Spiking neural network

Spiking neural network

Overview

Spiking neural networks (SNNs) fall into the third generation of neural network models, increasing the level of realism in a neural simulation. In addition to neuronal and synaptic state, SNNs also incorporate the concept of time into their operating model. The idea is that neurons in the SNN do not fire at each propagation cycle (as it happens with typical multi-layer perceptron networks), but rather fire only when a membrane potential - an intrinsic quality of the neuron related to its membrane electrical charge - reaches a specific value. When a neuron fires, it generates a signal which travels to other neurons which, in turn, increase or decrease their potentials in accordance with this signal.

In the context of spiking neural networks, the current activation level (modeled as some differential equation) is normally considered to be the neuron's state, with incoming spikes pushing this value higher, and then either firing or decaying over time. Various "coding methods" exist for interpreting the outgoing "spike train" as a real-value number, either relying on the frequency of spikes, or the timing between spikes, to encode information.

Beginnings

The first scientific model of a spiking neuron was proposed by Alan Lloyd Hodgkin and Andrew Huxley in 1952. This model describes how action potentials are initiated and propagated. Spikes, however are not generally transmitted directly between neurons, communication requires the exchange of chemical substances in the synaptic gap, called neurotransmitters. The complexity and variability of biological models have resulted in various neuron models, such as the integrate-and-fire (1907), FitzHugh-Nagumo (1961-1962) and Hindmarsh-Rose model (1984).

From the information theory point of view, the problem is to propose a model that explains how information is encoded and decoded by a series of trains of pulses, i.e., action potentials. Thus, one of the early questions of neuroscience is to determined if neurons communicated by a rate code or by a pulse code. [Maas, W. & Bishop, M.B.(1999) "Pulsed Neural Networks" MIT Press]

Early results with spiking neural models suggested that by using temporal coding, networks of spiking neurons may gain more computational power than traditional neural networks. It was also suggested that, under certain conditions, any multilayered perceptron can be simulated closely by a network consisting of spiking neurons.

References

External links

* Full text of the book [http://icwww.epfl.ch/~gerstner/SPNM/SPNM.html Spiking Neuron Models. Single Neurons, Populations, Plasticity] by Wulfram Gerstner and Werner M. Kistler (ISBN 0521890799)


Wikimedia Foundation. 2010.

Игры ⚽ Поможем написать реферат

Look at other dictionaries:

  • Neural network — For other uses, see Neural network (disambiguation). Simplified view of a feedforward artificial neural network The term neural network was traditionally used to refer to a network or circuit of biological neurons.[1] The modern usage of the term …   Wikipedia

  • Random neural network — The random neural network (RNN) is a mathematical representation of neurons or cells which exchange spiking signals. Each cell is represented by an integer whose value rises when the cell receives an excitatory spike and drops when it receives an …   Wikipedia

  • Neural oscillation — is rhythmic or repetitive neural activity in the central nervous system. Neural tissue can generate oscillatory activity in many ways, driven either by mechanisms localized within individual neurons or by interactions between neurons. In… …   Wikipedia

  • Neural correlates of consciousness — The Neuronal Correlates of Consciousness (NCC) constitute the smallest set of neural events and structures sufficient for a given conscious percept or explicit memory. This case involves synchronized action potentials in neocortical pyramidal… …   Wikipedia

  • Cultured neuronal network — A cultured neuronal network is a cell culture of neurons that is used as a model to study the central nervous system, especially the brain. Often, cultured neuronal networks are connected to an input/output device such as a multi electrode array… …   Wikipedia

  • Nonspiking neurons — Contents 1 History of Discovery 2 Definition and Physiology 3 Applications 4 References 5 Exte …   Wikipedia

  • EDLUT — (Event Driven LookUp Table) is a computer application for simulating networks of spiking neurons.It was developed in the University of Granada.EDLUT uses event driven simulation scheme and lookup tables to efficiently simulate medium or large… …   Wikipedia

  • Mind uploading — This page is about whole brain emulation in futurism, transhumanism and science. See also Mind uploading in fiction. Whole brain emulation or mind uploading (sometimes called mind transfer) is the hypothetical process of transferring or copying a …   Wikipedia

  • EDLUT — Saltar a navegación, búsqueda EDLUT (Event Driven LookUp Table) es una aplicación informática para simular redes neuronales de impulsos desarrollada en la Universidad de Granada. EDLUT usa un esquema de simulación dirigido por eventos y tablas de …   Wikipedia Español

  • SNN — Smith & Nephew P L C, American Depositary Receipts (Business » NYSE Symbols) * Snyder News Network (Community » Media) * Spiking Neural Network (Computing » Networking) * Schoolnet News Network (Community » Educational) * StarFleet News Network… …   Abbreviations dictionary

Share the article and excerpts

Direct link
Do a right-click on the link above
and select “Copy Link”