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Computational Models In Epilepsy
Computational models in epilepsy mainly focus on describing an electrophysiological manifestation associated with epilepsy called seizures. For this purpose, computational neurosciences use differential equations to reproduce the temporal evolution of the signals recorded experimentally. A book published in 2008, ''Computational Neuroscience in Epilepsy''. summarizes different works done up to this time. The goals of using its models are diverse, from prediction to comprehension of underlying mechanisms. The crisis phenomenon (seizure) exists and shares certain dynamical properties across different scales and different organisms. It is possible to distinguish different approaches: the phenomenological models focus on the dynamics observed, generally reduced to few dimension it facilitates the study from the point of view of the theory of dynamical systems and more mechanistic models that explain the biophysical interactions underlying seizures. It is also possible to use these appr ...
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Electrophysiology
Electrophysiology (from [see the Electron#Etymology, etymology of "electron"]; ; and ) is the branch of physiology that studies the electrical properties of biological cell (biology), cells and tissues. It involves measurements of voltage changes or electric current or manipulations on a wide variety of scales from single ion channel proteins to whole organs like the heart. In neuroscience, it includes measurements of the electrical activity of neurons, and, in particular, action potential activity. Recordings of large-scale electric signals from the nervous system, such as electroencephalography, may also be referred to as electrophysiological recordings. They are useful for electrodiagnostic medicine, electrodiagnosis and monitoring (medicine), monitoring. Definition and scope Classical electrophysiological techniques Principle and mechanisms Electrophysiology is the branch of physiology that pertains broadly to the flow of ions (ion current) in biological tissues and, in p ...
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Epilepsy
Epilepsy is a group of Non-communicable disease, non-communicable Neurological disorder, neurological disorders characterized by a tendency for recurrent, unprovoked Seizure, seizures. A seizure is a sudden burst of abnormal electrical activity in the brain that can cause a variety of symptoms, ranging from brief lapses of awareness or muscle jerks to prolonged convulsions. These episodes can result in physical injuries, either directly, such as broken bones, or through causing accidents. The diagnosis of epilepsy typically requires at least two unprovoked seizures occurring more than 24 hours apart. In some cases, however, it may be diagnosed after a single unprovoked seizure if clinical evidence suggests a high risk of recurrence. Isolated seizures that occur without recurrence risk or are provoked by identifiable causes are not considered indicative of epilepsy. The underlying cause is often unknown, but epilepsy can result from brain injury, stroke, infections, Brain tumor, ...
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Seizure
A seizure is a sudden, brief disruption of brain activity caused by abnormal, excessive, or synchronous neuronal firing. Depending on the regions of the brain involved, seizures can lead to changes in movement, sensation, behavior, awareness, or consciousness. Symptoms vary widely. Some seizures involve subtle changes, such as brief lapses in attention or awareness (as seen in absence seizures), while others cause generalized convulsions with loss of consciousness ( tonic–clonic seizures). Most seizures last less than two minutes and are followed by a postictal period of confusion, fatigue, or other symptoms. A seizure lasting longer than five minutes is a medical emergency known as status epilepticus. Seizures are classified as provoked, when triggered by a known cause such as fever, head trauma, or metabolic imbalance, or unprovoked, when no immediate trigger is identified. Recurrent unprovoked seizures define the neurological condition epilepsy. Clinical features Seizur ...
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Computational Neuroscience
Computational neuroscience (also known as theoretical neuroscience or mathematical neuroscience) is a branch of  neuroscience which employs mathematics, computer science, theoretical analysis and abstractions of the brain to understand the principles that govern the development, structure, physiology and cognitive abilities of the nervous system. Computational neuroscience employs computational simulations to validate and solve mathematical models, and so can be seen as a sub-field of theoretical neuroscience; however, the two fields are often synonymous. The term mathematical neuroscience is also used sometimes, to stress the quantitative nature of the field. Computational neuroscience focuses on the description of biologically plausible neurons (and neural systems) and their physiology and dynamics, and it is therefore not directly concerned with biologically unrealistic models used in connectionism, control theory, cybernetics, quantitative psychology, machine le ...
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Dynamical Systems Theory
Dynamical systems theory is an area of mathematics used to describe the behavior of complex systems, complex dynamical systems, usually by employing differential equations by nature of the ergodic theory, ergodicity of dynamic systems. When differential equations are employed, the theory is called continuous time, ''continuous dynamical systems''. From a physical point of view, continuous dynamical systems is a generalization of classical mechanics, a generalization where the equations of motion are postulated directly and are not constrained to be Euler–Lagrange equations of a Principle of least action, least action principle. When difference equations are employed, the theory is called discrete time, ''discrete dynamical systems''. When the time variable runs over a set that is discrete over some intervals and continuous over other intervals or is any arbitrary time-set such as a Cantor set, one gets dynamic equations on time scales. Some situations may also be modeled by mixed ...
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Large-scale Brain Networks
Large-scale brain networks (also known as intrinsic brain networks) are collections of widespread brain regions showing functional connectivity by statistical analysis of the fMRI BOLD signal or other recording methods such as EEG, PET and MEG. An emerging paradigm in neuroscience is that cognitive tasks are performed not by individual brain regions working in isolation but by networks consisting of several discrete brain regions that are said to be "functionally connected". Functional connectivity networks may be found using algorithms such as cluster analysis, spatial independent component analysis (ICA), seed based, and others. Synchronized brain regions may also be identified using long-range synchronization of the EEG, MEG, or other dynamic brain signals. The set of identified brain areas that are linked together in a large-scale network varies with cognitive function. When the cognitive state is not explicit (i.e., the subject is at "rest"), the large-scale brain network is ...
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Electroencephalography
Electroencephalography (EEG) is a method to record an electrogram of the spontaneous electrical activity of the brain. The biosignal, bio signals detected by EEG have been shown to represent the postsynaptic potentials of pyramidal neurons in the neocortex and allocortex. It is typically non-invasive, with the EEG electrodes placed along the scalp (commonly called "scalp EEG") using the 10–20 system (EEG), International 10–20 system, or variations of it. Electrocorticography, involving surgical placement of electrodes, is sometimes called Electrocorticography, "intracranial EEG". Clinical interpretation of EEG recordings is most often performed by visual inspection of the tracing or quantitative EEG, quantitative EEG analysis. Voltage fluctuations measured by the EEG bioamplifier, bio amplifier and electrodes allow the evaluation of normal Brain activity and meditation, brain activity. As the electrical activity monitored by EEG originates in neurons in the underlying Huma ...
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Computational Biology
Computational biology refers to the use of techniques in computer science, data analysis, mathematical modeling and Computer simulation, computational simulations to understand biological systems and relationships. An intersection of computer science, biology, and data science, the field also has foundations in applied mathematics, molecular biology, cell biology, chemistry, and genetics. History Bioinformatics, the analysis of informatics processes in biological systems, began in the early 1970s. At this time, research in artificial intelligence was using network models of the human brain in order to generate new algorithms. This use of biological data pushed biological researchers to use computers to evaluate and compare large data sets in their own field. By 1982, researchers shared information via Punched card, punch cards. The amount of data grew exponentially by the end of the 1980s, requiring new computational methods for quickly interpreting relevant information. Per ...
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