Literature DB >> 18940193

Linear and nonlinear systems analysis of the visual system: why does it seem so linear? A review dedicated to the memory of Henk Spekreijse.

Robert Shapley1.   

Abstract

Linear and nonlinear systems analysis are tools that can be used to study communication systems like the visual system. The first step of systems analysis often is to test whether or not the system is linear. Retinal pathways are surprisingly linear, and some neurons in the visual cortex also emulate linear sensory transducers. We conclude that the retinal linearity depends on specialized ribbon synapses while cortical linearity is the result of balanced excitatory and inhibitory synaptic interactions.

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Year:  2008        PMID: 18940193      PMCID: PMC2705991          DOI: 10.1016/j.visres.2008.09.026

Source DB:  PubMed          Journal:  Vision Res        ISSN: 0042-6989            Impact factor:   1.886


  75 in total

1.  X-like and Y-like ganglion cells in the Necturus retina.

Authors:  J R Tuttle; L C Scott
Journal:  Invest Ophthalmol Vis Sci       Date:  1979-05       Impact factor: 4.799

2.  Spatial properties of cells in the rabbit's striate cortex.

Authors:  D L Glanzman
Journal:  J Physiol       Date:  1983-07       Impact factor: 5.182

3.  Spatial frequency selectivity of cells in macaque visual cortex.

Authors:  R L De Valois; D G Albrecht; L G Thorell
Journal:  Vision Res       Date:  1982       Impact factor: 1.886

4.  Linear information processing in the retina: a study of horizontal cell responses.

Authors:  D Tranchina; J Gordon; R Shapley; J Toyoda
Journal:  Proc Natl Acad Sci U S A       Date:  1981-10       Impact factor: 11.205

5.  A method of nonlinear analysis in the frequency domain.

Authors:  J Victor; R Shapley
Journal:  Biophys J       Date:  1980-03       Impact factor: 4.033

6.  The effect of contrast on the transfer properties of cat retinal ganglion cells.

Authors:  R M Shapley; J D Victor
Journal:  J Physiol       Date:  1978-12       Impact factor: 5.182

7.  Receptive fields of neurons in areas 17 and 18 of tree shrews (Tupaia glis).

Authors:  P G Kaufmann; G G Somjen
Journal:  Brain Res Bull       Date:  1979 May-Jun       Impact factor: 4.077

8.  Receptive field characteristics of neurones in striate cortex of newborn lambs and adult sheep.

Authors:  H Kennedy; K A Martin; D Whitteridge
Journal:  Neuroscience       Date:  1983-10       Impact factor: 3.590

9.  The nonlinear pathway of Y ganglion cells in the cat retina.

Authors:  J D Victor; R M Shapley
Journal:  J Gen Physiol       Date:  1979-12       Impact factor: 4.086

10.  Receptive field mechanisms of cat X and Y retinal ganglion cells.

Authors:  J D Victor; R M Shapley
Journal:  J Gen Physiol       Date:  1979-08       Impact factor: 4.086

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  17 in total

1.  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

2.  Cell populations of the retina: the Proctor lecture.

Authors:  Richard H Masland
Journal:  Invest Ophthalmol Vis Sci       Date:  2011-06-28       Impact factor: 4.799

3.  The role of temporal contrast and blue light in emmetropization.

Authors:  Frances Rucker; Mark Henriksen; Tiffany Yanase; Christopher Taylor
Journal:  Vision Res       Date:  2017-08-01       Impact factor: 1.886

4.  Entrainment of visual steady-state responses is modulated by global spatial statistics.

Authors:  Thomas Nguyen; Karl Kuntzelman; Vladimir Miskovic
Journal:  J Neurophysiol       Date:  2017-04-26       Impact factor: 2.714

5.  Nonlinear spatial integration in the receptive field surround of retinal ganglion cells.

Authors:  Daisuke Takeshita; Tim Gollisch
Journal:  J Neurosci       Date:  2014-05-28       Impact factor: 6.167

6.  Nonlinear computations shaping temporal processing of precortical vision.

Authors:  Daniel A Butts; Yuwei Cui; Alexander R R Casti
Journal:  J Neurophysiol       Date:  2016-06-22       Impact factor: 2.714

7.  Divisive suppression explains high-precision firing and contrast adaptation in retinal ganglion cells.

Authors:  Yuwei Cui; Yanbin V Wang; Silvia J H Park; Jonathan B Demb; Daniel A Butts
Journal:  Elife       Date:  2016-11-14       Impact factor: 8.140

8.  Coding of chromatic spatial contrast by macaque V1 neurons.

Authors:  Abhishek De; Gregory D Horwitz
Journal:  Elife       Date:  2022-02-11       Impact factor: 8.140

9.  Revealing the neural networks associated with processing of natural social interaction and the related effects of actor-orientation and face-visibility.

Authors:  Manish Saggar; Elizabeth Walter Shelly; Jean-Francois Lepage; Fumiko Hoeft; Allan L Reiss
Journal:  Neuroimage       Date:  2013-09-29       Impact factor: 6.556

10.  Inferring nonlinear neuronal computation based on physiologically plausible inputs.

Authors:  James M McFarland; Yuwei Cui; Daniel A Butts
Journal:  PLoS Comput Biol       Date:  2013-07-18       Impact factor: 4.475

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