Biological Neural Network
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Biological Neural Network
A neural circuit is a population of neurons interconnected by synapses to carry out a specific function when activated. Neural circuits interconnect to one another to form large scale brain networks. Biological neural networks have inspired the design of artificial neural networks, but artificial neural networks are usually not strict copies of their biological counterparts. Early study Early treatments of neural networks can be found in Herbert Spencer's ''Principles of Psychology'', 3rd edition (1872), Theodor Meynert's ''Psychiatry'' (1884), William James' ''Principles of Psychology'' (1890), and Sigmund Freud's Project for a Scientific Psychology (composed 1895). The first rule of neuronal learning was described by Hebb in 1949, in the Hebbian theory. Thus, Hebbian pairing of pre-synaptic and post-synaptic activity can substantially alter the dynamic characteristics of the synaptic connection and therefore either facilitate or inhibit signal transmission. In 1959, the neur ...
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Blausen 0657 MultipolarNeuron
Blausen Medical Communications, Inc. is the creator and owner of a library of two- and three-dimensional medical and scientific images and animations, a developer of information technology allowing access to that content, and a business focused on licensing and distributing the content. It was founded by Bruce Blausen in Houston, Texas, in 1991, and is privately held. Background Blausen Medical Communications, Inc. (BMC) is a privately held company founded by Bruce Blausen in Houston, Texas in 1991. BMC created and owns a library of medical and scientific images and animations, and has developed information technology tools allowing access to the library; as well, it licenses and otherwise works to distribute the content. As of this date, BMC's animation library comprised approximately 1,500 animations and over 27,000 two- and three-dimensional images designed for point-of-care patient education, which could be accessed by consumers or professional caregivers (primarily via h ...
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Neurotransmission
Neurotransmission (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., endocannabinoids; synthesized in response to a rise in intracellular calcium levels) that signal through receptors that are located on the axon terminal of the presynaptic neuron, mainly at GABAergic and glutamatergic synapses. Neurotransmission is regulated by several different factors: the availability and rate-of-synthesis of the neurotransmitter, the release of that neurotransmitter, the baseline activity of the postsynaptic cell, the number of available postsynapti ...
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Leg Neural Network
A leg is a weight-bearing and locomotive anatomical structure, usually having a columnar shape. During locomotion, legs function as "extensible struts". The combination of movements at all joints can be modeled as a single, linear element capable of changing length and rotating about an omnidirectional "hip" joint. As an anatomical animal structure it is used for locomotion. The distal end is often modified to distribute force (such as a foot). Most animals have an even number of legs. As a component of furniture, it is used for the economy of materials needed to provide the support for the useful surface such as the table top or chair seat. Terminology *Uniped: 1 leg, such as clams *Biped: 2 legs, such as humans and birds * Triped: 3 legs, which typically does not occur naturally in healthy animals *Quadruped: 4 legs, such as dogs and horses Many taxa are characterized by the number of legs: *Tetrapods have four legs. Squamates of genus '' Bipes'' have only two. Caecilian ...
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Cell Body
The soma (pl. ''somata'' or ''somas''), perikaryon (pl. ''perikarya''), neurocyton, or cell body is the bulbous, non-process portion of a neuron or other brain cell type, containing the cell nucleus. The word 'soma' comes from the Greek '' σῶμα'', meaning 'body'. Although it is often used to refer to neurons, it can also refer to other cell types as well, including astrocytes, oligodendrocytes, and microglia. There are many different specialized types of neurons, and their sizes vary from as small as about 5 micrometres to over 10 millimetres for some of the smallest and largest neurons of invertebrates, respectively. The soma of a neuron (i.e., the main part of the neuron in which the dendrites branch off of) contains many organelles, including granules called Nissl granules, which are composed largely of rough endoplasmic reticulum and free polyribosomes. The cell nucleus is a key feature of the soma. The nucleus is the source of most of the RNA that is produced in neuron ...
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Summation (Neurophysiology)
Summation, which includes both spatial summation and temporal summation, is the process that determines whether or not an action potential will be generated by the combined effects of excitatory and inhibitory signals, both from multiple simultaneous inputs (spatial summation), and from repeated inputs (temporal summation). Depending on the sum total of many individual inputs, summation may or may not reach the threshold voltage to trigger an action potential. Neurotransmitters released from the terminals of a presynaptic neuron fall under one of two categories, depending on the ion channels gated or modulated by the neurotransmitter receptor. Excitatory neurotransmitters produce depolarization of the postsynaptic cell, whereas the hyperpolarization produced by an inhibitory neurotransmitter will mitigate the effects of an excitatory neurotransmitter. This depolarization is called an EPSP, or an excitatory postsynaptic potential, and the hyperpolarization is called an IPSP, or a ...
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Artificial Neurons
An 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). Usually each input is separately weighted, and the sum is passed through a non-linear function known as an activation function or transfer function. The transfer functions usually have a sigmoid shape, but they may also take the form of other non-linear functions, piecewise linear functions, or step functions. They are also often monotonically increasing, continuous, differentiable and bounded. Non-monotonic, unbounded and oscillating activation functions with multiple zeros that outperform sigmoidal and ReLU like activation ...
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Perceptrons
In machine learning, the perceptron (or McCulloch-Pitts neuron) is an algorithm for supervised learning of binary classifiers. A binary classifier is a function which can decide whether or not an input, represented by a vector of numbers, belongs to some specific class. It is a type of linear classifier, i.e. a classification algorithm that makes its predictions based on a linear predictor function combining a set of weights with the feature vector. History The perceptron was invented in 1943 by McCulloch and Pitts. The first implementation was a machine built in 1958 at the Cornell Aeronautical Laboratory by Frank Rosenblatt, funded by the United States Office of Naval Research. The perceptron was intended to be a machine, rather than a program, and while its first implementation was in software for the IBM 704, it was subsequently implemented in custom-built hardware as the "Mark 1 perceptron". This machine was designed for image recognition: it had an array of 400 photoc ...
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Biological Neuron Model
Biological 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. Spiking neuron models can be divided into different categories: the most detailed mathematical models are biophysical neuron models (also called Hodgkin-Huxley models) that describe the membrane voltage as a function of the input current and the activation of ion channels. Mathematically simpler are integrate-and-fire models that describe the membrane voltage as a function of the input current and predict the spike times without a description of the biophysical processes that shape ...
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Symbol
A symbol is a mark, sign, or word that indicates, signifies, or is understood as representing an idea, object, or relationship. Symbols allow people to go beyond what is known or seen by creating linkages between otherwise very different concepts and experiences. All communication (and data processing) is achieved through the use of symbols. Symbols take the form of words, sounds, gestures, ideas, or visual images and are used to convey other ideas and beliefs. For example, a red octagon is a common symbol for "STOP"; on maps, blue lines often represent rivers; and a red rose often symbolizes love and compassion. Numerals are symbols for numbers; letters of an alphabet may be symbols for certain phonemes; and personal names are symbols representing individuals. The variable 'x', in a mathematical equation, may symbolize the position of a particle in space. The academic study of symbols is semiotics. In cartography, an organized collection of symbols forms a legend for a map ...
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Arithmetic
Arithmetic () is an elementary part of mathematics that consists of the study of the properties of the traditional operations on numbers— addition, subtraction, multiplication, division, exponentiation, and extraction of roots. In the 19th century, Italian mathematician Giuseppe Peano formalized arithmetic with his Peano axioms, which are highly important to the field of mathematical logic today. History The prehistory of arithmetic is limited to a small number of artifacts, which may indicate the conception of addition and subtraction, the best-known being the Ishango bone from central Africa, dating from somewhere between 20,000 and 18,000 BC, although its interpretation is disputed. The earliest written records indicate the Egyptians and Babylonians used all the elementary arithmetic operations: addition, subtraction, multiplication, and division, as early as 2000 BC. These artifacts do not always reveal the specific process used for solving problems, but t ...
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Logic
Logic is the study of correct reasoning. It includes both formal and informal logic. Formal logic is the science of deductively valid inferences or of logical truths. It is a formal science investigating how conclusions follow from premises in a topic-neutral way. When used as a countable noun, the term "a logic" refers to a logical formal system that articulates a proof system. Formal logic contrasts with informal logic, which is associated with informal fallacies, critical thinking, and argumentation theory. While there is no general agreement on how formal and informal logic are to be distinguished, one prominent approach associates their difference with whether the studied arguments are expressed in formal or informal languages. Logic plays a central role in multiple fields, such as philosophy, mathematics, computer science, and linguistics. Logic studies arguments, which consist of a set of premises together with a conclusion. Premises and conclusions are usually un ...
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Implementation
Implementation is the realization of an application, or execution of a plan, idea, model, design, specification, standard, algorithm, or policy. Industry-specific definitions Computer science In computer science, an implementation is a realization of a technical specification or algorithm as a program, software component, or other computer system through computer programming and deployment. Many implementations may exist for a given specification or standard. For example, web browsers contain implementations of World Wide Web Consortium-recommended specifications, and software development tools contain implementations of programming languages. A special case occurs in object-oriented programming, when a concrete class implements an interface; in this case the concrete class is an ''implementation'' of the interface and it includes methods which are ''implementations'' of those methods specified by the interface. Information technology In the information technology during ind ...
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