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Leabra
Leabra stands for local, error-driven and associative, biologically realistic algorithm. It is a model of learning which is a balance between Hebbian and error-driven learning with other network-derived characteristics. This model is used to mathematically predict outcomes based on inputs and previous learning influences. This model is heavily influenced by and contributes to neural network designs and models. This algorithm is the default algorithm in ''emergent'' (successor of PDP++) when making a new project, and is extensively used in various simulations. Hebbian learning is performed using conditional principal components analysis (CPCA) algorithm with correction factor for sparse expected activity levels. Error-driven learning is performed using GeneRec, which is a generalization of the recirculation algorithm, and approximates Almeida–Pineda recurrent backpropagation. The symmetric, midpoint version of GeneRec is used, which is equivalent to the contrastive Hebbian l ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
GeneRec
GeneRec is a generalization of the recirculation algorithm, and approximates Almeida-Pineda recurrent backpropagation.O'Reilly, R.C. Biologically Plausible Error-driven Learning using Local Activation Differences: The Generalized Recirculation Algorithm. Neural Computation, 8, 895–938Abstract It is used as part of the Leabra algorithm for error-driven learning. The symmetric, midpoint version of GeneRec is equivalent to the contrastive Hebbian learning algorithm (CHL). See also * Leabra O'Reilly (1996; Neural Computation) References Neuroscience Machine learning algorithms {{neuroscience-stub ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
PVLV
The primary value learned value (PVLV) model is a possible explanation for the reward-predictive firing properties of dopamine (DA) neurons. It simulates behavioral and neural data on Pavlovian conditioning and the midbrain dopaminergic neurons that fire in proportion to unexpected rewards. It is an alternative to the temporal-differences (TD) algorithm. It is used as part of Leabra Leabra stands for local, error-driven and associative, biologically realistic algorithm. It is a model of learning which is a balance between Hebbian and error-driven learning with other network-derived characteristics. This model is used to mathe .... References Computational neuroscience Machine learning algorithms {{neuroscience-stub ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Emergent (software)
Emergent (formerly PDP++) is neural simulation software that is primarily intended for creating models of the brain and cognitive processes. Development initially began in 1995 at Carnegie Mellon University, and , continues at the University of Colorado at Boulder. The 3.x release of the software, which was known as PDP++, is featured in the textbook ''Computational Explorations in Cognitive Neuroscience''. Features Emergent features a modular design, based on the principles of object-oriented programming. It runs on Microsoft Windows, Darwin / macOS and Linux. C-Super-Script (variously, CSS and C^C), a built-in C++-like interpreted scripting language, allows access to virtually all simulator objects and can initiate all the same actions as the GUI, and more. Version 4 and upward features a full 3D environment for visualizations, based on Qt and Open Inventor. Robotics simulations are made possible by integration with the Open Dynamics Engine. A plugin system allows for exp ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Machine Learning Algorithms
The following outline is provided as an overview of and topical guide to machine learning. Machine learning is a subfield of soft computing within computer science that evolved from the study of pattern recognition and computational learning theory in artificial intelligence.http://www.britannica.com/EBchecked/topic/1116194/machine-learning In 1959, Arthur Samuel defined machine learning as a "field of study that gives computers the ability to learn without being explicitly programmed". Machine learning explores the study and construction of algorithms that can learn from and make predictions on data. Such algorithms operate by building a model from an example training set of input observations in order to make data-driven predictions or decisions expressed as outputs, rather than following strictly static program instructions. What ''type'' of thing is machine learning? * An academic discipline * A branch of science ** An applied science *** A subfield of computer sci ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Hebbian Learning
Hebbian theory is a neuroscientific theory claiming that an increase in synaptic efficacy arises from a presynaptic cell's repeated and persistent stimulation of a postsynaptic cell. It is an attempt to explain synaptic plasticity, the adaptation of brain neurons during the learning process. It was introduced by Donald Hebb in his 1949 book '' The Organization of Behavior.'' The theory is also called Hebb's rule, Hebb's postulate, and cell assembly theory. Hebb states it as follows: Let us assume that the persistence or repetition of a reverberatory activity (or "trace") tends to induce lasting cellular changes that add to its stability. ... When an axon of cell ''A'' is near enough to excite a cell ''B'' and repeatedly or persistently takes part in firing it, some growth process or metabolic change takes place in one or both cells such that ''A''’s efficiency, as one of the cells firing ''B'', is increased. The theory is often summarized as "Cells that fire together wire tog ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Go (programming Language)
Go is a statically typed, compiled programming language designed at Google by Robert Griesemer, Rob Pike, and Ken Thompson. It is syntactically similar to C, but with memory safety, garbage collection, structural typing, and CSP-style concurrency. It is often referred to as Golang because of its former domain name, golang.org, but its proper name is Go. There are two major implementations: * Google's self-hosting "gc" compiler toolchain, targeting multiple operating systems and WebAssembly. * gofrontend, a frontend to other compilers, with the ''libgo'' library. With GCC the combination is gccgo; with LLVM the combination is gollvm. A third-party source-to-source compiler, GopherJS, compiles Go to JavaScript for front-end web development. History Go was designed at Google in 2007 to improve programming productivity in an era of multicore, networked machines and large codebases. The designers wanted to address criticism of other languages in use at Google, b ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Basal Ganglia
The basal ganglia (BG), or basal nuclei, are a group of subcortical nuclei, of varied origin, in the brains of vertebrates. In humans, and some primates, there are some differences, mainly in the division of the globus pallidus into an external and internal region, and in the division of the striatum. The basal ganglia are situated at the base of the forebrain and top of the midbrain. Basal ganglia are strongly interconnected with the cerebral cortex, thalamus, and brainstem, as well as several other brain areas. The basal ganglia are associated with a variety of functions, including control of voluntary motor movements, procedural learning, habit learning, conditional learning, eye movements, cognition, and emotion. The main components of the basal ganglia – as defined functionally – are the striatum, consisting of both the dorsal striatum ( caudate nucleus and putamen) and the ventral striatum ( nucleus accumbens and olfactory tubercle), the globus ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Working Memory
Working memory is a cognitive system with a limited capacity that can hold information temporarily. It is important for reasoning and the guidance of decision-making and behavior. Working memory is often used synonymously with short-term memory, but some theorists consider the two forms of memory distinct, assuming that working memory allows for the manipulation of stored information, whereas short-term memory only refers to the short-term storage of information. Working memory is a theoretical concept central to cognitive psychology, neuropsychology, and neuroscience. History The term "working memory" was coined by Miller, Galanter, and Pribram, and was used in the 1960s in the context of theories that likened the mind to a computer. In 1968, Atkinson and Shiffrin used the term to describe their "short-term store". What we now call working memory was formerly referred to variously as a "short-term store" or short-term memory, primary memory, immediate memory, operant mem ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Prefrontal Cortex
In mammalian brain anatomy, the prefrontal cortex (PFC) covers the front part of the frontal lobe of the cerebral cortex. The PFC contains the Brodmann areas BA8, BA9, BA10, BA11, BA12, BA13, BA14, BA24, BA25, BA32, BA44, BA45, BA46, and BA47. The basic activity of this brain region is considered to be orchestration of thoughts and actions in accordance with internal goals. Many authors have indicated an integral link between a person's will to live, personality, and the functions of the prefrontal cortex. This brain region has been implicated in executive functions, such as planning, decision making, short-term memory, personality expression, moderating social behavior and controlling certain aspects of speech and language. Executive function relates to abilities to differentiate among conflicting thoughts, determine good and bad, better and best, same and different, future consequences of current activities, working toward a defined goal, prediction of outcom ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Neurons
A neuron, neurone, or nerve cell is an electrically excitable cell that communicates with other cells via specialized connections called synapses. The neuron is the main component of nervous tissue in all animals except sponges and placozoa. Non-animals like plants and fungi do not have nerve cells. Neurons are typically classified into three types based on their function. Sensory neurons respond to stimuli such as touch, sound, or light that affect the cells of the sensory organs, and they send signals to the spinal cord or brain. Motor neurons receive signals from the brain and spinal cord to control everything from muscle contractions to glandular output. Interneurons connect neurons to other neurons within the same region of the brain or spinal cord. When multiple neurons are connected together, they form what is called a neural circuit. A typical neuron consists of a cell body (soma), dendrites, and a single axon. The soma is a compact structure, and the axon an ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Classical Conditioning
Classical conditioning (also known as Pavlovian or respondent conditioning) is a behavioral procedure in which a biologically potent stimulus (e.g. food) is paired with a previously neutral stimulus (e.g. a triangle). It also refers to the learning process that results from this pairing, through which the neutral stimulus comes to elicit a response (e.g. salivation) that is usually similar to the one elicited by the potent stimulus. Classical conditioning is distinct from operant conditioning (also called instrumental conditioning), through which the strength of a voluntary behavior is modified by reinforcement or punishment. However, classical conditioning can affect operant conditioning in various ways; notably, classically conditioned stimuli may serve to reinforce operant responses. Classical conditioning was first studied in detail by Ivan Pavlov, who conducted experiments with dogs and published his findings in 1897. During the Russian physiologist's study of digestion, ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
