RESUMO
BACKGROUND: Epilepsy, a complex neurological disorder, is closely linked with structural and functional irregularities in the brain. However, the causal relationship between brain imaging-derived phenotypes (IDPs) and epilepsy remains unclear. This study aimed to investigate this relationship by employing a two-sample bidirectional Mendelian randomization (MR) approach. METHODS: The analysis involved 3935 cerebral IDPs from the UK Biobank and all documented cases of epilepsy (all epilepsies) cohorts from the International League Against Epilepsy, with further validation through replication and meta-analyses using epilepsy Genome-Wide Association Studies datasets from the FinnGen database. Additionally, a multivariate MR analysis framework was utilized to assess the direct impact of IDPs on all epilepsies. Furthermore, we performed a bidirectional MR analysis to investigate the relationship between the IDPs identified in all epilepsies and the 15 specific subtypes of epilepsy. RESULTS: The study identified significant causal links between four IDPs and epilepsy risk. Decreased fractional anisotropy in the left inferior longitudinal fasciculus was associated with a higher risk of epilepsy (odds ratio [OR]: 0.89, p = 3.31×10-5). Conversely, increased mean L1 in the left posterior thalamic radiation (PTR) was independently associated with a heightened epilepsy risk (OR: 1.14, p = 4.72×10-5). Elevated L3 in the left cingulate gyrus was also linked to an increased risk (OR: 1.09, p = .03), while decreased intracellular volume fraction in the corpus callosum was correlated with higher epilepsy risk (OR: 0.94, p = 1.15×10-4). Subtype analysis revealed that three of these IDPs are primarily associated with focal epilepsy (FE). Notably, increased L1 in the left PTR was linked to an elevated risk of hippocampal sclerosis (HS) and lesion-negative FE, whereas elevated L3 in the left cingulate gyrus was associated with HS-related FE. CONCLUSIONS: Our research offers genetic evidence for a causal link between brain IDPs and epilepsy. These results enhance our understanding of the structural brain changes associated with the onset and progression of epilepsy.
Assuntos
Epilepsia , Análise da Randomização Mendeliana , Humanos , Epilepsia/genética , Epilepsia/diagnóstico por imagem , Epilepsia/fisiopatologia , Encéfalo/diagnóstico por imagem , Encéfalo/patologia , Estudo de Associação Genômica Ampla , Imageamento por Ressonância Magnética , Masculino , Feminino , Fenótipo , Neuroimagem/métodos , Adulto , Pessoa de Meia-IdadeRESUMO
The integration of hippocampal oscillations during non-rapid eye movement (NREM) sleep is crucial for memory consolidation. However, how cardinal sleep oscillations bind across various subfields of the human hippocampus to promote information transfer and synaptic plasticity remains unclear. Using human intracranial recordings from 25 epilepsy patients, we find that hippocampal subfields, including DG/CA3, CA1, and SUB, all exhibit significant delta and spindle power during NREM sleep. The DG/CA3 displays strong coupling between delta and ripple oscillations with all the other hippocampal subfields. In contrast, the regions of CA1 and SUB exhibit more precise coordination, characterized by event-level triple coupling between delta, spindle, and ripple oscillations. Furthermore, we demonstrate that the synaptic plasticity within the hippocampal circuit, as indexed by delta-wave slope, is linearly modulated by spindle power. In contrast, ripples act as a binary switch that triggers a sudden increase in delta-wave slope. Overall, these results suggest that different subfields of the hippocampus regulate one another through diverse layers of sleep oscillation synchronization, collectively facilitating information processing and synaptic plasticity during NREM sleep.
Assuntos
Hipocampo , Plasticidade Neuronal , Humanos , Plasticidade Neuronal/fisiologia , Masculino , Feminino , Adulto , Hipocampo/fisiologia , Adulto Jovem , Sono/fisiologia , Eletroencefalografia , Pessoa de Meia-Idade , Fases do Sono/fisiologia , Epilepsia/fisiopatologia , Sono de Ondas Lentas/fisiologiaRESUMO
Visual working memory depends on both material-specific brain areas in the ventral visual stream (VVS) that support the maintenance of stimulus representations and on regions in the prefrontal cortex (PFC) that control these representations. How executive control prioritizes working memory contents and whether this affects their representational formats remains an open question, however. Here, we analyzed intracranial EEG (iEEG) recordings in epilepsy patients with electrodes in VVS and PFC who performed a multi-item working memory task involving a retro-cue. We employed Representational Similarity Analysis (RSA) with various Deep Neural Network (DNN) architectures to investigate the representational format of prioritized VWM content. While recurrent DNN representations matched PFC representations in the beta band (15-29 Hz) following the retro-cue, they corresponded to VVS representations in a lower frequency range (3-14 Hz) towards the end of the maintenance period. Our findings highlight the distinct coding schemes and representational formats of prioritized content in VVS and PFC.
Assuntos
Memória de Curto Prazo , Córtex Pré-Frontal , Humanos , Memória de Curto Prazo/fisiologia , Córtex Pré-Frontal/fisiologia , Masculino , Feminino , Adulto , Adulto Jovem , Epilepsia/fisiopatologia , Eletroencefalografia , Sinais (Psicologia) , Pessoa de Meia-Idade , Redes Neurais de Computação , Percepção Visual/fisiologia , Eletrocorticografia , Mapeamento Encefálico/métodos , Função Executiva/fisiologiaRESUMO
Antagonistic activity of brain networks likely plays a fundamental role in how the brain optimizes its performance by efficient allocation of computational resources. A prominent example involves externally/internally oriented attention tasks, implicating two anticorrelated, intrinsic brain networks: the default mode network (DMN) and the dorsal attention network (DAN). To elucidate electrophysiological underpinnings and causal interplay during attention switching, we recorded intracranial EEG (iEEG) from 25 epilepsy patients with electrode contacts localized in the DMN and DAN. We show antagonistic network dynamics of activation-related changes in high-frequency (> 50 Hz) and low-frequency (< 30 Hz) power. The temporal profile of information flow between the networks estimated by functional connectivity suggests that the activated network inhibits the other one, gating its activity by increasing the amplitude of the low-frequency oscillations. Insights about inter-network communication may have profound implications for various brain disorders in which these dynamics are compromised.
Assuntos
Atenção , Encéfalo , Rede Nervosa , Humanos , Atenção/fisiologia , Masculino , Feminino , Adulto , Encéfalo/fisiologia , Encéfalo/fisiopatologia , Rede Nervosa/fisiologia , Adulto Jovem , Epilepsia/fisiopatologia , Eletroencefalografia , Pessoa de Meia-Idade , Fenômenos EletrofisiológicosRESUMO
Seizure prediction using EEG has significant implications for the daily monitoring and treatment of epilepsy patients. However, the task is challenging due to the underlying spatiotemporal correlations and patient heterogeneity. Traditional methods often use large-scale models with independent components to capture the spatial and temporal features of EEG separately or explore shared patterns among patients with the help of pre-defined functional connectivity. In this paper, we propose a compact model, called the graph convolutional network based on adaptive functional connectivity (AFC-GCN), for seizure prediction. The model can adaptively infer evolution of functional connectivity in epilepsy patients during seizures through data-driven methods and synchronously analyze spatiotemporal response of functional connectivity in multiple topologies. On CHB-MIT datasets, the experimental results demonstrate that AFC-GCN achieves accurate and robust performance with low complexity. (AUC: 0.9820, accuracy: 0.9815, sensitivity: 0.9802, FPR: 0.0172). The proposed method has the potential to predict seizure during daily monitoring.
Assuntos
Algoritmos , Eletroencefalografia , Redes Neurais de Computação , Convulsões , Humanos , Eletroencefalografia/métodos , Convulsões/fisiopatologia , Convulsões/diagnóstico , Epilepsia/fisiopatologia , Epilepsia/diagnóstico , Masculino , Feminino , Adulto , Área Sob a Curva , Curva ROCRESUMO
DHPS deficiency syndrome is an ultra-rare neurodevelopmental disorder (NDD) which results from biallelic mutations in the gene encoding the enzyme deoxyhypusine synthase (DHPS). DHPS is essential to synthesize hypusine, a rare amino acid formed by post-translational modification of a conserved lysine in eukaryotic initiation factor 5 A (eIF5A). DHPS deficiency syndrome causes epilepsy, cognitive and motor impairments, and mild facial dysmorphology. In mice, a brain-specific genetic deletion of Dhps at birth impairs eIF5AHYP-dependent mRNA translation. This alters expression of proteins required for neuronal development and function, and phenotypically models features of human DHPS deficiency. We studied the role of DHPS in early brain development using a zebrafish loss-of-function model generated by knockdown of dhps expression with an antisense morpholino oligomer (MO) targeting the exon 2/intron 2 (E2I2) splice site of the dhps pre-mRNA. dhps knockdown embryos exhibited dose-dependent developmental delay and dysmorphology, including microcephaly, axis truncation, and body curvature. In dhps knockdown larvae, electrophysiological analysis showed increased epileptiform activity, and confocal microscopy analysis revealed reduced arborisation of GABAergic neurons. Our findings confirm that hypusination of eIF5A by DHPS is needed for early brain development, and zebrafish with an antisense knockdown of dhps model features of DHPS deficiency syndrome.
Assuntos
Modelos Animais de Doenças , Epilepsia , Interneurônios , Oxirredutases atuantes sobre Doadores de Grupo CH-NH , Peixe-Zebra , Animais , Oxirredutases atuantes sobre Doadores de Grupo CH-NH/genética , Oxirredutases atuantes sobre Doadores de Grupo CH-NH/metabolismo , Epilepsia/genética , Epilepsia/patologia , Epilepsia/fisiopatologia , Interneurônios/metabolismo , Proteínas de Peixe-Zebra/metabolismo , Proteínas de Peixe-Zebra/genética , Proteínas de Peixe-Zebra/deficiência , Técnicas de Silenciamento de Genes , Fenótipo , Encéfalo/patologia , Encéfalo/metabolismoRESUMO
This paper comprehensively reviews hardware acceleration techniques and the deployment of convolutional neural networks (CNNs) for analyzing electroencephalogram (EEG) signals across various application areas, including emotion classification, motor imagery, epilepsy detection, and sleep monitoring. Previous reviews on EEG have mainly focused on software solutions. However, these reviews often overlook key challenges associated with hardware implementation, such as scenarios that require a small size, low power, high security, and high accuracy. This paper discusses the challenges and opportunities of hardware acceleration for wearable EEG devices by focusing on these aspects. Specifically, this review classifies EEG signal features into five groups and discusses hardware implementation solutions for each category in detail, providing insights into the most suitable hardware acceleration strategies for various application scenarios. In addition, it explores the complexity of efficient CNN architectures for EEG signals, including techniques such as pruning, quantization, tensor decomposition, knowledge distillation, and neural architecture search. To the best of our knowledge, this is the first systematic review that combines CNN hardware solutions with EEG signal processing. By providing a comprehensive analysis of current challenges and a roadmap for future research, this paper provides a new perspective on the ongoing development of hardware-accelerated EEG systems.
Assuntos
Eletroencefalografia , Redes Neurais de Computação , Processamento de Sinais Assistido por Computador , Eletroencefalografia/métodos , Eletroencefalografia/instrumentação , Humanos , Dispositivos Eletrônicos Vestíveis , Epilepsia/diagnóstico , Epilepsia/fisiopatologiaRESUMO
BACKGROUND: Mozart's Sonata for Two Pianos in D Major (K448) is a classic double piano work. This study investigated its effect on children with epilepsy (EP) and analyzed the changes in electroencephalography (EEG) among children on the basis of acoustic quality. METHODS: The clinical data of 150 children with EP in the Affiliated Hospital (Group) of Putian University from March 2020 to March 2023 were retrospectively analyzed. They were divided into group A (n = 73, antiepileptic drug therapy) and group B (n = 77, antiepileptic drug therapy + Mozart K448) in accordance with the treatment methods. The seizure frequency, frequency of epileptic discharges (EDs), and Quality of Life in Childhood Epilepsy Questionnaire-16 in both groups were compared before and after treatment. The changes in EEG before, during, and after music appreciation were observed. The effects of the acoustic characteristics (rhythm, root mean square value, roughness, and spectral flux) of Mozart K448 on EDs in children were explored. RESULTS: After treatment, group A had a higher seizure frequency (P < 0.001), a higher frequency of EDs (P < 0.05), and significantly lower scores of cognition and emotion than group B (P < 0.001), without significant difference in the scores of social function and physical function (P > 0.05). The frequency of EDs before music appreciation was significantly higher than that during music appreciation (P < 0.01). Spearman correlation analysis showed that the rhythm, spectral flux, and roughness in Mozart K488 were related to the decrease in EDs among children with EP (P < 0.001). CONCLUSION: This study confirmed the application effect of Mozart K448 in children with EP. Mozart K448 can decrease the seizure frequency, reduce the ED occurrence, and improve the quality of life. The acoustic characteristics of K448 may be the reason for improving EP in children.
Assuntos
Eletroencefalografia , Epilepsia , Musicoterapia , Qualidade de Vida , Humanos , Feminino , Criança , Masculino , Musicoterapia/métodos , Epilepsia/tratamento farmacológico , Epilepsia/fisiopatologia , Estudos Retrospectivos , Pré-Escolar , Música , Anticonvulsivantes/uso terapêutico , AdolescenteRESUMO
Rationale: The brain-computer interface (BCI) is core tasks in comprehensively understanding the brain, and is one of the most significant challenges in neuroscience. The development of novel non-invasive neuromodulation technique will drive major innovations and breakthroughs in the field of BCI. Methods: We develop a new noninvasive closed-loop acoustic brain-computer interface (aBCI) for decoding the seizure onset based on the electroencephalography and triggering ultrasound stimulation of the vagus nerve to terminate seizures. Firstly, we create the aBCI system and decode the onset of seizure via a multi-level threshold model based on the analysis of wireless-collected electroencephalogram (EEG) signals recorded from above the hippocampus. Then, the different acoustic parameters induced acoustic radiation force were used to stimulate the vagus nerve in a rat model of epilepsy-induced by pentylenetetrazole. Finally, the results of epileptic EEG signal triggering ultrasound stimulation of the vagus nerve to control seizures. In addition, the mechanism of aBCI control seizures were investigated by real-time quantitative polymerase chain reaction (RT-qPCR). Results: In a rat model of epilepsy, the aBCI system selectively actives mechanosensitive neurons in the nodose ganglion while suppressing neuronal excitability in the hippocampus and amygdala, and stops seizures rapidly upon ultrasound stimulation of the vagus nerve. Physical transection or chemical blockade of the vagus nerve pathway abolish the antiepileptic effects of aBCI. In addition, aBCI shows significant antiepileptic effects compared to conventional vagus nerve electrical stimulation in an acute experiment. Conclusions: Closed-loop aBCI provides a novel, safe and effective tool for on-demand stimulation to treat abnormal neuronal discharges, opening the door to next generation non-invasive BCI.
Assuntos
Interfaces Cérebro-Computador , Eletroencefalografia , Convulsões , Animais , Ratos , Convulsões/fisiopatologia , Convulsões/terapia , Eletroencefalografia/métodos , Ratos Sprague-Dawley , Estimulação do Nervo Vago/métodos , Modelos Animais de Doenças , Masculino , Hipocampo/fisiopatologia , Nervo Vago/fisiologia , Epilepsia/terapia , Epilepsia/fisiopatologia , Encéfalo/fisiopatologia , Encéfalo/fisiologiaRESUMO
In this issue of Neuron, Zada et al.1 examine how linguistic information flows from a speaker's brain to a listener's brain during face-to-face spontaneous conversation. The authors use intracranial recordings from five pairs of epilepsy patients and neural network language models to establish the existence of an abstract, linguistic space that is shared during conversation.
Assuntos
Linguística , Humanos , Encéfalo/fisiologia , Idioma , Epilepsia/fisiopatologiaRESUMO
Despite promising advancements, closed-loop neurostimulation for drug-resistant epilepsy (DRE) still relies on manual tuning and produces variable outcomes, while automated predictable algorithms remain an aspiration. As a fundamental step towards addressing this gap, here we study predictive dynamical models of human intracranial EEG (iEEG) response under parametrically rich neurostimulation. Using data from n = 13 DRE patients, we find that stimulation-triggered switched-linear models with ~300 ms of causal historical dependence best explain evoked iEEG dynamics. These models are highly consistent across different stimulation amplitudes and frequencies, allowing for learning a generalizable model from abundant STIM OFF and limited STIM ON data. Further, evoked iEEG in nearly all subjects exhibited a distance-dependent pattern, whereby stimulation directly impacts the actuation site and nearby regions (â² 20 mm), affects medium-distance regions (20 ~ 100 mm) through network interactions, and hardly reaches more distal areas (â³ 100 mm). Peak network interaction occurs at 60 ~ 80 mm from the stimulation site. Due to their predictive accuracy and mechanistic interpretability, these models hold significant potential for model-based seizure forecasting and closed-loop neurostimulation design.
Assuntos
Eletrocorticografia , Lobo Temporal , Humanos , Lobo Temporal/fisiopatologia , Lobo Temporal/fisiologia , Feminino , Masculino , Epilepsia Resistente a Medicamentos/fisiopatologia , Epilepsia Resistente a Medicamentos/terapia , Adulto , Eletroencefalografia , Adulto Jovem , Epilepsia/fisiopatologia , Epilepsia/terapia , Modelos NeurológicosRESUMO
Cell replacement therapies using medial ganglionic eminence (MGE)-derived GABAergic precursors reduce seizures by restoring inhibition in animal models of epilepsy. However, how MGE-derived cells affect abnormal neuronal networks and consequently brain oscillations to reduce ictogenesis is still under investigation. We performed quantitative analysis of pre-ictal local field potentials (LFP) of cortical and hippocampal CA1 areas recorded in vivo in the pilocarpine rat model of epilepsy, with or without intrahippocampal MGE-precursor grafts (PILO and PILO+MGE groups, respectively). The PILO+MGE animals had a significant reduction in the number of seizures. The quantitative analysis of pre-ictal LFP showed decreased power of cortical and hippocampal delta, theta and beta oscillations from the 5 min. interictal baseline to the 20 s. pre-ictal period in both groups. However, PILO+MGE animals had higher power of slow and fast oscillations in the cortex and lower power of slow and fast oscillations in the hippocampus compared to the PILO group. Additionally, PILO+MGE animals exhibited decreased cortico-hippocampal synchrony for theta and gamma oscillations at seizure onset and lower hippocampal CA1 synchrony between delta and theta with slow gamma oscillations compared to PILO animals. These findings suggest that MGE-derived cell integration into the abnormally rewired network may help control ictogenesis.
Assuntos
Córtex Cerebral , Modelos Animais de Doenças , Epilepsia , Hipocampo , Pilocarpina , Animais , Pilocarpina/toxicidade , Hipocampo/fisiopatologia , Masculino , Córtex Cerebral/fisiopatologia , Epilepsia/induzido quimicamente , Epilepsia/fisiopatologia , Ratos , Ondas Encefálicas/fisiologia , Ratos Wistar , Eletroencefalografia , Eminência GanglionarRESUMO
PURPOSE: To analyze the characteristics of cerebral blood flow changes of poor sleep quality in people with epilepsy(PWE). METHODS: 90 PWE treated in The General Hospital of Ningxia Medical University from December 2021 to September 2023 were divided into poor sleep quality group (PSQG) and good sleep quality group (GSQG) according to the Chinese version of the Pittsburgh Sleep Quality Index (CPSQI), to compare the differences in cerebral perfusion between the two groups of patients, so as to summarize the characteristics of cerebral blood flow changes of poor sleep quality in PWE. RESULTS: The positive rate of interictal single-photon emission computed tomography/computed tomography (SPECT/CT) was 76.7 %(69/90), which showed localized cerebral hypoperfusion. There was no statistical difference between the two groups of PSQG (N=29) and GSQG (N=61) in terms of the positive rate of SPECT/CT, the number of hypoperfusion foci, and the range of hypoperfusion foci. In PSQG and GSQG, 9 patients(31.0 %) and 6 patients(9.8 %) showed hypoperfusion in the right parietal lobe, respectively, and the difference between the two groups was statistically significant (P=0.017). There was no statistical difference the rate of the interictal epileptiform discharges (IEDs) and the brain area of IEDs in electroencephalography(EEG) between the two groups. CONCLUSION: SPECT/CT of poor sleep quality in PWE demonstrated hypoperfusion in the right parietal lobe.
Assuntos
Circulação Cerebrovascular , Epilepsia , Tomografia Computadorizada com Tomografia Computadorizada de Emissão de Fóton Único , Humanos , Feminino , Masculino , Adulto , Epilepsia/diagnóstico por imagem , Epilepsia/fisiopatologia , Epilepsia/complicações , Pessoa de Meia-Idade , Circulação Cerebrovascular/fisiologia , Adulto Jovem , Adolescente , Encéfalo/diagnóstico por imagem , Encéfalo/fisiopatologia , Qualidade do Sono , Idoso , Eletroencefalografia , Transtornos do Sono-Vigília/diagnóstico por imagem , Transtornos do Sono-Vigília/fisiopatologia , Transtornos do Sono-Vigília/etiologiaRESUMO
Epilepsy claims the lives of many people, so researchers strive to build highly accurate diagnostic models. One of the limitations of obtaining high accuracy is the scarcity of Electroencephalography (EEG) data and the fact that they are from different devices in terms of the channels number and sampling frequency. The paper proposes universal epilepsy diagnoses with high accuracy from electroencephalography signals taken from any device. The novelty of the proposal is to convert VEEG video into images, separating some parts and unifying images taken from different devices. The images were tested by dividing the video into labeled frames of different periods. By adding the spatial attention layer to the deep learning in the new model, classification accuracy increased to 99.95 %, taking five seconds/frame. The proposed has high accuracy in detecting epilepsy from any EEG without being restricted to a specific number of channels or sampling frequencies.
Assuntos
Aprendizado Profundo , Eletroencefalografia , Epilepsia , Epilepsia/diagnóstico , Epilepsia/fisiopatologia , Humanos , Processamento de Sinais Assistido por Computador , Processamento de Imagem Assistida por Computador/métodos , Diagnóstico por Computador/métodosRESUMO
BACKGROUND: Activation procedures (APs) are adopted during routine electroencephalography (rEEG) to provoke interictal epileptiform abnormalities (EAs). This study aimed to observe interictal and ictal (EAs) of different EEG patterns, provoked by various APs. METHODOLOGY: This cross-sectional study was performed in the neurology department of King Fahd hospital of university, Saudi Arabia. The EEGs and medical records of patients who presented for EEG recordings were screened initially, then 146 EEGs provoked EAs due to utilization of APs, were included for analysis. RESULTS: Among all EEGs with provoked EAs, Non-rapid eye movement sleep (NREM) provoked EAs in 93 (63.7%) patients with following patterns, focal spike wave discharges (FSWDs) 45 (P= 0.01), focal spike wave discharges with bilateral synchrony (FSWDBS) 27 (P=0.03) and generalized spike wave discharges (GSWDs) 46 (P=0.01). Intermittent photic stimulation (IPS) most significantly provoked FSWDs in 07 patient (P =0.01) and GSWDs in 30 patients (P=<0.001) 7 patients (P = 0.01) and GSWDs in 30 patients (P < 0.001). Hyperventilation (HV) was associated with a higher occurrence of GSWDs in 37 patients (P =0.01). Female sex 7 (P = 0.02), provoked GSWDs 3 (P = 0.03), NREM sleep 8 (P = 0.04), prolonged EEG record 3 (P = 0.02), clinical events during recording 5 (P ≤ 0.01), diagnosis of genetic 05 (P = 0.03), and immune-mediated epilepsies 2 (P = 0.001) were associated with the provocation of ictal EAs; however, in multiple logistic regression analysis, no statistically significant association of these variables (P ≥ 0.05 each) was noted. CONCLUSION: The provocation of EAs in rEEG with different APs varies according to circumstances, including seizure types, epilepsy etiology, and the type of AP applied. These clinical and procedural parameters affect the diagnostic yield of rEEG and need careful consideration during rEEG recordings. APs adopted during rEEG recording can induce FSWDs, FSWDBS, and GSWDs in the form of either interictal or ictal EAs in various etiologies of epilepsy. Ictal EAs may appear in the form of GSWDs, during NREM sleep, in prolonged EEG records; however, their independent association needs to be evaluated in larger sample studies. Further, prospective cohort studies with adequate sample sizes are warranted.
Résumé Contexte:Des procédures d'activation (AP) sont adoptées lors d'une électroencéphalographie de routine (rEEG) pour provoquer des anomalies épileptiformes (EA) intercritiques. Cette étude visait à observer les inter-critiques et critiques (EA) de différents modèles EEG, provoqués par divers PA.Méthodes:Cette étude transversale a été réalisée dans le département de neurologie de l'hôpital universitaire King Fahd de Khobar, en Arabie Saoudite. Les EEG et les dossiers médicaux des patients qui se sont présentés pour des enregistrements EEG ont été initialement examinés, puis 146 EEG avec des EA provoqués lors de l'utilisation des AP ont été inclus pour analyse.Résultats:Parmi tous les EEG avec des AE provoqués, le sommeil à mouvements oculaires non rapides (NREM) a provoqué des EA chez 93 (63,7 %) patients avec les schémas suivants : décharges d'ondes de pointe focales (FSWD) 45 ( P = 0,01), onde de pointe focale avec bilatéral synchronisation (FSWBS) 27 ( P = 0,03) et décharges d'ondes de pointe généralisées (GSWD) 46 ( P = 0,01). La stimulation photique intermittente (IPS) a provoqué de manière plus significative des FSWD chez 07 patients ( P = 0,01) et des GSWD chez 30 patients ( P = < 0,001) 7 patients ( P = 0,01) et des GSWD chez 30 patients ( P < 0,001). L'hyperventilation (HV) était associée à une fréquence plus élevée de GSWD chez 37 patients ( P = 0,01). Sexe féminin 07 ( P = 0,02), GSWD provoqués 03 ( P = 0,03), sommeil NREM 08 ( P = 0,04), enregistrement EEG prolongé 03 ( P = 0,02), événements cliniques lors de l'enregistrement 05 ( P = < 0,01), diagnostic des épilepsies génétiques 05 ( P = 0,03) et des épilepsies à médiation immunitaire 02 ( P = 0,001) étaient associées à la provocation d'EA critiques, cependant, dans l'analyse de régression logistique multiple, aucune association statistiquement significative de ces variables ( P = > 0,05 chacune) était noté.Conclusion:La provocation d'EA dans l'EEGr avec différents AP varie en fonction des circonstances, notamment des types de crises, de l'étiologie de l'épilepsie et du type d'AP appliqué. Ces paramètres cliniques et procéduraux affectent le rendement diagnostique du rEEG et doivent être soigneusement pris en compte lors des enregistrements rEEG. Les AP adoptés lors de l'enregistrement rEEG peuvent induire des FSWD, des FSWBS et des GSWD sous la forme d'EA inter-critiques ou critiques dans diverses étiologies de l'épilepsie. Les EA critiques peuvent apparaître sous forme de GSWD, pendant le sommeil NREM, dans les enregistrements EEG prolongés; cependant, leur association indépendante doit être évaluée dans des études sur un échantillon plus large. De plus, des études de cohortes prospectives avec des échantillons de taille adéquate sont justifiées.
Assuntos
Eletroencefalografia , Epilepsia , Convulsões , Humanos , Eletroencefalografia/métodos , Feminino , Masculino , Estudos Transversais , Adulto , Epilepsia/fisiopatologia , Epilepsia/diagnóstico , Arábia Saudita , Pessoa de Meia-Idade , Convulsões/diagnóstico , Convulsões/fisiopatologia , Adolescente , Adulto JovemRESUMO
Functional MRI (fMRI) is gaining importance in the preoperative assessment of language for presurgical planning. However, inconsistencies with the Wada test might arise. This current case report describes a very rare case of an epileptic patient who exhibited bilateral distribution (right > left) in the inferior frontal gyrus (laterality index [LI] = -0.433) and completely right dominance in the superior temporal gyrus (LI = -1). However, the Wada test revealed a dissociation: his motor speech was located in the left hemisphere, while he could understand vocal instructions with his right hemisphere. A clinical implication is that the LIs obtained by fMRI should be cautiously used to determine Broca's area in atypical patients; for example, even when complete right dominance is found in the temporal cortex in right-handed patients. Theoretically, as the spatially separated functions of motor speech and language comprehension (by the combined results of fMRI and Wada) can be further temporally separated (by the intracarotid amobarbital procedure) in this case report, these findings might provide direct support to Broca's initial conclusions that Broca's area is associated with acquired motor speech impairment, but not language comprehension per se. Moreover, this current finding supports the idea that once produced, motor speech can be independent from language comprehension.
Assuntos
Lateralidade Funcional , Idioma , Imageamento por Ressonância Magnética , Humanos , Imageamento por Ressonância Magnética/métodos , Masculino , Área de Broca/diagnóstico por imagem , Área de Broca/fisiopatologia , Adulto , Lobo Temporal/diagnóstico por imagem , Lobo Temporal/fisiopatologia , Mapeamento Encefálico/métodos , Epilepsia/diagnóstico por imagem , Epilepsia/cirurgia , Epilepsia/fisiopatologia , Epilepsia/diagnóstico , Fala/fisiologiaRESUMO
Objective.Monotherapy with antiepileptic drugs (AEDs) is the preferred strategy for the initial treatment of epilepsy. However, an inadequate response to the initially prescribed AED is a significant indicator of a poor long-term prognosis, emphasizing the importance of precise prediction of treatment outcomes with the initial AED regimen in patients with epilepsy.Approach. We introduce OxcarNet, an end-to-end neural network framework developed to predict treatment outcomes in patients undergoing oxcarbazepine monotherapy. The proposed predictive model adopts a Sinc Module in its initial layers for adaptive identification of discriminative frequency bands. The derived feature maps are then processed through a Spatial Module, which characterizes the scalp distribution patterns of the electroencephalography (EEG) signals. Subsequently, these features are fed into an attention-enhanced Temporal Module to capture temporal dynamics and discrepancies. A channel module with an attention mechanism is employed to reveal inter-channel dependencies within the output of the Temporal Module, ultimately achieving response prediction. OxcarNet was rigorously evaluated using a proprietary dataset of retrospectively collected EEG data from newly diagnosed epilepsy patients at Nanjing Drum Tower Hospital. This dataset included patients who underwent long-term EEG monitoring in a clinical inpatient setting.Main results.OxcarNet demonstrated exceptional accuracy in predicting treatment outcomes for patients undergoing Oxcarbazepine monotherapy. In the ten-fold cross-validation, the model achieved an accuracy of 97.27%, and in the validation involving unseen patient data, it maintained an accuracy of 89.17%, outperforming six conventional machine learning methods and three generic neural decoding networks. These findings underscore the model's effectiveness in accurately predicting the treatment responses in patients with newly diagnosed epilepsy. The analysis of features extracted by the Sinc filters revealed a predominant concentration of predictive frequencies in the high-frequency range of the gamma band.Significance. The findings of our study offer substantial support and new insights into tailoring early AED selection, enhancing the prediction accuracy for the responses of AEDs.
Assuntos
Anticonvulsivantes , Eletroencefalografia , Epilepsia , Redes Neurais de Computação , Oxcarbazepina , Humanos , Oxcarbazepina/administração & dosagem , Epilepsia/tratamento farmacológico , Epilepsia/diagnóstico , Epilepsia/fisiopatologia , Anticonvulsivantes/administração & dosagem , Anticonvulsivantes/uso terapêutico , Eletroencefalografia/métodos , Eletroencefalografia/efeitos dos fármacos , Masculino , Feminino , Resultado do Tratamento , Adulto , Estudos Retrospectivos , Pessoa de Meia-Idade , Adulto Jovem , Atenção/efeitos dos fármacos , Atenção/fisiologiaAssuntos
Epilepsia , Magnetoencefalografia , Humanos , Magnetoencefalografia/métodos , Epilepsia/fisiopatologia , Epilepsia/diagnóstico , Masculino , Feminino , Estudo de Prova de Conceito , Rede Nervosa/fisiopatologia , Rede Nervosa/diagnóstico por imagem , Adulto , Encéfalo/fisiopatologia , Encéfalo/diagnóstico por imagem , Pessoa de Meia-Idade , Eletroencefalografia/métodosRESUMO
Thrombospondins (TSPs) are astrocyte-secreted extracellular matrix proteins that play key roles as regulators of synaptogenesis in the central nervous system. We previously showed that TSP1/2 are upregulated in the partial neocortical isolation model ("undercut" or "UC" below) of posttraumatic epileptogenesis and may contribute to abnormal axonal sprouting, aberrant synaptogenesis and epileptiform discharges in the UC cortex. These results led to the hypothesis that posttraumatic epileptogeneis would be reduced in TSP1/2 knockout (TSP1/2 KO) mice. To test the hypothesis, we made UC lesions at P21, and subsequent experiments were conducted 14d later at P35. Ex vivo extracellular single or multi-electrode field potential recordings were obtained from layer V in cortical slices at P35 and in vivo video-EEGs of spontaneous epileptiform bursts were recorded to examine the effect of TSP1/2 deletion on epileptogenesis following cortical injury. Immunohistochemical experiments were performed to assess the effect of TSP1/2 KO + UC on the number of putative excitatory synapses and the expression of TSP4 and HEVIN, other astrocytic proteins known to up-regulate excitatory synapse formation. Unexpectedly, our results showed that, compared with WT + UC mice, TSP1/2 KO + UC mice displayed increased epileptiform activity, as indicated by 1) increased incidence and more rapid propagation of evoked and spontaneous epileptiform discharges in UC neocortical slices; 2) increased occurrence of spontaneous epileptiform discharges in vivo. There was an associated increase in the density of VLUT1/PSD95-IR colocalizations (putative excitatory synapses) and significantly upregulated TSP4- and HEVIN-IR in TSP1/2 KO + UC versus WT + UC mice. Results suggest that TSP1/2 deletion plays a potential epileptogenic role following neocortical injury, associated with compensatory upregulation of TSP4 and HEVIN, which may contribute to the increase in the density of excitatory synapses and resulting neural network hyperexcitability.
Assuntos
Camundongos Knockout , Trombospondina 1 , Trombospondinas , Animais , Trombospondinas/genética , Trombospondinas/metabolismo , Trombospondina 1/genética , Trombospondina 1/metabolismo , Camundongos , Masculino , Camundongos Endogâmicos C57BL , Córtex Cerebral/metabolismo , Córtex Cerebral/fisiopatologia , Epilepsia/genética , Epilepsia/fisiopatologia , Epilepsia/metabolismo , Sinapses/metabolismo , Eletroencefalografia , Neocórtex/metabolismo , Neocórtex/fisiopatologiaRESUMO
Effective communication hinges on a mutual understanding of word meaning in different contexts. We recorded brain activity using electrocorticography during spontaneous, face-to-face conversations in five pairs of epilepsy patients. We developed a model-based coupling framework that aligns brain activity in both speaker and listener to a shared embedding space from a large language model (LLM). The context-sensitive LLM embeddings allow us to track the exchange of linguistic information, word by word, from one brain to another in natural conversations. Linguistic content emerges in the speaker's brain before word articulation and rapidly re-emerges in the listener's brain after word articulation. The contextual embeddings better capture word-by-word neural alignment between speaker and listener than syntactic and articulatory models. Our findings indicate that the contextual embeddings learned by LLMs can serve as an explicit numerical model of the shared, context-rich meaning space humans use to communicate their thoughts to one another.