensus regarding the mechanisms related to the disease.

The role of axon guidance molecules in the pathogenesis of epilepsy

Current treatments for epilepsy can only manage the symptoms of the condition but cannot alter the initial onset or halt the progression of the disease. Consequently, it is crucial to identify drugs that can target novel cellular and molecular mechanisms and mechanisms of action. Increasing evidence suggests that axon guidance molecules play a role in the structural and functional modifications of neural networks and that the dysregulation of these molecules is associated with epilepsy susceptibility. In this review, we discuss the essential role of axon guidance molecules in neuronal activity in patients with epilepsy as well as the impact of these molecules on synaptic plasticity and brain tissue remodeling. Furthermore, we examine the relationship between axon guidance molecules and neuroinflammation, as well as the structural changes in specific brain regions that contribute to the development of epilepsy. Ample evidence indicates that axon guidance molecules, including semaphorins and ephrins, play a fundamental role in guiding axon growth and the establishment of synaptic connections. Deviations in their expression or function can disrupt neuronal connections, ultimately leading to epileptic seizures. The remodeling of neural networks is a significant characteristic of epilepsy, with axon guidance molecules playing a role in the dynamic reorganization of neural circuits. This, in turn, affects synapse formation and elimination. Dysregulation of these molecules can upset the delicate balance between excitation and inhibition within a neural network, thereby increasing the risk of overexcitation and the development of epilepsy. Inflammatory signals can regulate the expression and function of axon guidance molecules, thus influencing axonal growth, axon orientation, and synaptic plasticity. The dysregulation of neuroinflammation can intensify neuronal dysfunction and contribute to the occurrence of epilepsy. This review delves into the mechanisms associated with the pathogenicity of axon guidance molecules in epilepsy, offering a valuable reference for the exploration of therapeutic targets and presenting a fresh perspective on treatment strategies for this condition.

Survey of Indoor Localization Based on Deep Learning

This study comprehensively examines the current state of deep learning (DL) usage in indoor positioning.It emphasizes the significance and efficiency of convolutional neural networks (CNNs) and recurrent neuralnetworks (RNNs). Unlike prior studies focused on single sensor modalities like Wi-Fi or Bluetooth, this researchexplores the integration of multiple sensor modalities (e.g.,Wi-Fi, Bluetooth, Ultra-Wideband, ZigBee) to expandindoor localization methods, particularly in obstructed environments. It addresses the challenge of precise objectlocalization, introducing a novel hybrid DL approach using received signal information (RSI), Received SignalStrength (RSS), and Channel State Information (CSI) data to enhance accuracy and stability. Moreover, thestudy introduces a device-free indoor localization algorithm, offering a significant advancement with potentialobject or individual tracking applications. It recognizes the increasing importance of indoor positioning forlocation-based services. It anticipates future developments while acknowledging challenges such as multipathinterference, noise, data standardization, and scarcity of labeled data. This research contributes significantly toindoor localization technology, offering adaptability, device independence, and multifaceted DL-based solutionsfor real-world challenges and future advancements. Thus, the proposed work addresses challenges in objectlocalization precision and introduces a novel hybrid deep learning approach, contributing to advancing locationcentricservices.While deep learning-based indoor localization techniques have improved accuracy, challenges likedata noise, standardization, and availability of training data persist. However, ongoing developments are expectedto enhance indoor positioning systems to meet real-world demands.

Improved PSO-Extreme Learning Machine Algorithm for Indoor Localization

Wi Fi and fingerprinting localization method have been a hot topic in indoor positioning because of their universality and location-related features.The basic assumption of fingerprinting localization is that the received signal strength indication(RSSI)distance is accord with the location distance.Therefore,how to efficiently match the current RSSI of the user with the RSSI in the fingerprint database is the key to achieve high-accuracy localization.In this paper,a particle swarm optimization-extreme learning machine(PSO-ELM)algorithm is proposed on the basis of the original fingerprinting localization.Firstly,we collect the RSSI of the experimental area to construct the fingerprint database,and the ELM algorithm is applied to the online stages to determine the corresponding relation between the location of the terminal and the RSSI it receives.Secondly,PSO algorithm is used to improve the bias and weight of ELM neural network,and the global optimal results are obtained.Finally,extensive simulation results are presented.It is shown that the proposed algorithm can effectively reduce mean error of localization and improve positioning accuracy when compared with K-Nearest Neighbor(KNN),Kmeans and Back-propagation(BP)algorithms.

Treadmill exercise improves hippocampal neural plasticity and relieves cognitive deficits in a mouse model of epilepsy

Epilepsy frequently leads to cognitive dysfunction and approaches to treatment remain limited.Although regular exercise effectively improves learning and memory functions across multiple neurological diseases,its application in patients with epilepsy remains controversial.Here,we adopted a 14-day treadmill-exercise paradigm in a pilocarpine injection-induced mouse model of epilepsy.Cognitive assays confirmed the improvement of object and spatial memory after endurance training,and electrophysiological studies revealed the maintenance of hippocampal plasticity as a result of physical exercise.Investigations of the mechanisms underlying this effect revealed that exercise protected parvalbumin interneurons,probably via the suppression of neuroinflammation and improved integrity of blood-brain barrier.In summary,this work identified a previously unknown mechanism through which exercise improves cognitive rehabilitation in epilepsy.

Aberrant adult neurogenesis in intractable epilepsy:can GABAergic progenitor transplantation normalize this process?

Temporal lobe epilepsy(TLE) is a common type of focal epilepsy characterized by seizure foci within the temporal lobes.While surgical resection of the foci is an established and effective approach for controlling seizures,both temporal lobes cannot be removed,due to their prominent roles in learning and memory.Additionally,seizures induce changes to the temporal lobes that contribute to hyperexcitability,including mossy fiber sprouting,astrogliosis.

Astrocyte chloride,excitatory-inhibitory balance and epilepsy

Excitation and inhibition are at the core of brain function and malfunction.To sustain the activity of neuronal networks over time and space,glutamatergic excitation is balanced by GABAergic inhibition.The equipoise of excitation and inhibition,known as the excitation/inhibition(E/I)balance,is crucial for proper brain function.The E/I balance is highly dynamic and shifts across different brain states:wakefulness primarily augments excitatory activity,while sleep promotes a decrease in excitation and an increase in inhibition(Bridi et al.,2020).Neuronal activity during various brain states is primarily regulated by neurotransmitters(Schiemann et al.,2015),alongside non-synaptic mechanisms that operate on a slower timescale.The non-synaptic mechanisms are many,with the ionic composition of the extracellular space playing a significant role;altering extracellular ion concentrations affects sleep,arousal,electroencephalogram patterns,and behavioral states(Ding et al.,2016).

Psychiatric comorbidities in epilepsy:population co-occurrence,genetic correlations and causal effects

Background Psychiatric comorbidities are common in patients with epilepsy.Reasons for the co-occurrence of psychiatric conditions and epilepsy remain poorly understood.Aim We aimed to triangulate the relationship between epilepsy and psychiatric conditions to determine the extent and possible origins of these conditions.Methods Using nationwide Swedish health registries,we quantified the lifetime prevalence of psychiatric disorders in patients with epilepsy.We then used summarydata from genome-wide association studies to investigate whether the identified observational associations could be attributed to a shared underlying genetic aetiology using cross-trait linkage disequilibrium score regression.Finally,we assessed the potential bidirectional relationships using two-sample Mendelian randomisation.Results In a cohort of 7628495 individuals,we found that almost half of the 94435 individuals diagnosed with epilepsy were also diagnosed with a psychiatric condition in their lifetime(adjusted lifetime prevalence,44.09%;95%confidence interval(Cl)43.78%to 44.39%).We found evidence for a genetic correlation between epilepsy and some neurodevelopmental and psychiatric conditions.For example,we observed a genetic correlation between epilepsy and attention-deficit/hyperactivity disorder(r,=0.18,95%Cl 0.09 to 0.27,p<0.001)—a correlation that was more pronounced in focal epilepsy(r=0.23,95%CI 0.09 to 0.36,p<0.001).Findings from Mendelian randomisation using common genetic variants did not support bidirectional effects between epilepsy and neurodevelopmental or psychiatric conditions.Conclusions Psychiatric comorbidities are common in patients with epilepsy.Genetic correlations may partially explain some comorbidities;however,there is little evidence of a bidirectional relationship between the genetic liability of epilepsy and psychiatric conditions.These findings highlight the need to understand the role of environmental factors or rare genetic variations in the origins of psychiatric comorbidities in epilepsy.

Nrf2 as a potential target for the treatment of epilepsy

Epilepsy is a prevalent chronic brain disorder that is characterized by a persistent predisposition to recurrently generate epileptic seizures and is often associated with cognitive and psychological consequences.Epilepsy affects approximately 65 million individuals,including both males and females of all ages worldwide,and poses a significant burden on patients,their families,and the health system(Vezzani et al.,2019).

Electroencephalogram findings in 10 patients with post-stroke epilepsy:A retrospective study

BACKGROUND Post-stroke epilepsy is a common and easily overlooked complication of acute cerebrovascular disease.Long-term seizures can seriously affect the prognosis and quality of life of patients.Electroencephalogram(EEG)is the simplest way to diagnose epilepsy,and plays an important role in predicting seizures and guiding medication.AIM To explore the EEG characteristics of patients with post-stroke epilepsy and improve the detection rate of inter-seizure epileptiform discharges.METHODS From January 2017 to June 2020,10 patients with post-stroke epilepsy in our hospital were included.The clinical,imaging,and EEG characteristics were collected.The stroke location,seizure type,and ictal and interictal EEG manifestations of the patients with post-stroke epilepsy were then retrospectively analyzed.RESULTS In all 10 patients,epileptiform waves occurred in the side opposite to the stroke lesion during the interictal stage;these manifested as sharp wave,sharp-wave complex,or spike discharges in the anterior head lead of the side opposite to the lesion.CONCLUSION In EEG,epileptiform waves can occur in the side opposite to the stroke lesion in patients with post-stroke epilepsy.

Interplay between topology and localization on superconducting circuits

Topological insulators occupy a prominent position in the realm of condensed matter physics. Nevertheless, the presence of strong disorder has the potential to disrupt the integrity of topological states, leading to the localization of all states.This study delves into the intricate interplay between topology and localization within the one-dimensional Su–Schrieffer–Heeger(SSH) model, which incorporates controllable off-diagonal quasi-periodic modulations on superconducting circuits.Through the application of external alternating current(ac) magnetic fluxes, each transmon undergoes controlled driving,enabling independent tuning of all coupling strengths. Within a framework of this model, we construct comprehensive phase diagrams delineating regions characterized by extended topologically nontrivial states, critical localization, and coexisting topological and critical localization phases. The paper also addresses the dynamics of qubit excitations, elucidating distinct quantum state transfers resulting from the intricate interplay between topology and localization. Additionally, we propose a method for detecting diverse quantum phases utilizing existing experimental setups.

Cognitive Disorders, Depression and Anxiety in Temporal Lobe Epilepsy: An Overview

Partial epilepsies, originating in a specific brain region, affect about 60% of adults with epilepsy. Temporal lobe epilepsy (TLE) is the most prevalent subtype within this category, often necessitating surgical intervention due to its refractoriness to antiepileptic drugs (AEDs). Hippocampal sclerosis, a common underlying pathology, often exacerbates the severity by introducing cognitive and emotional challenges. This review delves deeper into the cognitive profile of TLE, along with the risk factors for cognitive disorders, depression, and anxiety in this population.

Bibliometric analysis of research in epilepsy and comorbid depression from 2014 to 2023

BACKGROUND Epilepsy and depression have complicated bidirectional relationships.Our study aimed to explore the field of epilepsy comorbid with depression in a bibliometric perspective from 2014-2023.AIM To improve our understanding of epilepsy and depression by evaluating the relationship between epilepsy and depression,bibliometric analyses were performed.METHODS Epilepsy and depression-related publications from the last decade were retrieved from the Web of Science Core Collection.We conducted bibliometric and visual analysis using VOSviewer and CiteSpace,examining authorships,countries,institutions,journals of publication,co-citations of references,connections between keywords,clusters of keywords,and keywords with citation bursts.RESULTS Over the past ten years,we collected 1045 research papers focusing on the field of epilepsy and comorbid depression.Publications on epilepsy and depression have shown a general upward trend over time,though with some fluctuations.The United States,with 287 articles,and the University of Melbourne,contributing 34 articles,were the top countries and institutions,respectively.In addition,in the field of epilepsy and depression,Professor Lee,who has published 30 articles,was the most contributing author.The hot topics pay attention to the quality of life in patients with epilepsy and depression.CONCLUSION We reported that quality of life and stigma in patients with epilepsy comorbid with depression are possible future hot topics and directions in the field of epilepsy and depression research.

Dynamical localization in a non-Hermitian Floquet synthetic system

We investigate the non-Hermitian effects on quantum diffusion in a kicked rotor model where the complex kicking potential is quasi-periodically modulated in the time domain.The synthetic space with arbitrary dimension can be created by incorporating incommensurate frequencies in the quasi-periodical modulation.In the Hermitian case,strong kicking induces the chaotic diffusion in the four-dimension momentum space characterized by linear growth of mean energy.We find that the quantum coherence in deep non-Hermitian regime can effectively suppress the chaotic diffusion and hence result in the emergence of dynamical localization.Moreover,the extent of dynamical localization is dramatically enhanced by increasing the non-Hermitian parameter.Interestingly,the quasi-energies become complex when the non-Hermitian parameter exceeds a certain threshold value.The quantum state will finally evolve to a quasi-eigenstate for which the imaginary part of its quasi-energy is large most.The exponential localization length decreases with the increase of the non-Hermitian parameter,unveiling the underlying mechanism of the enhancement of the dynamical localization by nonHermiticity.

Scenario Modeling-Aided AP Placement Optimization Method for Indoor Localization and Network Access

Owing to the ubiquity of wireless networks and the popularity of WiFi infrastructures,received signal strength(RSS)-based indoor localization systems have received much attention.The placement of access points(APs)significantly influences localization accuracy and network access.However,the indoor scenario and network access are not fully considered in previous AP placement optimization methods.This study proposes a practical scenario modelingaided AP placement optimization method for improving localization accuracy and network access.In order to reduce the gap between simulation-based and field measurement-based AP placement optimization methods,we introduce an indoor scenario modeling and Gaussian process-based RSS prediction method.After that,the localization and network access metrics are implemented in the multiple objective particle swarm optimization(MOPSO)solution,Pareto front criterion and virtual repulsion force are applied to determine the optimal AP placement.Finally,field experiments demonstrate the effectiveness of the proposed indoor scenario modeling method and RSS prediction model.A thorough comparison confirms the localization and network access improvement attributed to the proposed anchor placement method.