Literature DB >> 10226187

Analysis of integrate-and-fire neurons: synchronization of synaptic input and spike output.

A N Burkitt1, G M Clark.   

Abstract

A new technique for analyzing the probability distribution of output spikes for the integrate-and-fire model is presented. This technique enables us to investigate models with arbitrary synaptic response functions that incorporate both leakage across the membrane and a rise time of the postsynaptic potential. The results, which are compared with numerical simulations, are exact in the limit of a large number of small-amplitude inputs. This method is applied to the synchronization problem, in which we examine the relationship between the spread in arrival times of the inputs (the temporal jitter of the synaptic input) and the resultant spread in the times at which the output spikes are generated (output jitter). The results of previous studies, which indicated that the ration of the output jitter to the input jitter is consistently less than one and that it decreases for increasing numbers of inputs, are confirmed for three classes of the integrate-and-fire model. In addition to the previously identified factors of axonal propagation times and synaptic jitter, we identify the variation in the spike-generating thresholds of the neurons and the variation in the number of active inputs as being important factors that determine the timing jitter in layered networks. Previously observed phase differences between optimally and suboptimally stimulated neurons may be understood in terms of the relative time taken to reach threshold.

Mesh:

Year:  1999        PMID: 10226187     DOI: 10.1162/089976699300016485

Source DB:  PubMed          Journal:  Neural Comput        ISSN: 0899-7667            Impact factor:   2.026


  17 in total

1.  Influence of temporal correlation of synaptic input on the rate and variability of firing in neurons.

Authors:  G Svirskis; J Rinzel
Journal:  Biophys J       Date:  2000-08       Impact factor: 4.033

2.  The transient precision of integrate and fire neurons: effect of background activity and noise.

Authors:  M C Van Rossum
Journal:  J Comput Neurosci       Date:  2001 May-Jun       Impact factor: 1.621

3.  Fast propagation of firing rates through layered networks of noisy neurons.

Authors:  Mark C W van Rossum; Gina G Turrigiano; Sacha B Nelson
Journal:  J Neurosci       Date:  2002-03-01       Impact factor: 6.167

4.  Summation of spatiotemporal input patterns in leaky integrate-and-fire neurons: application to neurons in the cochlear nucleus receiving converging auditory nerve fiber input.

Authors:  Levin Kuhlmann; Anthony N Burkitt; Antonio Paolini; Graeme M Clark
Journal:  J Comput Neurosci       Date:  2002 Jan-Feb       Impact factor: 1.621

5.  Mathematical models of cochlear nucleus onset neurons: I. Point neuron with many weak synaptic inputs.

Authors:  Sridhar Kalluri; Bertrand Delgutte
Journal:  J Comput Neurosci       Date:  2003 Jan-Feb       Impact factor: 1.621

6.  Neuromodulation by GABA converts a relay into a coincidence detector.

Authors:  Soham Chanda; Matthew A Xu-Friedman
Journal:  J Neurophysiol       Date:  2010-08-11       Impact factor: 2.714

7.  The most likely voltage path and large deviations approximations for integrate-and-fire neurons.

Authors:  Liam Paninski
Journal:  J Comput Neurosci       Date:  2006-04-22       Impact factor: 1.621

8.  Integral equation methods for computing likelihoods and their derivatives in the stochastic integrate-and-fire model.

Authors:  Liam Paninski; Adrian Haith; Gabor Szirtes
Journal:  J Comput Neurosci       Date:  2007-05-10       Impact factor: 1.621

9.  Tonotopic Optimization for Temporal Processing in the Cochlear Nucleus.

Authors:  Stefan N Oline; Go Ashida; R Michael Burger
Journal:  J Neurosci       Date:  2016-08-10       Impact factor: 6.167

Review 10.  Reliability, synchrony and noise.

Authors:  G Bard Ermentrout; Roberto F Galán; Nathaniel N Urban
Journal:  Trends Neurosci       Date:  2008-07-05       Impact factor: 13.837

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