Literature DB >> 9482804

Refractoriness and neural precision.

M J Berry1, M Meister.   

Abstract

The response of a spiking neuron to a stimulus is often characterized by its time-varying firing rate, estimated from a histogram of spike times. If the cell's firing probability in each small time interval depends only on this firing rate, one predicts a highly variable response to repeated trials, whereas many neurons show much greater fidelity. Furthermore, the neuronal membrane is refractory immediately after a spike, so that the firing probability depends not only on the stimulus but also on the preceding spike train. To connect these observations, we investigated the relationship between the refractory period of a neuron and its firing precision. The light response of retinal ganglion cells was modeled as probabilistic firing combined with a refractory period: the instantaneous firing rate is the product of a "free firing rate, " which depends only on the stimulus, and a "recovery function," which depends only on the time since the last spike. This recovery function vanishes for an absolute refractory period and then gradually increases to unity. In simulations, longer refractory periods were found to make the response more reproducible, eventually matching the precision of measured spike trains. Refractoriness, although often thought to limit the performance of neurons, may in fact benefit neuronal reliability. The underlying free firing rate derived by allowing for the refractory period often exceeded the observed firing rate by an order of magnitude and was found to convey information about the stimulus over a much wider dynamic range. Thus, the free firing rate may be the preferred variable for describing the response of a spiking neuron.

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Year:  1998        PMID: 9482804      PMCID: PMC6792934     

Source DB:  PubMed          Journal:  J Neurosci        ISSN: 0270-6474            Impact factor:   6.167


  36 in total

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Authors:  S B Lowen; M C Teich
Journal:  J Acoust Soc Am       Date:  1992-08       Impact factor: 1.840

2.  Conditional probability analyses of the spike activity of single neurons.

Authors:  P R Gray
Journal:  Biophys J       Date:  2008-12-31       Impact factor: 4.033

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Journal:  J Acoust Soc Am       Date:  1985-04       Impact factor: 1.840

Review 5.  White-noise analysis in visual neuroscience.

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Journal:  Vis Neurosci       Date:  1988       Impact factor: 3.241

Review 6.  Cracking the neuronal code.

Authors:  D Ferster; N Spruston
Journal:  Science       Date:  1995-11-03       Impact factor: 47.728

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Journal:  Curr Opin Neurobiol       Date:  1994-08       Impact factor: 6.627

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Journal:  Exp Brain Res       Date:  1984       Impact factor: 1.972

9.  Stimulus and recovery dependence of cat cochlear nerve fiber spike discharge probability.

Authors:  R P Gaumond; C E Molnar; D O Kim
Journal:  J Neurophysiol       Date:  1982-09       Impact factor: 2.714

10.  The transmission of signals by auditory-nerve fiber discharge patterns.

Authors:  D H Johnson; A Swami
Journal:  J Acoust Soc Am       Date:  1983-08       Impact factor: 1.840

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  114 in total

1.  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

2.  Reliability of a fly motion-sensitive neuron depends on stimulus parameters.

Authors:  A K Warzecha; J Kretzberg; M Egelhaaf
Journal:  J Neurosci       Date:  2000-12-01       Impact factor: 6.167

3.  Temporal coding of visual information in the thalamus.

Authors:  P Reinagel; R C Reid
Journal:  J Neurosci       Date:  2000-07-15       Impact factor: 6.167

4.  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

5.  Negative interspike interval correlations increase the neuronal capacity for encoding time-dependent stimuli.

Authors:  M J Chacron; A Longtin; L Maler
Journal:  J Neurosci       Date:  2001-07-15       Impact factor: 6.167

6.  Information conveyed by onset transients in responses of striate cortical neurons.

Authors:  J R Müller; A B Metha; J Krauskopf; P Lennie
Journal:  J Neurosci       Date:  2001-09-01       Impact factor: 6.167

7.  Decorrelation and efficient coding by retinal ganglion cells.

Authors:  Xaq Pitkow; Markus Meister
Journal:  Nat Neurosci       Date:  2012-03-11       Impact factor: 24.884

8.  Information transmission rates of cat retinal ganglion cells.

Authors:  Christopher L Passaglia; John B Troy
Journal:  J Neurophysiol       Date:  2003-11-05       Impact factor: 2.714

9.  Synergy, redundancy, and independence in population codes.

Authors:  Elad Schneidman; William Bialek; Michael J Berry
Journal:  J Neurosci       Date:  2003-12-17       Impact factor: 6.167

10.  Measurement of excitability of tonically firing neurones tested in a variable-threshold model motoneurone.

Authors:  Peter B C Matthews
Journal:  J Physiol       Date:  2002-10-01       Impact factor: 5.182

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