Literature DB >> 4301347

Statistical analysis of membrane potential fluctuations. Relation with presynaptic spike train.

H Levitan, J P Segundo, G P Moore, D H Perkel.   

Abstract

In a study of integration at the single neuron level, the relationships between the postsynaptic membrane potential and the presynaptic spike train were analyzed. Fluctuations in membrane potential of neurons in the visceral ganglion of Aplysia were measured and described by histograms. The histogram estimates the probability density function of the membrane potential. Comparisons were made among histograms when there was no synaptic input, and when there was a single input in which variations were made in the PSP (postsynaptic potential) sign, i.e. excitatory or inhibitory, and arrival statistics, e.g. slow or fast, regular, Poisson-like, or patterned. This was examined in cells where the membrane potential was constant and in cells in which there was spontaneous pacemaker activity. The form of the histogram depended on whether the neuron was spontaneously quiescent or a pacemaker, or whether it received presynaptic input and, if it did, on the sign and temporal characteristics of such input. From such histograms the mean firing rate of output spike trains can be predicted; additional information of a temporal nature is required, however, to predict features of the interval structure of the output train. Suggestions are made concerning the way the nervous system might utilize the information summarized in the membrane potential histogram.

Mesh:

Year:  1968        PMID: 4301347      PMCID: PMC1367693          DOI: 10.1016/S0006-3495(68)86554-3

Source DB:  PubMed          Journal:  Biophys J        ISSN: 0006-3495            Impact factor:   4.033


  13 in total

1.  The recording of potentials from motoneurones with an intracellular electrode.

Authors:  L G BROCK; J S COOMBS; J C ECCLES
Journal:  J Physiol       Date:  1952-08       Impact factor: 5.182

2.  Spontaneous subthreshold activity at motor nerve endings.

Authors:  P FATT; B KATZ
Journal:  J Physiol       Date:  1952-05       Impact factor: 5.182

3.  Neuronal spike trains and stochastic point processes. I. The single spike train.

Authors:  D H Perkel; G L Gerstein; G P Moore
Journal:  Biophys J       Date:  1967-07       Impact factor: 4.033

4.  Input-output relations in computer-simulated nerve cells. Influence of the statistical properties, strength, number and inter-dependence of excitatory pre-synaptic terminals.

Authors:  J P Segundo; D H Perkel; H Wyman; H Hegstad; G P Moore
Journal:  Kybernetik       Date:  1968-05

Review 5.  Statistical analysis and functional interpretation of neuronal spike data.

Authors:  G P Moore; D H Perkel; J P Segundo
Journal:  Annu Rev Physiol       Date:  1966       Impact factor: 19.318

6.  Voltage fluctuations of neural membrane.

Authors:  A A Verveen; H E Derksen; K L Schick
Journal:  Nature       Date:  1967-11-11       Impact factor: 49.962

7.  Algebraical summation in synaptic activation of motoneurones firing within the 'primary range' to injected currents.

Authors:  R Granit; D Kernell; Y Lamarre
Journal:  J Physiol       Date:  1966-11       Impact factor: 5.182

8.  Fluctuations of resting neural membrane potential.

Authors:  H E Derksen; A A Verveen
Journal:  Science       Date:  1966-03-18       Impact factor: 47.728

9.  Site of origin and propagation in spike in the giant neuron of Aplysia.

Authors:  L TAUC
Journal:  J Gen Physiol       Date:  1962-07       Impact factor: 4.086

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  7 in total

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Authors:  Y Katayama; K Murata
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2.  Linear models for biological transducers and impulse train spectra: general formulation and review.

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Journal:  Kybernetik       Date:  1973-07

3.  Effect of structure on function in model nerve nets.

Authors:  P A Anninos; R Elul
Journal:  Biophys J       Date:  1974-01       Impact factor: 4.033

4.  On modelling the variability of interspike intervals during epileptic unit activity.

Authors:  F Pongrácz; M Szente
Journal:  Biol Cybern       Date:  1981       Impact factor: 2.086

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Journal:  Front Psychol       Date:  2011-04-09

6.  Adaptive Spike Threshold Enables Robust and Temporally Precise Neuronal Encoding.

Authors:  Chao Huang; Andrey Resnik; Tansu Celikel; Bernhard Englitz
Journal:  PLoS Comput Biol       Date:  2016-06-15       Impact factor: 4.475

7.  Optimized Real-Time Biomimetic Neural Network on FPGA for Bio-hybridization.

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  7 in total

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