Recurrent neural networkA recurrent neural network (RNN) is one of the two broad types of artificial neural network, characterized by direction of the flow of information between its layers. In contrast to uni-directional feedforward neural network, it is a bi-directional artificial neural network, meaning that it allows the output from some nodes to affect subsequent input to the same nodes. Their ability to use internal state (memory) to process arbitrary sequences of inputs makes them applicable to tasks such as unsegmented, connected handwriting recognition or speech recognition.
NeurotransmissionNeurotransmission (Latin: transmissio "passage, crossing" from transmittere "send, let through") is the process by which signaling molecules called neurotransmitters are released by the axon terminal of a neuron (the presynaptic neuron), and bind to and react with the receptors on the dendrites of another neuron (the postsynaptic neuron) a short distance away. A similar process occurs in retrograde neurotransmission, where the dendrites of the postsynaptic neuron release retrograde neurotransmitters (e.g.
Generalized epilepsyGeneralized epilepsy is a form of epilepsy characterised by generalised seizures with no apparent cause. Generalized seizures, as opposed to focal seizures, are a type of seizure that impairs consciousness and distorts the electrical activity of the whole or a larger portion of the brain (which can be seen, for example, on electroencephalography, EEG). Generalized epilepsy is primary because the epilepsy is the originally diagnosed condition itself, as opposed to secondary epilepsy, which occurs as a symptom of a diagnosed condition.
Status epilepticusStatus epilepticus (SE), or status seizure, is a medical condition consisting of a single seizure lasting more than 5 minutes, or 2 or more seizures within a 5-minute period without the person returning to normal between them. Previous definitions used a 30-minute time limit. The seizures can be of the tonic–clonic type, with a regular pattern of contraction and extension of the arms and legs, or of types that do not involve contractions, such as absence seizures or complex partial seizures.
Kuramoto modelThe Kuramoto model (or Kuramoto–Daido model), first proposed by Yoshiki Kuramoto, is a mathematical model used in describing synchronization. More specifically, it is a model for the behavior of a large set of coupled oscillators. Its formulation was motivated by the behavior of systems of chemical and biological oscillators, and it has found widespread applications in areas such as neuroscience and oscillating flame dynamics. Kuramoto was quite surprised when the behavior of some physical systems, namely coupled arrays of Josephson junctions, followed his model.
Photosensitive epilepsyPhotosensitive epilepsy (PSE) is a form of epilepsy in which seizures are triggered by visual stimuli that form patterns in time or space, such as flashing lights; bold, regular patterns; or regular moving patterns. PSE affects approximately one in 4,000 people (5% of those with epilepsy). People with PSE experience epileptiform seizures upon exposure to certain visual stimuli. The exact nature of the stimulus or stimuli that triggers the seizures varies from one patient to another, as does the nature and severity of the resulting seizures (ranging from brief absence seizures to full tonic–clonic seizures).
Temporal lobe epilepsyIn the field of neurology, temporal lobe epilepsy is an enduring brain disorder that causes unprovoked seizures from the temporal lobe. Temporal lobe epilepsy is the most common type of focal onset epilepsy among adults. Seizure symptoms and behavior distinguish seizures arising from the medial temporal lobe from seizures arising from the lateral (neocortical) temporal lobe. Memory and psychiatric comorbidities may occur. Diagnosis relies on electroencephalographic (EEG) and neuroimaging studies.
BrainA brain is an organ that serves as the center of the nervous system in all vertebrate and most invertebrate animals. It is located in the head, usually close to the sensory organs for senses such as vision. It is the most complex organ in a vertebrate's body. In a human, the cerebral cortex contains approximately 14–16 billion neurons, and the estimated number of neurons in the cerebellum is 55–70 billion. Each neuron is connected by synapses to several thousand other neurons.
Computational biologyComputational biology refers to the use of data analysis, mathematical modeling and computational simulations to understand biological systems and relationships. An intersection of computer science, biology, and big data, the field also has foundations in applied mathematics, chemistry, and genetics. It differs from biological computing, a subfield of computer engineering which uses bioengineering to build computers. Bioinformatics, the analysis of informatics processes in biological systems, began in the early 1970s.
Monitoring (medicine)In medicine, monitoring is the observation of a disease, condition or one or several medical parameters over time. It can be performed by continuously measuring certain parameters by using a medical monitor (for example, by continuously measuring vital signs by a bedside monitor), and/or by repeatedly performing medical tests (such as blood glucose monitoring with a glucose meter in people with diabetes mellitus). Transmitting data from a monitor to a distant monitoring station is known as telemetry or biotelemetry.
Spike-and-waveSpike-and-wave is a pattern of the electroencephalogram (EEG) typically observed during epileptic seizures. A spike-and-wave discharge is a regular, symmetrical, generalized EEG pattern seen particularly during absence epilepsy, also known as ‘petit mal’ epilepsy. The basic mechanisms underlying these patterns are complex and involve part of the cerebral cortex, the thalamocortical network, and intrinsic neuronal mechanisms. The first spike-and-wave pattern was recorded in the early twentieth century by Hans Berger.
Predictive modellingPredictive modelling uses statistics to predict outcomes. Most often the event one wants to predict is in the future, but predictive modelling can be applied to any type of unknown event, regardless of when it occurred. For example, predictive models are often used to detect crimes and identify suspects, after the crime has taken place. In many cases, the model is chosen on the basis of detection theory to try to guess the probability of an outcome given a set amount of input data, for example given an email determining how likely that it is spam.
