Literature DB >> 2746312

Dissection of the neuron network in the catfish inner retina. III. Interpretation of spike kernels.

M J Korenberg1, H M Sakai, K Naka.   

Abstract

1. Three independent sets of evidence have been obtained to show that similar first- and second-order light-evoked kernels are computed for the ganglion cell when the system output is taken to be either the spike train (discrete signal) or the postsynaptic potential (analog signal). In this paper we show that the similarity of postsynaptic potential (PSP) kernels and spike kernels is readily explained by assuming an underlying cascade structure for the neural information processing. The cascade structure enables spike kernels to be mathematically related very simply to the process of generating the postsynaptic potentials of ganglion cells. 2. Mathematical analysis of the cascade structure also suggests why spike kernels appear to differ slightly from PSP kernels. The relation between the two sets of kernels predicted from our analysis is substantiated here by experiment and reveals an interconnection between several of the signals measured. 3. Our experimental results, in particular, suggest that the neuronal circuitry leading from the light stimulus to the generation of ganglion cell spike discharges can be represented as follows: either a Wiener (LN) or a dynamic linear-static nonlinear-dynamic linear (LNL) structure is followed by a highly nonlinear process [static or brief-memory Hammerstein static-nonlinear dynamic-linear (NL) structure] of spike generation. Cross-correlation between the analog input and spike output enables identification of these structures.

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Year:  1989        PMID: 2746312     DOI: 10.1152/jn.1989.61.6.1110

Source DB:  PubMed          Journal:  J Neurophysiol        ISSN: 0022-3077            Impact factor:   2.714


  13 in total

Review 1.  The identification of nonlinear biological systems: Wiener kernel approaches.

Authors:  M J Korenberg; I W Hunter
Journal:  Ann Biomed Eng       Date:  1990       Impact factor: 3.934

2.  Temporal precision in the visual pathway through the interplay of excitation and stimulus-driven suppression.

Authors:  Daniel A Butts; Chong Weng; Jianzhong Jin; Jose-Manuel Alonso; Liam Paninski
Journal:  J Neurosci       Date:  2011-08-03       Impact factor: 6.167

Review 3.  Refractoriness and neural precision.

Authors:  M J Berry; M Meister
Journal:  J Neurosci       Date:  1998-03-15       Impact factor: 6.167

4.  The identification of nonlinear biological systems: Volterra kernel approaches.

Authors:  M J Korenberg; I W Hunter
Journal:  Ann Biomed Eng       Date:  1996 Mar-Apr       Impact factor: 3.934

5.  Contrast gain control in the lower vertebrate retinas.

Authors:  H M Sakai; J L Wang; K Naka
Journal:  J Gen Physiol       Date:  1995-06       Impact factor: 4.086

6.  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

7.  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

8.  Spike discharges of skeletomotor neurons during random noise modulated transmembrane current stimulation and muscle stretch.

Authors:  D Boskov; M Jocic; K Jovanovic; M Ljubisavljevic; R Anastasijevic
Journal:  Biol Cybern       Date:  1994       Impact factor: 2.086

9.  Functional identification of the input-output transforms of motoneurones in the rat and cat.

Authors:  A V Poliakov; R K Powers; M D Binder
Journal:  J Physiol       Date:  1997-10-15       Impact factor: 5.182

Review 10.  Modeling convergent ON and OFF pathways in the early visual system.

Authors:  Tim Gollisch; Markus Meister
Journal:  Biol Cybern       Date:  2008-11-15       Impact factor: 2.086

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