Literature DB >> 15341738

Efficiency of information transmission by retinal ganglion cells.

Kristin Koch1, Judith McLean, Michael Berry, Peter Sterling, Vijay Balasubramanian, Michael A Freed.   

Abstract

BACKGROUND: Different types of retinal ganglion cells convey different messages to the brain. Messages are in the form of spike patterns, and the number of possible patterns per second sets the coding capacity. We asked if different ganglion cell types make equally efficient use of their coding capacity or whether efficiency depends on the message conveyed.
RESULTS: We recorded spike trains from retinal ganglion cells in an in vitro preparation of the guinea pig retina. By calculating, for the observed spike rate, the number of possible spike patterns per second, we calculated coding capacity, and by counting the actual number of patterns, we estimated information rate. Cells with "brisk" responses, i.e., high firing rates, and a general message transmitted information at high rates (21 +/- 9 bits s(-1)). Cells with "sluggish" responses, i.e., lower firing rates, and specific messages (direction of motion, local-edge) transmitted information at lower rates (13 +/- 7 bits s(-1)). Yet, for every type of ganglion cell examined, the information rate was about one-third of coding capacity. For every ganglion cell, information rate was very close (within 4%) to that predicted from Poisson noise and the cell's actual time-modulated rate.
CONCLUSIONS: Different messages are transmitted with similar efficiency. Efficiency is limited by temporal correlations, but correlations may be essential to improve decoding in the presence of irreducible noise.

Entities:  

Mesh:

Year:  2004        PMID: 15341738     DOI: 10.1016/j.cub.2004.08.060

Source DB:  PubMed          Journal:  Curr Biol        ISSN: 0960-9822            Impact factor:   10.834


  34 in total

1.  An information transmission measure for the analysis of effective connectivity among cortical neurons.

Authors:  Andrew J Law; Gaurav Sharma; Marc H Schieber
Journal:  Annu Int Conf IEEE Eng Med Biol Soc       Date:  2010

2.  Biophysical information representation in temporally correlated spike trains.

Authors:  William H Nesse; Leonard Maler; André Longtin
Journal:  Proc Natl Acad Sci U S A       Date:  2010-12-03       Impact factor: 11.205

3.  Spatial and temporal correlations of spike trains in frog retinal ganglion cells.

Authors:  Wen-Zhong Liu; Wei Jing; Hao Li; Hai-Qing Gong; Pei-Ji Liang
Journal:  J Comput Neurosci       Date:  2010-09-24       Impact factor: 1.621

4.  Stimulus discrimination via responses of retinal ganglion cells and dopamine-dependent modulation.

Authors:  Hao Li; Pei-Ji Liang
Journal:  Neurosci Bull       Date:  2013-08-29       Impact factor: 5.203

5.  Sluggish and brisk ganglion cells detect contrast with similar sensitivity.

Authors:  Ying Xu; Narender K Dhingra; Robert G Smith; Peter Sterling
Journal:  J Neurophysiol       Date:  2004-12-15       Impact factor: 2.714

6.  How much the eye tells the brain.

Authors:  Kristin Koch; Judith McLean; Ronen Segev; Michael A Freed; Michael J Berry; Vijay Balasubramanian; Peter Sterling
Journal:  Curr Biol       Date:  2006-07-25       Impact factor: 10.834

7.  Design of a neuronal array.

Authors:  Bart G Borghuis; Charles P Ratliff; Robert G Smith; Peter Sterling; Vijay Balasubramanian
Journal:  J Neurosci       Date:  2008-03-19       Impact factor: 6.167

8.  Reliability and frequency response of excitatory signals transmitted to different types of retinal ganglion cell.

Authors:  Michael A Freed; Zhiyin Liang
Journal:  J Neurophysiol       Date:  2010-01-20       Impact factor: 2.714

Review 9.  Receptive fields and functional architecture in the retina.

Authors:  Vijay Balasubramanian; Peter Sterling
Journal:  J Physiol       Date:  2009-06-15       Impact factor: 5.182

10.  Nonlinear convergence boosts information coding in circuits with parallel outputs.

Authors:  Gabrielle J Gutierrez; Fred Rieke; Eric T Shea-Brown
Journal:  Proc Natl Acad Sci U S A       Date:  2021-02-23       Impact factor: 11.205

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