Literature DB >> 3719030

Minimum-order Wiener modelling of spike-output systems.

V Z Marmarelis, M C Citron, C P Vivo.   

Abstract

Systems that generate spike outputs in response to continuous inputs abound in neurophysiology. The study of their dynamics with the use of systems analysis methods has been complicated by the difference in modality of the input and output signals. When the problem is placed in the framework of Wiener's theory in discrete time, an infinite functional series is required for the formal representation of the input-output relation. This has given rise to the belief that a large number of Wiener functionals is needed in practice before a model of reasonable accuracy can be obtained. In this paper, we introduce the concept of minimum-order Wiener models for spike-output systems, and we show that a low-order Wiener model is adequate in many cases for predicting fully the timing of the output spikes.

Mesh:

Year:  1986        PMID: 3719030     DOI: 10.1007/bf00320482

Source DB:  PubMed          Journal:  Biol Cybern        ISSN: 0340-1200            Impact factor:   2.086


  1 in total

1.  Triggered correlation.

Authors:  R de Boer; P Kuyper
Journal:  IEEE Trans Biomed Eng       Date:  1968-07       Impact factor: 4.538

  1 in total
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5.  Identification of complex-cell intensive nonlinearities in a cascade model of cat visual cortex.

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Journal:  Biol Cybern       Date:  1992       Impact factor: 2.086

6.  White noise analysis of temporal properties in simple receptive fields of cat cortex.

Authors:  M Mancini; B C Madden; R C Emerson
Journal:  Biol Cybern       Date:  1990       Impact factor: 2.086

7.  Applications of minimum-order Wiener modeling to retinal ganglion cell spatiotemporal dynamics.

Authors:  M C Citron; V Z Marmarelis
Journal:  Biol Cybern       Date:  1987       Impact factor: 2.086

8.  Third-order reverse correlation analysis of muscle spindle primary afferent fiber responses to random muscle stretch.

Authors:  J Kröller
Journal:  Biol Cybern       Date:  1996-01       Impact factor: 2.086

9.  Reverse correlation analysis of the stretch response of primary muscle spindle afferent fibers.

Authors:  J Kröller
Journal:  Biol Cybern       Date:  1993       Impact factor: 2.086

10.  A method for constructing data-based models of spiking neurons using a dynamic linear-static nonlinear cascade.

Authors:  M G Paulin
Journal:  Biol Cybern       Date:  1993       Impact factor: 2.086

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