SeizureAn epileptic seizure, informally known as a seizure, is a period of symptoms due to abnormally excessive or synchronous neuronal activity in the brain. Outward effects vary from uncontrolled shaking movements involving much of the body with loss of consciousness (tonic-clonic seizure), to shaking movements involving only part of the body with variable levels of consciousness (focal seizure), to a subtle momentary loss of awareness (absence seizure). Most of the time these episodes last less than two minutes and it takes some time to return to normal.
Computational complexityIn computer science, the computational complexity or simply complexity of an algorithm is the amount of resources required to run it. Particular focus is given to computation time (generally measured by the number of needed elementary operations) and memory storage requirements. The complexity of a problem is the complexity of the best algorithms that allow solving the problem. The study of the complexity of explicitly given algorithms is called analysis of algorithms, while the study of the complexity of problems is called computational complexity theory.
Absence seizureAbsence seizures are one of several kinds of generalized seizures. These seizures are sometimes referred to as petit mal seizures (from the French for "little illness", a term dated in the late 18th century). Absence seizures are characterized by a brief loss and return of consciousness, generally not followed by a period of lethargy (i.e. without a notable postictal state). Absence seizures are most common in children. They affect both sides of the brain. Absence seizures affect between 0.7 and 4.
Complexity classIn computational complexity theory, a complexity class is a set of computational problems "of related resource-based complexity". The two most commonly analyzed resources are time and memory. In general, a complexity class is defined in terms of a type of computational problem, a model of computation, and a bounded resource like time or memory. In particular, most complexity classes consist of decision problems that are solvable with a Turing machine, and are differentiated by their time or space (memory) requirements.
ElectroencephalographyElectroencephalography (EEG) is a method to record an electrogram of the spontaneous electrical activity of the brain. The biosignals 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 International 10–20 system, or variations of it. Electrocorticography, involving surgical placement of electrodes, is sometimes called "intracranial EEG".
EpilepsyEpilepsy is a group of non-communicable neurological disorders characterized by recurrent epileptic seizures. An epileptic seizure is the clinical manifestation of an abnormal, excessive, purposeless and synchronized electrical discharge in the brain cells called neurons. The occurrence of two or more unprovoked seizures defines epilepsy. The occurrence of just one seizure may warrant the definition (set out by the International League Against Epilepsy) in a more clinical usage where recurrence may be able to be prejudged.
Computational complexity theoryIn theoretical computer science and mathematics, computational complexity theory focuses on classifying computational problems according to their resource usage, and relating these classes to each other. A computational problem is a task solved by a computer. A computation problem is solvable by mechanical application of mathematical steps, such as an algorithm. A problem is regarded as inherently difficult if its solution requires significant resources, whatever the algorithm used.
Quantum complexity theoryQuantum complexity theory is the subfield of computational complexity theory that deals with complexity classes defined using quantum computers, a computational model based on quantum mechanics. It studies the hardness of computational problems in relation to these complexity classes, as well as the relationship between quantum complexity classes and classical (i.e., non-quantum) complexity classes. Two important quantum complexity classes are BQP and QMA.
Generalized tonic–clonic seizureA generalized tonic–clonic seizure, commonly known as a grand mal seizure or GTCS, is a type of generalized seizure that produces bilateral, convulsive tonic and clonic muscle contractions. Tonic–clonic seizures are the seizure type most commonly associated with epilepsy and seizures in general and the most common seizure associated with metabolic imbalances. It is a misconception that they are the sole type of seizure, as they are the main seizure type in approximately 10% of those with epilepsy.
Febrile seizureA febrile seizure, also known as a fever fit or febrile convulsion, is a seizure associated with a high body temperature but without any serious underlying health issue. They most commonly occur in children between the ages of 6 months and 5 years. Most seizures are less than five minutes in duration, and the child is completely back to normal within an hour of the event. There are two types: simple febrile seizures and complex febrile seizures.
Parameterized complexityIn computer science, parameterized complexity is a branch of computational complexity theory that focuses on classifying computational problems according to their inherent difficulty with respect to multiple parameters of the input or output. The complexity of a problem is then measured as a function of those parameters. This allows the classification of NP-hard problems on a finer scale than in the classical setting, where the complexity of a problem is only measured as a function of the number of bits in the input.
Psychogenic non-epileptic seizurePsychogenic non-epileptic seizures (PNES), which have been more recently classified as functional seizures, are events resembling an epileptic seizure, but without the characteristic electrical discharges associated with epilepsy. PNES fall under the category of disorders known as functional neurological disorders (FND), also known as conversion disorders. These are typically treated by psychologists or psychiatrists. PNES has previously been called pseudoseizures, psychogenic seizures, and hysterical seizures, but these terms have fallen out of favor.
ElectrocorticographyElectrocorticography (ECoG), a type of intracranial electroencephalography (iEEG), is a type of electrophysiological monitoring that uses electrodes placed directly on the exposed surface of the brain to record electrical activity from the cerebral cortex. In contrast, conventional electroencephalography (EEG) electrodes monitor this activity from outside the skull. ECoG may be performed either in the operating room during surgery (intraoperative ECoG) or outside of surgery (extraoperative ECoG).
Reflex seizureReflex seizures are epileptic seizures that are consistently induced by a specific stimulus or trigger making them distinct from other epileptic seizures, which are usually unprovoked. Reflex seizures are otherwise similar to unprovoked seizures and may be focal (simple or complex), generalized, myoclonic, or absence seizures. Epilepsy syndromes characterized by repeated reflex seizures are known as reflex epilepsies. Photosensitive seizures are often myoclonic, absence, or focal seizures in the occipital lobe, while musicogenic seizures are associated with focal seizures in the temporal lobe.
Advice (complexity)In computational complexity theory, an advice string is an extra input to a Turing machine that is allowed to depend on the length n of the input, but not on the input itself. A decision problem is in the complexity class P/f(n) if there is a polynomial time Turing machine M with the following property: for any n, there is an advice string A of length f(n) such that, for any input x of length n, the machine M correctly decides the problem on the input x, given x and A.
Generalized epilepsy with febrile seizures plusGeneralized epilepsy with febrile seizures plus (GEFS+) is a syndromic autosomal dominant disorder where affected individuals can exhibit numerous epilepsy phenotypes. GEFS+ can persist beyond early childhood (i.e., 6 years of age). GEFS+ is also now believed to encompass three other epilepsy disorders: severe myoclonic epilepsy of infancy (SMEI), which is also known as Dravet's syndrome, borderline SMEI (SMEB), and intractable epilepsy of childhood (IEC). There are at least six types of GEFS+, delineated by their causative gene.
Patient safetyPatient safety is a discipline that emphasizes safety in health care through the prevention, reduction, reporting and analysis of error and other types of unnecessary harm that often lead to adverse patient events. The frequency and magnitude of avoidable adverse events, often known as patient safety incidents, experienced by patients was not well known until the 1990s, when multiple countries reported significant numbers of patients harmed and killed by medical errors.
Sudden unexpected death in epilepsySudden unexpected death in epilepsy (SUDEP) is a fatal complication of epilepsy. It is defined as the sudden and unexpected, non-traumatic and non-drowning death of a person with epilepsy, without a toxicological or anatomical cause of death detected during the post-mortem examination. While the mechanisms underlying SUDEP are still poorly understood, it is possibly the most common cause of death as a result of complications from epilepsy, accounting for between 7.5 and 17% of all epilepsy-related deaths and 50% of all deaths in refractory epilepsy.
Feature selectionFeature selection is the process of selecting a subset of relevant features (variables, predictors) for use in model construction. Stylometry and DNA microarray analysis are two cases where feature selection is used. It should be distinguished from feature extraction. Feature selection techniques are used for several reasons: simplification of models to make them easier to interpret by researchers/users, shorter training times, to avoid the curse of dimensionality, improve data's compatibility with a learning model class, encode inherent symmetries present in the input space.
NeuroimagingNeuroimaging is the use of quantitative (computational) techniques to study the structure and function of the central nervous system, developed as an objective way of scientifically studying the healthy human brain in a non-invasive manner. Increasingly it is also being used for quantitative research studies of brain disease and psychiatric illness. Neuroimaging is highly multidisciplinary involving neuroscience, computer science, psychology and statistics, and is not a medical specialty.
