Literature DB >> 11430813

Predicting every spike: a model for the responses of visual neurons.

J Keat1, P Reinagel, R C Reid, M Meister.   

Abstract

In the early visual system, neuronal responses can be extremely precise. Under a wide range of stimuli, cells in the retina and thalamus fire spikes very reproducibly, often with millisecond precision on subsequent stimulus repeats. Here we develop a mathematical description of the firing process that, given the recent visual input, accurately predicts the timing of individual spikes. The formalism is successful in matching the spike trains from retinal ganglion cells in salamander, rabbit, and cat, as well as from lateral geniculate nucleus neurons in cat. It adapts to many different response types, from very precise to highly variable. The accuracy of the model allows a compact description of how these neurons encode the visual stimulus.

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Year:  2001        PMID: 11430813     DOI: 10.1016/s0896-6273(01)00322-1

Source DB:  PubMed          Journal:  Neuron        ISSN: 0896-6273            Impact factor:   17.173


  111 in total

1.  Adaptation to temporal contrast in primate and salamander retina.

Authors:  D Chander; E J Chichilnisky
Journal:  J Neurosci       Date:  2001-12-15       Impact factor: 6.167

2.  Different circuits for ON and OFF retinal ganglion cells cause different contrast sensitivities.

Authors:  Kareem A Zaghloul; Kwabena Boahen; Jonathan B Demb
Journal:  J Neurosci       Date:  2003-04-01       Impact factor: 6.167

3.  Decorrelation and efficient coding by retinal ganglion cells.

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

4.  Linking the computational structure of variance adaptation to biophysical mechanisms.

Authors:  Yusuf Ozuysal; Stephen A Baccus
Journal:  Neuron       Date:  2012-03-08       Impact factor: 17.173

5.  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

6.  Non-Euclidean properties of spike train metric spaces.

Authors:  Dmitriy Aronov; Jonathan D Victor
Journal:  Phys Rev E Stat Nonlin Soft Matter Phys       Date:  2004-06-02

7.  Impact of noise on retinal coding of visual signals.

Authors:  Christopher L Passaglia; John B Troy
Journal:  J Neurophysiol       Date:  2004-04-07       Impact factor: 2.714

8.  Inferring the role of inhibition in auditory processing of complex natural stimuli.

Authors:  Nadja Schinkel-Bielefeld; Stephen V David; Shihab A Shamma; Daniel A Butts
Journal:  J Neurophysiol       Date:  2012-03-28       Impact factor: 2.714

9.  The episodic nature of spike trains in the early visual pathway.

Authors:  Daniel A Butts; Gaëlle Desbordes; Chong Weng; Jianzhong Jin; Jose-Manuel Alonso; Garrett B Stanley
Journal:  J Neurophysiol       Date:  2010-10-06       Impact factor: 2.714

10.  Identifying Dendritic Processing.

Authors:  Aurel A Lazar; Yevgeniy B Slutskiy
Journal:  Adv Neural Inf Process Syst       Date:  2010
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