[Clinicopathological characteristics of gangliogliomas with anaplastic morphology].

Objective: To investigate the clinical, radiological, and pathological features of anaplastic gangliogliomas (AGGs) and to determine whether these tumors represent a distinct entity. Methods: Consecutive 667 cases of ganglioglioma (GG) diagnosed at the Xuanwu Hospital, Capital Medical University, Beijing, China between January 2015 and July 2023 were screened. Among these cases, 9 pathologically confirmed AGG cases were identified. Their clinical, radiological, treatment, and outcome data were analyzed retrospectively. Most of the tumor samples were subject to next-generation sequencing, while a subset of them were subject to DNA methylation profiling. Results: Among the 9 patients, there were five males and four females, with a median age of 8 years. Epileptic seizures (5/9) were the most frequently presented symptom. Radiological examinations showed three types of radiological manifestations: four cases showed abnormal MRI signals with no significant mass effects and mild enhancement; two cases demonstrated a mixed solid-cystic density lesion with peritumoral edema, which showed significant heterogeneous enhancement and obvious mass effects, and one case displayed cystic cavity formation with nodules on MRI, which showed evident enhancements. All cases exhibited mutations that were predicted to activate the MAP kinase signaling pathway, including seven with BRAF p.V600E mutation and two with NF1 mutation. Five AGGs with mutations involving the MAP kinase signaling pathway also had concurrent mutations, including three with CDKN2A homozygous deletion, one with a TERT promoter mutation, one with a H3F3A mutation, and one with a PTEN mutation. Conclusions: AGG exhibits a distinct spectrum of pathology, genetic mutations and clinical behaviors, differing from GG. Given these characteristics suggest that AGG may be a distinct tumor type, further expansion of the case series is needed. Therefore, a comprehensive integration of clinical, histological, and molecular analyses is required to correctly diagnose AGG. It will also help guide treatments and prognostication.

Automatic detection of epilepsy from EEGs using a temporal convolutional network with a self-attention layer.

BACKGROUND: Over 60% of epilepsy patients globally are children, whose early diagnosis and treatment are critical for their development and can substantially reduce the disease's burden on both families and society. Numerous algorithms for automated epilepsy detection from EEGs have been proposed. Yet, the occurrence of epileptic seizures during an EEG exam cannot always be guaranteed in clinical practice. Models that exclusively use seizure EEGs for detection risk artificially enhanced performance metrics. Therefore, there is a pressing need for a universally applicable model that can perform automatic epilepsy detection in a variety of complex real-world scenarios. METHOD: To address this problem, we have devised a novel technique employing a temporal convolutional neural network with self-attention (TCN-SA). Our model comprises two primary components: a TCN for extracting time-variant features from EEG signals, followed by a self-attention (SA) layer that assigns importance to these features. By focusing on key features, our model achieves heightened classification accuracy for epilepsy detection. RESULTS: The efficacy of our model was validated on a pediatric epilepsy dataset we collected and on the Bonn dataset, attaining accuracies of 95.50% on our dataset, and 97.37% (A v. E), and 93.50% (B vs E), respectively. When compared with other deep learning architectures (temporal convolutional neural network, self-attention network, and standardized convolutional neural network) using the same datasets, our TCN-SA model demonstrated superior performance in the automated detection of epilepsy. CONCLUSION: The proven effectiveness of the TCN-SA approach substantiates its potential as a valuable tool for the automated detection of epilepsy, offering significant benefits in diverse and complex real-world clinical settings.

Therapeutic Drug Monitoring of Levetiracetam in Different Trimesters of Pregnant Women with Epilepsy in a Tertiary Care Center: A Prospective Study.

BACKGROUND: Levetiracetam is the most commonly used antiepileptic drug in pregnant women due to its low teratogenic risk profile, favorable pharmacokinetic characteristics, and safety profile. Serum levels of levetiracetam vary in epilepsy during pregnancy. Therefore, the aim of the study was to evaluate the serum levels of levetiracetam during different trimesters of pregnancy by using therapeutic drug monitoring (TDM). MATERIALS AND METHODS: This was a single-center, prospective study. Pregnant women with epilepsy on levetiracetam were enrolled after getting written informed consent from them. Serum trough levels of levetiracetam were estimated at all trimesters by high-performance liquid chromatography (HPLC). RESULTS: The study included 16 participants with mean ± standard deviation (SD) age of 27.75 ± 4 years. There were nine (56.2%) participants with generalized seizure disorder and seven (43.8%) participants of focal seizure disorder. Among 16 patients, 10 (62.5%) participants were on levetiracetam alone and six (37.5%) participants were on levetiracetam combined with other antiepileptic drugs. In a total of 48 trough samples, 45 sample concentrations were below the therapeutic range of 12-46 mg/l and three sample concentrations were within the therapeutic range. There was a statistically significant difference in the concentration-dose ratio (CDR) of levetiracetam between the third and first trimesters (P-value 0.018). CONCLUSION: There was a statistically significant difference in serum levetiracetam concentration between the third and first trimesters. A well-conducted, intensive pharmacokinetic sampling study in PWWE with a control group is needed in future to evaluate the whole pharmacokinetic profile of levetiracetam and to correlate the clinical outcome.

Spectrum of NMDA Receptor Variants in Neurodevelopmental Disorders and Epilepsy.

N-methyl-D-aspartate receptors (NMDAR) are ligand-gated ion channels mediating excitatory neurotransmission and are important for normal brain development, cognitive abilities, and motor functions. Pathogenic variants in the Glutamate receptor Ionotropic N-methyl-D-aspartate (GRIN) genes (GRIN1, GRIN2A-D) encoding NMDAR subunits have been associated with a wide spectrum of neurodevelopmental disorders and epilepsies ranging from treatable focal epilepsies to devastating early-onset developmental and epileptic encephalopathies. Genetic variants in NMDA receptor genes can cause a range of complex alterations to receptor properties resulting in various degrees of loss-of-function, gain-of-function, or mixtures thereof. Understanding how genetic variants affect the function of the receptors, therefore, represents an important first step in the ongoing development towards targeted therapies. Currently, targeted treatment options for GRIN-related diseases are limited. However, treatment with memantine has been reported to significantly reduce seizure frequency in a few individuals with developmental and epileptic encephalopathies harboring de novo gain-of-function GRIN2A missense variants, and supplementary treatment with L-serine has been associated with improved motor and cognitive performance as well as reduced seizure frequency in patients with GRIN2B loss-of-function missense variants as well as GRIN2A and GRIN2B null variants.

A multiscale symbolic approach to decoding delta and ripple oscillation bands as biomarkers for epileptiform discharges.

We use a multiscale symbolic approach to study the complex dynamics of temporal lobe refractory epilepsy employing high-resolution intracranial electroencephalogram (iEEG). We consider the basal and preictal phases and meticulously analyze the dynamics across frequency bands, focusing on high-frequency oscillations up to 240 Hz. Our results reveal significant periodicities and critical time scales within neural dynamics across frequency bands. By bandpass filtering neural signals into delta, theta, alpha, beta, gamma, and ripple high-frequency bands (HFO), each associated with specific neural processes, we examine the distinct nonlinear dynamics. Our method introduces a reliable approach to pinpoint intrinsic time lag scales τ within frequency bands of the basal and preictal signals, which are crucial for the study of refractory epilepsy. Using metrics such as permutation entropy (H), Fisher information (F), and complexity (C), we explore nonlinear patterns within iEEG signals. We reveal the intrinsic τmax that maximize complexity within each frequency band, unveiling the nonlinear subtle patterns of the temporal structures within the basal and preictal signal. Examining the H×F and C×F values allows us to identify differences in the delta band and a band between 200 and 220 Hz (HFO 6) when comparing basal and preictal signals. Differences in Fisher information in the delta and HFO 6 bands before seizures highlight their role in capturing important system dynamics. This offers new perspectives on the intricate relationship between delta oscillations and HFO waves in patients with focal epilepsy, highlighting the importance of these patterns and their potential as biomarkers.

A needle in a haystack? The impact of a targeted epilepsy gene panel in the identification of a treatable but rapidly progressive metabolic epilepsy: CLN2 disease.

BACKGROUND: Neuronal ceroid lipofuscinoses (NCL) are a group of autosomal recessive, inherited, lysosomal, and neurodegenerative diseases that causes progressive dementia, seizures, movement disorders, language delay/regression, progressive visual failure, and early death. Neuronal ceroid lipofuscinosis type 2 (CLN2), caused by biallelic pathogenic variants of the TPP1 gene, is the only NCL with an approved targeted therapy. The laboratory diagnosis of CLN2 is established through highly specific tests, leading to diagnostic delays and eventually hampering the provision of specific treatment for patients with CLN2. Epilepsy is a common and clinically-identifiable feature among NCLs, and seizure onset is the main driver for families to seek medical care. OBJECTIVE: To evaluate the results of the Latin America Epilepsy and Genetics Program, an epilepsy gene panel, as a comprehensive tool for the investigation of CLN2 among other genetic causes of epilepsy. METHODS: A total of 1,284 patients with epilepsy without a specific cause who had at least 1 symptom associated with CLN2 were screened for variants in 160 genes associated with epilepsy or metabolic disorders presenting with epilepsy through an epilepsy gene panel. RESULTS: Variants of the TPP1 gene were identified in 25 individuals (1.9%), 21 of them with 2 variants. The 2 most frequently reported variants were p.Arg208* and p.Asp276Val, and 2 novel variants were detected in the present study: p.Leu308Pro and c.89 + 3G > C Intron 2. CONCLUSION: The results suggest that these genetic panels can be very useful tools to confirm or exclude CLN2 diagnosis and, if confirmed, provide disease-specific treatment for the patients.

ANTECEDENTES: As lipofuscinoses ceroides neuronais (neuronal ceroid lipofuscinoses, NCLs, em inglês) são um grupo de doenças autossômicas recessivas, hereditárias, lisossomais e neurodegenerativas que causam demência progressiva, crises epiléticas, distúrbios de movimento, atraso/regressão da linguagem, deficiência visual progressiva e morte precoce. A lipofuscinose ceroide neuronal tipo 2 (neuronal ceroid lipofuscinosis type 2, CLN2, em inglês), causada por variantes patogênicas bialélicas do gene TPP1, é a única com terapia-alvo aprovada. O diagnóstico laboratorial é realizado por testes específicos, o que leva a atrasos diagnósticos e, consequentemente, prejudica a disponibilização de tratamento. A epilepsia é uma característica comum e clinicamente identificável entre as NCLs, e o início das convulsões é o principal motivo para as famílias buscarem atendimento médico. OBJETIVO: Avaliar os resultados do Programa de Epilepsia e Genética da América Latina, um painel genético, como uma ferramenta abrangente para a investigação de CLN2 entre outras causas genéticas de epilepsia. MéTODOS: Um total de 1.284 pacientes com epilepsia sem uma causa específica e que tinham pelo menos 1 sintoma associado à CLN2 foram rastreados em busca de variantes em 160 genes associados à epilepsia ou a distúrbios metabólicos que apresentam epilepsia, por meio de um painel genético. RESULTADOS: Variantes do gene TPP1 foram identificadas em 25 indivíduos (1,9%), sendo que ; 21 apresentavam duas variantes. As duas variantes mais frequentes foram p.Arg208* e p.Asp276Val, e duas variantes novas foram detectadas neste: p.Leu308Pro e c.89 + 3G > C Intron 2. CONCLUSãO: Os resultados sugerem que os painéis genéticos de epilepsia podem ser uma ferramenta útil para confirmar ou excluir o diagnóstico de CLN2 e, se confirmado, fornecer tratamento específico para os pacientes.

Parvalbumin Interneuron Dysfunction in Neurological Disorders: Focus on Epilepsy and Alzheimer's Disease.

Parvalbumin expressing (PV+) GABAergic interneurons are fast spiking neurons that provide powerful but relatively short-lived inhibition to principal excitatory cells in the brain. They play a vital role in feedforward and feedback synaptic inhibition, preventing run away excitation in neural networks. Hence, their dysfunction can lead to hyperexcitability and increased susceptibility to seizures. PV+ interneurons are also key players in generating gamma oscillations, which are synchronized neural oscillations associated with various cognitive functions. PV+ interneuron are particularly vulnerable to aging and their degeneration has been associated with cognitive decline and memory impairment in dementia and Alzheimer's disease (AD). Overall, dysfunction of PV+ interneurons disrupts the normal excitatory/inhibitory balance within specific neurocircuits in the brain and thus has been linked to a wide range of neurodevelopmental and neuropsychiatric disorders. This review focuses on the role of dysfunctional PV+ inhibitory interneurons in the generation of epileptic seizures and cognitive impairment and their potential as targets in the design of future therapeutic strategies to treat these disorders. Recent research using cutting-edge optogenetic and chemogenetic technologies has demonstrated that they can be selectively manipulated to control seizures and restore the balance of neural activity in the brains of animal models. This suggests that PV+ interneurons could be important targets in developing future treatments for patients with epilepsy and comorbid disorders, such as AD, where seizures and cognitive decline are directly linked to specific PV+ interneuron deficits.

Performance investigation of epilepsy detection from noisy EEG signals using base-2-meta stacking classifier.

Epilepsy is a chronic neurological disease, characterized by spontaneous, unprovoked, recurrent seizures that may lead to long-term disability and premature death. Despite significant efforts made to improve epilepsy detection clinically and pre-clinically, the pervasive presence of noise in EEG signals continues to pose substantial challenges to their effective application. In addition, discriminant features for epilepsy detection have not been investigated yet. The objective of this study is to develop a hybrid model for epilepsy detection from noisy and fragmented EEG signals. We hypothesized that a hybrid model could surpass existing single models in epilepsy detection. Our approach involves manual noise rejection and a novel statistical channel selection technique to detect epilepsy even from noisy EEG signals. Our proposed Base-2-Meta stacking classifier achieved notable accuracy (0.98 ± 0.05), precision (0.98 ± 0.07), recall (0.98 ± 0.05), and F1 score (0.98 ± 0.04) even with noisy 5-s segmented EEG signals. Application of our approach to the specific problem like detection of epilepsy from noisy and fragmented EEG data reveals a performance that is not only superior to others, but also is translationally relevant, highlighting its potential application in a clinic setting, where EEG signals are often noisy or scanty. Our proposed metric DF-A (Discriminant feature-accuracy), for the first time, identified the most discriminant feature with models that give A accuracy or above (A = 95 used in this study). This groundbreaking approach allows for detecting discriminant features and can be used as potential electrographic biomarkers in epilepsy detection research. Moreover, our study introduces innovative insights into the understanding of these features, epilepsy detection, and cross-validation, markedly improving epilepsy detection in ways previously unavailable.

Teratogenesis, Perinatal, and Neurodevelopmental Outcomes After In Utero Exposure to Antiseizure Medication: Practice Guideline From the AAN, AES, and SMFM.

This practice guideline provides updated evidence-based conclusions and recommendations regarding the effects of antiseizure medications (ASMs) and folic acid supplementation on the prevalence of major congenital malformations (MCMs), adverse perinatal outcomes, and neurodevelopmental outcomes in children born to people with epilepsy of childbearing potential (PWECP). A multidisciplinary panel conducted a systematic review and developed practice recommendations following the process outlined in the 2017 edition of the American Academy of Neurology Clinical Practice Guideline Process Manual. The systematic review includes studies through August 2022. Recommendations are supported by structured rationales that integrate evidence from the systematic review, related evidence, principles of care, and inferences from evidence. The following are some of the major recommendations. When treating PWECP, clinicians should recommend ASMs and doses that optimize both seizure control and fetal outcomes should pregnancy occur, at the earliest possible opportunity preconceptionally. Clinicians must minimize the occurrence of convulsive seizures in PWECP during pregnancy to minimize potential risks to the birth parent and to the fetus. Once a PWECP is already pregnant, clinicians should exercise caution in attempting to remove or replace an ASM that is effective in controlling generalized tonic-clonic or focal-to-bilateral tonic-clonic seizures. Clinicians must consider using lamotrigine, levetiracetam, or oxcarbazepine in PWECP when appropriate based on the patient's epilepsy syndrome, likelihood of achieving seizure control, and comorbidities, to minimize the risk of MCMs. Clinicians must avoid the use of valproic acid in PWECP to minimize the risk of MCMs or neural tube defects (NTDs), if clinically feasible. Clinicians should avoid the use of valproic acid or topiramate in PWECP to minimize the risk of offspring being born small for gestational age, if clinically feasible. To reduce the risk of poor neurodevelopmental outcomes, including autism spectrum disorder and lower IQ, in children born to PWECP, clinicians must avoid the use of valproic acid in PWECP, if clinically feasible. Clinicians should prescribe at least 0.4 mg of folic acid supplementation daily preconceptionally and during pregnancy to any PWECP treated with an ASM to decrease the risk of NTDs and possibly improve neurodevelopmental outcomes in the offspring.

Challenging behaviour and epilepsy in patients with intellectual disability: frequency and mutual association.

Comorbid epilepsy and challenging behaviours is quiet common in patients with ID (intellectual disability). This study aims to determine the frequency and mutual association between epilepsy and challenging behaviours. In this cross-sectional analytical study, 252 patients were enrolled through convenient sampling technique. Comorbid epilepsy and CB (challenging behaviour) were seen in 111 (44.6%) and 116 (46.6%) patients, respectively. Epilepsy and severity of intellectual disability (ID) are statistically and significantly associated with challenging behaviour. This study concluded that comorbid epilepsy is more common among people with ID as compared to the general population. The clinical variables, i.e. comorbid epilepsy and severity of ID have statistically significant association with the CB.

[Risk of epilepsy after a first epileptic seizure with unknown etiology in elderly patients]. / Riesgo de epilepsia tras una primera crisis epiléptica de etiología desconocida en pacientes de edad avanzada.

AIM: Patients whose epilepsy begins with seizures with unknown etiology in old age have been studied to a limited extent. The aim is to clinically characterise these patients, and predict their risk of developing epilepsy in the long term. MATERIALS AND METHODS: This is a retrospective observational study of patients over 55 years old experiencing a first epileptic seizure with unknown etiology. The data were collected from their clinical history, including electroencephalogram (EEG) and brain magnetic resonance imaging (MRI) results. RESULTS: Eighty-seven patients (58.6% male; 71.5 ± 8.1 years) were included. The mean follow-up was 7.3 ± 4.9 years. The most common vascular risk factor was arterial hypertension (77%; n = 67). Focal seizures with altered consciousness were the most frequent type of seizure (44.8%; n = 39), followed by focal seizures evolving to bilateral tonic-clonic seizures (39.1%; n = 34). Brain MRI showed cortical atrophy (50%; n = 42) and signs of small-vessel vascular disease (SVVD) (67.8%; n = 57). Interictal epileptiform EEG abnormalities were observed in 43.7% (n = 38) of the patients, mostly with temporal localisations (94.7%; n = 36). 44.8% (n = 39) had mild cognitive impairment at baseline. Recurrence of seizures, which was observed in 49 patients (56.1%), occurred after a median of 12 months (interquartile range: 4.4-25.9). Finally, 71 patients (81.6%) developed epilepsy. CONCLUSION: The risk of epilepsy in the long term following a single seizure of unknown etiology in elderly patients is greater than 80%. Arterial hypertension and mild cognitive impairment at baseline are the most common clinical features. Cortical atrophy and the presence of SVVD are frequent in MRI, and routine EEGs do not usually show epileptiform alterations.

TITLE: Riesgo de epilepsia tras una primera crisis epiléptica de etiología desconocida en pacientes de edad avanzada.Objetivo. Los pacientes que comienzan con crisis de origen desconocido en la edad avanzada no están bien estudiados. El objetivo es caracterizar clínicamente a estos pacientes y predecir el riesgo de desarrollar epilepsia a largo plazo. Materiales y métodos. Es un estudio observacional retrospectivo en pacientes mayores de 55 años con una primera crisis epiléptica de causa desconocida. Se recogieron los datos desde la historia clínica, incluyendo electroencefalograma (EEG) y resonancia magnética (RM) cerebral. Resultados. Se incluyó a 87 pacientes (58,6% varones; 71,5 ± 8,1 años). El seguimiento medio fue de 7,3 ± 4,9 años. El factor de riesgo vascular más frecuente fue la hipertensión arterial (77%; n = 67). Las crisis focales con alteración de la conciencia fueron el tipo de crisis más frecuente (44,8%; n = 39), seguidas de las crisis focales con evolución a bilaterales tonicoclónicas (39,1%; n = 34). La RM cerebral mostró atrofia cortical (50%; n = 42) y signos de enfermedad vascular de pequeño vaso (EVPV) (67,8%; n = 57). Se observaron anomalías epileptiformes intercríticas en el EEG en un 43,7% (n = 38) de los pacientes, mayoritariamente con localización temporal (94,7%; n = 36). Hasta un 44,8% (n = 39) presentaba deterioro cognitivo leve basalmente. La recurrencia de crisis, observada en 49 pacientes (56,1%), sucedió con una mediana de 12 meses (rango intercuartílico: 4,4-25,9). Finalmente, 71 pacientes (81,6%) desarrollaron epilepsia. Conclusión. El riesgo de epilepsia a largo plazo tras una crisis única de etiología desconocida en pacientes de edad avanzada es superior al 80%. La hipertensión arterial y el deterioro cognitivo leve en el inicio son las características clínicas más frecuentes. En la RM, la atrofia cortical y la presencia de EVPV son frecuentes, y los EEG de rutina no suelen mostrar alteraciones epileptiformes.

Contribution of microglia to the epileptiform activity that results from neonatal hypoxia.

Microglia are described as the immune cells of the brain, their immune properties have been extensively studied since first described, however, their neural functions have only been explored over the last decade. Microglia have an important role in maintaining homeostasis in the central nervous system by surveying their surroundings to detect pathogens or damage cells. While these are the classical functions described for microglia, more recently their neural functions have been defined; they are critical to the maturation of neurons during embryonic and postnatal development, phagocytic microglia remove excess synapses during development, a process called synaptic pruning, which is important to overall neural maturation. Furthermore, microglia can respond to neuronal activity and, together with astrocytes, can regulate neural activity, contributing to the equilibrium between excitation and inhibition through a feedback loop. Hypoxia at birth is a serious neurological condition that disrupts normal brain function resulting in seizures and epilepsy later in life. Evidence has shown that microglia may contribute to this hyperexcitability after neonatal hypoxia. This review will summarize the existing data on the role of microglia in the pathogenesis of neonatal hypoxia and the plausible mechanisms that contribute to the development of hyperexcitability after hypoxia in neonates. This article is part of the Special Issue on "Microglia".

Prevalence of abnormal electrocardiographic findings and associated factors among patients with epilepsy at Jimma Medical Center, Ethiopia; Hospital-based cross-sectional study.

BACKGROUND: A person with epilepsy experiences recurrent seizures as a result of a persistent underlying disorder. About 50 million people globally are impacted by it, with 4 million of those being in Sub-Saharan Africa. One of the most frequent comorbidities that raise the mortality and morbidity rates of epileptic patients is abnormal Electrocardiographic (ECG) findings. Thus, the purpose of this study is to evaluate the prevalence of abnormal ECG findings in epileptic patients that might lead to increased risk of sudden cardiac death. METHODOLOGY: A hospital based cross-sectional study was at Jimma Medical Center of Ethiopia on epileptic patients who were on follow-up at neurologic clinics during the data collection period. The malignant ECG characteristics and was identified using the ECG abnormality tool. To facilitate analysis, the gathered data was imported into Epidata version 3.1 and exported to the SPSS version 26. The factors of abnormal ECG and sudden death risk were examined using bivariate logistic regression. RESULTS: The study comprised 190 epileptic patients, with a mean age of 32 years. There were more men than women, making up 60.2%. A 43.2% (n = 80) frequency of ECG abnormalities was identified. According to the study, early repolarization abnormalities were the most common ECG abnormalities and increased with male sex and the length of time a person had seizures (AOR) of 4.751 and 95% CI (.273,.933), p = 0.029, compared to their female counterparts. CONCLUSION: The frequency of malignant ECG alterations in epileptic patients on follow-up at Jimma Medical Center in Ethiopia is described in the study. According to the study, there were significant ECG alterations in epileptic individuals. Male gender and longer duration of epilepsy raise the risk of abnormal ECG findings that could result in sudden cardiac death.

Modeling a neurological disorder as the result of an operator acting on the brain: A first sketch based on network channel modeling.

The brain is a complex network, and diseases can alter its structures and connections between regions. Therefore, we can try to formalize the action of diseases by using operators acting on the brain network. Here, we propose a conceptual model of the brain, seen as a multilayer network, whose intra-lobe interactions are formalized as the diagonal blocks of an adjacency matrix. We propose a general and abstract definition of disease as an operator altering the weights of the connections between neural agglomerates, that is, the elements of the brain matrix. As models, we consider examples from three neurological disorders: epilepsy, Alzheimer-Perusini's disease, and schizophrenia. The alteration of neural connections can be seen as alterations of communication pathways, and thus, they can be described with a new channel model.