Biological neuron modelBiological neuron models, also known as a spiking neuron models, are mathematical descriptions of the properties of certain cells in the nervous system that generate sharp electrical potentials across their cell membrane, roughly one millisecond in duration, called action potentials or spikes (Fig. 2). Since spikes are transmitted along the axon and synapses from the sending neuron to many other neurons, spiking neurons are considered to be a major information processing unit of the nervous system.
MemoryMemory is the faculty of the mind by which data or information is encoded, stored, and retrieved when needed. It is the retention of information over time for the purpose of influencing future action. If past events could not be remembered, it would be impossible for language, relationships, or personal identity to develop. Memory loss is usually described as forgetfulness or amnesia. Memory is often understood as an informational processing system with explicit and implicit functioning that is made up of a sensory processor, short-term (or working) memory, and long-term memory.
Memory consolidationMemory consolidation is a category of processes that stabilize a memory trace after its initial acquisition. A memory trace is a change in the nervous system caused by memorizing something. Consolidation is distinguished into two specific processes. The first, synaptic consolidation, which is thought to correspond to late-phase long-term potentiation, occurs on a small scale in the synaptic connections and neural circuits within the first few hours after learning.
Artificial neuronAn artificial neuron is a mathematical function conceived as a model of biological neurons, a neural network. Artificial neurons are elementary units in an artificial neural network. The artificial neuron receives one or more inputs (representing excitatory postsynaptic potentials and inhibitory postsynaptic potentials at neural dendrites) and sums them to produce an output (or , representing a neuron's action potential which is transmitted along its axon).
Long-term depressionIn neurophysiology, long-term depression (LTD) is an activity-dependent reduction in the efficacy of neuronal synapses lasting hours or longer following a long patterned stimulus. LTD occurs in many areas of the CNS with varying mechanisms depending upon brain region and developmental progress. As the opposing process to long-term potentiation (LTP), LTD is one of several processes that serves to selectively weaken specific synapses in order to make constructive use of synaptic strengthening caused by LTP.
Models of neural computationModels of neural computation are attempts to elucidate, in an abstract and mathematical fashion, the core principles that underlie information processing in biological nervous systems, or functional components thereof. This article aims to provide an overview of the most definitive models of neuro-biological computation as well as the tools commonly used to construct and analyze them.
SynapseIn the nervous system, a synapse is a structure that permits a neuron (or nerve cell) to pass an electrical or chemical signal to another neuron or to the target effector cell. Synapses are essential to the transmission of nervous impulses from one neuron to another. Neurons are specialized to pass signals to individual target cells, and synapses are the means by which they do so. At a synapse, the plasma membrane of the signal-passing neuron (the presynaptic neuron) comes into close apposition with the membrane of the target (postsynaptic) cell.
Neural facilitationNeural facilitation, also known as paired-pulse facilitation (PPF), is a phenomenon in neuroscience in which postsynaptic potentials (PSPs) (EPPs, EPSPs or IPSPs) evoked by an impulse are increased when that impulse closely follows a prior impulse. PPF is thus a form of short-term synaptic plasticity. The mechanisms underlying neural facilitation are exclusively pre-synaptic; broadly speaking, PPF arises due to increased presynaptic Ca2+ concentration leading to a greater release of neurotransmitter-containing synaptic vesicles.
Network scienceNetwork science is an academic field which studies complex networks such as telecommunication networks, computer networks, biological networks, cognitive and semantic networks, and social networks, considering distinct elements or actors represented by nodes (or vertices) and the connections between the elements or actors as links (or edges). The field draws on theories and methods including graph theory from mathematics, statistical mechanics from physics, data mining and information visualization from computer science, inferential modeling from statistics, and social structure from sociology.
Non-spiking neuronNon-spiking neurons are neurons that are located in the central and peripheral nervous systems and function as intermediary relays for sensory-motor neurons. They do not exhibit the characteristic spiking behavior of action potential generating neurons. Non-spiking neural networks are integrated with spiking neural networks to have a synergistic effect in being able to stimulate some sensory or motor response while also being able to modulate the response.
