Literature DB >> 7295867

A method of nonlinear analysis in the frequency domain.

J Victor, R Shapley.   

Abstract

A method is developed for the analysis of nonlinear biological systems based on an input temporal signal that consists of a sum of a large number of sinusoids. Nonlinear properties of the system are manifest by responses at harmonics and intermodulation frequencies of the input frequencies. The frequency kernels derived from these nonlinear responses are similar to the Fourier transforms of the Wiener kernels. Guidelines for the choice of useful input frequency sets, and examples satisfying these guidelines, are given. A practical algorithm for varying the relative phases of the input sinusoids to separate high-order interactions is presented. The utility of this technique is demonstrated with data obtained from a cat retinal ganglion cell of the Y type. For a high spatial frequency grafting, the entire response is contained in the even-order nonlinear components. Even at low contrast, fourth-order components are detectable. This suggests the presence of an essential nonlinearity in the functional pathway of the Y cell, with its singularity at zero contrast.

Mesh:

Year:  1980        PMID: 7295867      PMCID: PMC1328680          DOI: 10.1016/S0006-3495(80)85146-0

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


  15 in total

1.  Linear and nonlinear spatial subunits in Y cat retinal ganglion cells.

Authors:  S Hochstein; R M Shapley
Journal:  J Physiol       Date:  1976-11       Impact factor: 5.182

2.  Nonlinear analysis of cat retinal ganglion cells in the frequency domain.

Authors:  J D Victor; R M Shapley; B W Knight
Journal:  Proc Natl Acad Sci U S A       Date:  1977-07       Impact factor: 11.205

3.  Transfer characteristics of excitation and inhibition in cat retinal ganglion cells.

Authors:  L Maffei; L Cervetto; A Fiorentini
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4.  Linear systems analysis of the Limulus retina.

Authors:  F A Dodge; R M Shapley; B W Knight
Journal:  Behav Sci       Date:  1970-01

5.  Fourier analysis of dynamics of excitation and inhibition in the eye of Limulus: amplitude, phase and distance.

Authors:  F Ratliff; B W Knight; F A Dodge; H K Hartline
Journal:  Vision Res       Date:  1974-11       Impact factor: 1.886

6.  Statistical evaluation of the dynamic properties of cochlear nucleus units using stimuli modulated with pseudorandom noise.

Authors:  A R Moller
Journal:  Brain Res       Date:  1973-07-27       Impact factor: 3.252

7.  Nonlinear analysis and synthesis of receptive-field responses in the catfish retina. II. One-input white-noise analysis.

Authors:  P Z Marmarelis; K I Naka
Journal:  J Neurophysiol       Date:  1973-07       Impact factor: 2.714

8.  Nonlinearities of the human oculomotor system: gain.

Authors:  G J St-Cyr; D H Fender
Journal:  Vision Res       Date:  1969-10       Impact factor: 1.886

9.  Response of cat retinal ganglion cells to moving visual patterns.

Authors:  R W Rodieck; J Stone
Journal:  J Neurophysiol       Date:  1965-09       Impact factor: 2.714

10.  The analysis of nonlinear synaptic transmission.

Authors:  H I Krausz; W O Friesen
Journal:  J Gen Physiol       Date:  1977-08       Impact factor: 4.086

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  50 in total

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Journal:  Biol Cybern       Date:  1992       Impact factor: 2.086

6.  Signal transduction and nonlinearities revealed by white noise inputs in the fast adapting crayfish stretch receptor.

Authors:  J Bustamante; W Buño
Journal:  Exp Brain Res       Date:  1992       Impact factor: 1.972

7.  Stimulus-invariant processing and spectrotemporal reverse correlation in primary auditory cortex.

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Journal:  J Comput Neurosci       Date:  2006-02-20       Impact factor: 1.621

8.  The dynamical response properties of neocortical neurons to temporally modulated noisy inputs in vitro.

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9.  Maximally informative pairwise interactions in networks.

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Journal:  Phys Rev E Stat Nonlin Soft Matter Phys       Date:  2009-09-23

10.  Time dependence of stimulation/recording-artifact transfer function estimates for neural interface systems.

Authors:  Nick Chernyy; Steven J Schiff; Bruce J Gluckman
Journal:  Conf Proc IEEE Eng Med Biol Soc       Date:  2009
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