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A neural network is a group of interconnected units called neurons that send signals to one another. Neurons can be either biological cells or mathematical models . While individual neurons are simple, many of them together in a network can perform complex tasks.
Network models can be classified as either network of neurons propagating through different levels of cortex or neuron populations interconnected as multilevel neurons. The spatial positioning of neuron could be 1-, 2- or 3-dimensional; the latter ones are called small-world networks as they are related to local region. The neuron could be ...
They showed that adding feedback connections between a resonance pair can support successful propagation of a single pulse packet throughout the entire network. [11] [12] The connectivity of a neural network stems from its biological structures and is usually challenging to map out experimentally. Scientists used a variety of statistical tools ...
The capacity of a network of standard neurons (not convolutional) can be derived by four rules [217] that derive from understanding a neuron as an electrical element. The information capacity captures the functions modelable by the network given any data as input. The second notion, is the VC dimension.
The central connectionist principle is that mental phenomena can be described by interconnected networks of simple and often uniform units. The form of the connections and the units can vary from model to model. For example, units in the network could represent neurons and the connections could represent synapses, as in the human brain.
Each output can be the input to an arbitrary number of neurons, including itself (i.e., self-loops are possible). However, an output cannot connect more than once with a single neuron. Self-loops do not cause contradictions, since the network operates in synchronous discrete time-steps.
Many neuroscientists believe that the human mind is largely an emergent property of the information processing of its neuronal network. [9]Neuroscientists have stated that important functions performed by the mind, such as learning, memory, and consciousness, are due to purely physical and electrochemical processes in the brain and are governed by applicable laws.
By analyzing different metrics from these connection matrices from the network, one can obtain a topological analysis of the desired graph; and this is referred to as the human brain network in the field of neuroscience. [12] One of the core architectures in brain network models is the "small-world" architecture.