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Epilepsy is the third most commonly diagnosed neurological disorder. For drug-resistant patients, epilepsy surgery is the only option. The outcome of epilepsy surgery largely depends on an accurate mapping of epileptogenic zone. In clinic, this is done with subdural electrode array to monitor the Electrocorticography (ECoG) with a disappointing low spatial resolution of ∼ 1cm. As a result, the cure...
Sudden unexpected death in epilepsy (SUDEP) is the leading cause of epilepsy-related mortality, but its genetic etiology is largely unknown and likely complex involving multiple genes. The Kcna1 gene encodes Kv1.1 potassium channels that act to dampen neuronal excitability whereas the Scn2a gene encodes Nav1.2 sodium channels important for action potential conduction. We tested the hypothesis that...
Sudden unexpected death in epilepsy (SUDEP) is the leading cause of epilepsy-related death in young and otherwise healthy patients with epilepsy, and sudden unexpected death is at least 20 times more common in epilepsy patients than the general population. Cardiac arrhythmias, respiratory abnormalities, or a combination of both have been postulated in the causation of SUDEP. Voltage-gated Kv1.1 channels,...
While originally astrocytes have been thought to only act as support to neurons, recent studies have implicated them in multiple active roles, including the ability to moderate or alter neuronal firing patterns and to possibly be involved in both the prevention and propagation of epileptic seizures. In this study we propose a new model to incorporate pyramidal cells and interneurons (a common neural...
The paper is the minireview of the main data concerning the functional properties of rodent audiogenic epilepsy (AE) in rats of inbred strain Krushinsky-Molodkina -- KM (Moscow, Russia). These data demonstrate that the genetically determined abnormal functions of CNS (presumably in brainstem neural circuits) which are the cause of AE could be responsible not only for the clonic and tonic seizures...
Here we report first results of numerical methods for modeling the dynamic structure and evolution of epileptic seizure activity in an intracranial subdural electrode recording from a patient with partial refractory epilepsy. A 16-min dataset containing two seizures was decomposed using up to five competing adaptive mixture independent component analysis (AMICA) models. Multiple models modeled early...
The gold standard for the localization of epileptic activities in the cerebral cortex is intracranial electrocorticography (ECoG) electrodes placed directly on the brain surface. However, it has limitations in being able to localize deep brain epileptic sources. As a means to improve the localization of epileptic activities from these subdural electrical recordings, we developed a simple source monitoring...
This work presents a novel algorithmic method based on an ngram approach and applies it ECoG and deep brain neural data for analysis of epileptic seizures. This is part of a project (WiNAM) to design an analysis framework suitable for analysing brain dynamical changes. By first exploring the ngram model and its traditional use we describe how to apply it to biological data for pattern recognition...
Approximately 1% of people in the world have epilepsy and 25% of epilepsy patients cannot be treated sufficiently by any available therapy. An automatic seizure detection system can reduce the time taken to review the EEG data by the neurologist for epilepsy diagnosis. In this paper, various EEG features integrated with the linear or non-linear classifiers are evaluated for seizure detection. For...
Epilepsy is one of the most common diseases related to the disfunctioning of the central nervous system. For the patients whose drug therapy turns out to be ineffective, it is a common method to identify the locations of sources that trigger the seizure in the brain tissue and resect them through surgical means for treatment. The success of the surgical operation depends on the accurate localization...
Our objective is to analyze EEG signals recorded with depth electrodes during seizures in patients with drug-resistant epilepsy. Usually, different phases are observed during the seizure process, including a fast onset activity (FOA). We aim to determine how cerebral structures get involved during this FOA, in particular whether some structure can “drive” some other structures. This paper focuses...
Model and truth: By thinking in terms of and with the help of models, we consciously give up a language, which implies that we might be the only ones, who are able to know the only truth. We do not say that ldquothese are the facts, and only the facts matterrdquo. A more appropriate language says: ldquoBy assuming this and that, and adopting the set of these rules, we may imply this and thatrdquo...
During epilepsy seizure Electrocorticogram (ECoG) may change dramatically from a nearly chaotic signal (basal state) into a highly synchronized signal during a seizure, characterized by high amplitude and low frequency, and suddenly go back to the basal sate, making hard to identify them from time series. The epileptic seizure shows some stages as it is evolving, the here studied are: basal, preictal,...
Recent physiological evidence has suggested that initiation of partial epileptic seizures may be due to a desynchronization rather than hypersynchronization of neuronal communication at a seizure focus. This hypothesis was tested using a computational model of the hippocampal slice possessing a physiologically-consistent network structure and behavior. When desynchronization was simulated using either...
High-resolution time-frequency analyses of ictal EEG allow for identification and characterization of ictal patterns. These patterns reflect alterations in the brain network synchrony. It is not clear why seizures undergo these dynamical changes and what mechanisms contribute to or cause these changes. In this work we use neural modeling studies to address these issues. We investigate the role of...
We examined the effects of both intrinsic neuronal membrane properties and network parameters on oscillatory activity in a model of neocortex. A scalable network model with six different cell types was built with the pGENESIS neural simulator. The neocortical network consisted of two types of pyramidal cells and four types of inhibitory interneurons. All cell types contained both fast sodium and delayed...
A system theoretic computational approach has been recently proposed as a generalization of probabilistic networks for modeling complex systems. The computational approach, fuzzy measure-theoretic quantum approximation of an abstract system (FMQAS), generates a system measure between each pair of system objects as a relative measure of association incorporating, through a hierarchical iterative procedure,...
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