Literature DB >> 10695759

Temporal aspects of neural coding in the retina and lateral geniculate.

J D Victor1.   

Abstract

The early stages of visual processing provide excellent models for the study of how information is represented in, and processed by, the activity of neurons. The fact that the retina contains both non-spiking and spiking neurons leads us to frame questions about neural coding in a general fashion, rather than in a manner specific either to point processes or continuous signals. In particular, we ask about the role of the statistical structure of the response, the extent to which the neural representation is 'literal', and how information content can be estimated from laboratory data. The broad theme that emerges from a review of experimental data is that each stage of visual processing is accompanied by new features, including adaptive filtering, feedback, rectification and spike generation. These dynamical elements allow an increasingly rich set of strategies for the representation and processing of visual information at retinal and thalamic levels.

Mesh:

Year:  1999        PMID: 10695759

Source DB:  PubMed          Journal:  Network        ISSN: 0954-898X            Impact factor:   1.273


  23 in total

1.  Temporal coding of visual information in the thalamus.

Authors:  P Reinagel; R C Reid
Journal:  J Neurosci       Date:  2000-07-15       Impact factor: 6.167

2.  The transient precision of integrate and fire neurons: effect of background activity and noise.

Authors:  M C Van Rossum
Journal:  J Comput Neurosci       Date:  2001 May-Jun       Impact factor: 1.621

3.  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

4.  Assessing the encoding of stimulus attributes with rapid sequences of stimulus events.

Authors:  M Eger; R Eckhorn
Journal:  J Comput Neurosci       Date:  2002 Nov-Dec       Impact factor: 1.621

5.  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

6.  Analysis of between-trial and within-trial neural spiking dynamics.

Authors:  Gabriela Czanner; Uri T Eden; Sylvia Wirth; Marianna Yanike; Wendy A Suzuki; Emery N Brown
Journal:  J Neurophysiol       Date:  2008-01-23       Impact factor: 2.714

7.  Ruling out and ruling in neural codes.

Authors:  Adam L Jacobs; Gene Fridman; Robert M Douglas; Nazia M Alam; Peter E Latham; Glen T Prusky; Sheila Nirenberg
Journal:  Proc Natl Acad Sci U S A       Date:  2009-03-18       Impact factor: 11.205

8.  Cerebellar Purkinje cells control eye movements with a rapid rate code that is invariant to spike irregularity.

Authors:  Hannah L Payne; Ranran L French; Christine C Guo; Td Barbara Nguyen-Vu; Tiina Manninen; Jennifer L Raymond
Journal:  Elife       Date:  2019-05-03       Impact factor: 8.140

Review 9.  Re-membering the body: applications of computational neuroscience to the top-down control of regeneration of limbs and other complex organs.

Authors:  G Pezzulo; M Levin
Journal:  Integr Biol (Camb)       Date:  2015-11-16       Impact factor: 2.192

10.  Timing precision in population coding of natural scenes in the early visual system.

Authors:  Gaëlle Desbordes; Jianzhong Jin; Chong Weng; Nicholas A Lesica; Garrett B Stanley; Jose-Manuel Alonso
Journal:  PLoS Biol       Date:  2008-12-16       Impact factor: 8.029

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