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v. t. e. In machine learning, a neural network (also artificial neural network or neural net, abbreviated ANN or NN) is a model inspired by the structure and function of biological neural networks in animal brains. [ 1 ][ 2 ] An ANN consists of connected units or nodes called artificial neurons, which loosely model the neurons in the brain.
Sholl analysis is used to measure the number of crossings processes make at different distances from the centroid, and is a type of morphometric analysis. It is primarily used to measure arbour complexity. Certain morphologies cannot however be indexed using Sholl alone. For instance it may not make sense to compare neurons with arbors that ...
The summation of these three EPSPs generates an action potential. In neuroscience, an excitatory postsynaptic potential (EPSP) is a postsynaptic potential that makes the postsynaptic neuron more likely to fire an action potential. This temporary depolarization of postsynaptic membrane potential, caused by the flow of positively charged ions ...
D001931. Brain mapping is a set of neuroscience techniques predicated on the mapping of (biological) quantities or properties onto spatial representations of the (human or non-human) brain resulting in maps. According to the definition established in 2013 by Society for Brain Mapping and Therapeutics (SBMT), brain mapping is specifically ...
Mind uploading is a speculative process of whole brain emulation in which a brain scan is used to completely emulate the mental state of the individual in a digital computer. The computer would then run a simulation of the brain's information processing, such that it would respond in essentially the same way as the original brain and experience ...
The neuron whose weight vector is most similar to the input is called the best matching unit (BMU). The weights of the BMU and neurons close to it in the SOM grid are adjusted towards the input vector. The magnitude of the change decreases with time and with the grid-distance from the BMU. The update formula for a neuron v with weight vector W ...
Neuron (software) Neuron is a simulation environment for modeling individual and networks of neurons. It was primarily developed by Michael Hines, John W. Moore, and Ted Carnevale at Yale and Duke. Neuron models individual neurons via the use of sections that are automatically subdivided into individual compartments, instead of requiring the ...
Artificial neuron structure. An artificial neuron is a mathematical function conceived as a model of biological neurons in a neural network. Artificial neurons are the elementary units of artificial neural networks. [1] The artificial neuron is a function that receives one or more inputs, applies weights to these inputs, and sums them to ...