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Spiking Neuron Models
W. Gerstner,W. K. Kistler +1 more
- pp 277-280
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Note: book Reference LCN-BOOK-2002-001 URL: http://diwww.epfl.ch/~gerstner/BUCH.htmlAbstract:
Note: book Reference LCN-BOOK-2002-001 URL: http://diwww.epfl.ch/~gerstner/BUCH.html Record created on 2006-12-12, modified on 2017-05-12read more
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Neuronal Oscillations in Cortical Networks
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Which model to use for cortical spiking neurons
TL;DR: The biological plausibility and computational efficiency of some of the most useful models of spiking and bursting neurons are discussed and their applicability to large-scale simulations of cortical neural networks is compared.
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Ralf Metzler,Joseph Klafter +1 more
TL;DR: Fractional dynamics has experienced a firm upswing during the past few years, having been forged into a mature framework in the theory of stochastic processes as mentioned in this paper, and a large number of research papers developing fractional dynamics further, or applying it to various systems have appeared since our first review article on the fractional Fokker-Planck equation.
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References
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Book
Spikes: Exploring the Neural Code
TL;DR: Spikes provides a self-contained review of relevant concepts in information theory and statistical decision theory about the representation of sensory signals in neural spike trains and a quantitative framework is used to pose precise questions about the structure of the neural code.
Journal ArticleDOI
How spike generation mechanisms determine the neuronal response to fluctuating inputs
TL;DR: This study examines the ability of neurons to track temporally varying inputs by investigating how the instantaneous firing rate of a neuron is modulated by a noisy input with a small sinusoidal component with frequency, and proposes a simplified one-variable model, the “exponential integrate-and-fire neuron,” as an approximation of a conductance-based model.
Journal ArticleDOI
The role of single neurons in information processing.
Christof Koch,Idan Segev +1 more
TL;DR: The role of neurons has evolved conceptually from that of a simple integrator of synaptic inputs until a threshold is reached and an output pulse is initiated, to a much more sophisticated processor with mixed analog-digital logic and highly adaptive synaptic elements.
Journal ArticleDOI
Impact of Synaptic Unreliability on the Information Transmitted by Spiking Neurons
TL;DR: This work considers a model in which a population of independent unreliable synapses provides the drive to an integrate-and-fire neuron, and considers two factors that govern the rate of information transfer: the synaptic reliability and the number of synapses connecting each presynaptic axon to its postsynaptic target.