Literature DB >> 8779718

A neuronal learning rule for sub-millisecond temporal coding.

W Gerstner1, R Kempter, J L van Hemmen, H Wagner.   

Abstract

A paradox that exists in auditory and electrosensory neural systems is that they encode behaviorally relevant signals in the range of a few microseconds with neurons that are at least one order of magnitude slower. The importance of temporal coding in neural information processing is not clear yet. A central question is whether neuronal firing can be more precise than the time constants of the neuronal processes involved. Here we address this problem using the auditory system of the barn owl as an example. We present a modelling study based on computer simulations of a neuron in the laminar nucleus. Three observations explain the paradox. First, spiking of an 'integrate-and-fire' neuron driven by excitatory postsynaptic potentials with a width at half-maximum height of 250 micros, has an accuracy of 25 micros if the presynaptic signals arrive coherently. Second, the necessary degree of coherence in the signal arrival times can be attained during ontogenetic development by virtue of an unsupervised hebbian learning rule. Learning selects connections with matching delays from a broad distribution of axons with random delays. Third, the learning rule also selects the correct delays from two independent groups of inputs, for example, from the left and right ear.

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Year:  1996        PMID: 8779718     DOI: 10.1038/383076a0

Source DB:  PubMed          Journal:  Nature        ISSN: 0028-0836            Impact factor:   49.962


  254 in total

1.  Formation of temporal-feature maps by axonal propagation of synaptic learning.

Authors:  R Kempter; C Leibold; H Wagner; J L van Hemmen
Journal:  Proc Natl Acad Sci U S A       Date:  2001-03-13       Impact factor: 11.205

2.  Noise shaping in populations of coupled model neurons.

Authors:  D J Mar; C C Chow; W Gerstner; R W Adams; J J Collins
Journal:  Proc Natl Acad Sci U S A       Date:  1999-08-31       Impact factor: 11.205

3.  Stable Hebbian learning from spike timing-dependent plasticity.

Authors:  M C van Rossum; G Q Bi; G G Turrigiano
Journal:  J Neurosci       Date:  2000-12-01       Impact factor: 6.167

4.  Computational consequences of temporally asymmetric learning rules: II. Sensory image cancellation.

Authors:  P D Roberts; C C Bell
Journal:  J Comput Neurosci       Date:  2000 Jul-Aug       Impact factor: 1.621

5.  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

6.  Rate and timing in cortical synaptic plasticity.

Authors:  Sacha B Nelson; Per Jesper Sjöström; Gina G Turrigiano
Journal:  Philos Trans R Soc Lond B Biol Sci       Date:  2002-12-29       Impact factor: 6.237

7.  Modeling of time disparity detection by the Hodgkin-Huxley equations.

Authors:  H Takagi; M Kawasaki
Journal:  J Comp Physiol A Neuroethol Sens Neural Behav Physiol       Date:  2003-03-07       Impact factor: 1.836

8.  Design parameters of the fan-out phase of sensory systems.

Authors:  Marta García-Sanchez; Ramón Huerta
Journal:  J Comput Neurosci       Date:  2003 Jul-Aug       Impact factor: 1.621

Review 9.  Time windows and reverberating loops: a reverse-engineering approach to cerebellar function.

Authors:  Werner M Kistler; Chris I De Zeeuw
Journal:  Cerebellum       Date:  2003       Impact factor: 3.847

10.  Temporal characteristics of the predictive synchronous firing modeled by spike-timing-dependent plasticity.

Authors:  Katsunori Kitano; Tomoki Fukai
Journal:  Learn Mem       Date:  2004 May-Jun       Impact factor: 2.460

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