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Neural networks with dynamic synapses

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Synaptic vesicle

In a neuron, synaptic vesicles (or neurotransmitter vesicles) store various neurotransmitters that are released at the synapse. The release is regulated by a voltage-dependent calcium channel. Vesicles are essential for propagating nerve impulses between neurons and are constantly recreated by the cell. The area in the axon that holds groups of vesicles is an axon terminal or "terminal bouton". Up to 130 vesicles can be released per bouton over a ten-minute period of stimulation at 0.2 Hz.

Neural facilitation

Neural 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.

Threshold potential

In electrophysiology, the threshold potential is the critical level to which a membrane potential must be depolarized to initiate an action potential. In neuroscience, threshold potentials are necessary to regulate and propagate signaling in both the central nervous system (CNS) and the peripheral nervous system (PNS). Most often, the threshold potential is a membrane potential value between –50 and –55 mV, but can vary based upon several factors.

Postsynaptic potential

Postsynaptic potentials are changes in the membrane potential of the postsynaptic terminal of a chemical synapse. Postsynaptic potentials are graded potentials, and should not be confused with action potentials although their function is to initiate or inhibit action potentials. They are caused by the presynaptic neuron releasing neurotransmitters from the terminal bouton at the end of an axon into the synaptic cleft. The neurotransmitters bind to receptors on the postsynaptic terminal, which may be a neuron or a muscle cell in the case of a neuromuscular junction.

Long-term depression

In 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.

Electrical synapse

An electrical synapse is a mechanical and electrically conductive link between two neighboring neurons that is formed at a narrow gap between the pre- and postsynaptic neurons known as a gap junction. At gap junctions, such cells approach within about 3.8 nm of each other, a much shorter distance than the 20- to 40-nanometer distance that separates cells at chemical synapse. In many animals, electrical synapse-based systems co-exist with chemical synapses.

Axon terminal

Axon terminals (also called synaptic boutons, terminal boutons, or end-feet) are distal terminations of the telodendria (branches) of an axon. An axon, also called a nerve fiber, is a long, slender projection of a nerve cell, or neuron, that conducts electrical impulses called action potentials away from the neuron's cell body, or soma, in order to transmit those impulses to other neurons, muscle cells or glands.

Neural network

A neural network can refer to a neural circuit of biological neurons (sometimes also called a biological neural network), a network of artificial neurons or nodes in the case of an artificial neural network. Artificial neural networks are used for solving artificial intelligence (AI) problems; they model connections of biological neurons as weights between nodes. A positive weight reflects an excitatory connection, while negative values mean inhibitory connections. All inputs are modified by a weight and summed.

Electrotonic potential

In physiology, electrotonus refers to the passive spread of charge inside a neuron and between cardiac muscle cells or smooth muscle cells. Passive means that voltage-dependent changes in membrane conductance do not contribute. Neurons and other excitable cells produce two types of electrical potential: Electrotonic potential (or graded potential), a non-propagated local potential, resulting from a local change in ionic conductance (e.g. synaptic or sensory that engenders a local current).

Recurrent neural network

A 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.