Literature DB >> 11731537

Variability and information in a neural code of the cat lateral geniculate nucleus.

R C Liu1, S Tzonev, S Rebrik, K D Miller.   

Abstract

A central theme in neural coding concerns the role of response variability and noise in determining the information transmission of neurons. This issue was investigated in single cells of the lateral geniculate nucleus of barbiturate-anesthetized cats by quantifying the degree of precision in and the information transmission properties of individual spike train responses to full field, binary (bright or dark), flashing stimuli. We found that neuronal responses could be highly reproducible in their spike timing (approximately 1-2 ms standard deviation) and spike count (approximately 0.3 ratio of variance/mean, compared with 1.0 expected for a Poisson process). This degree of precision only became apparent when an adequate length of the stimulus sequence was specified to determine the neural response, emphasizing that the variables relevant to a cell's response must be controlled to observe the cell's intrinsic response precision. Responses could carry as much as 3.5 bits/spike of information about the stimulus, a rate that was within a factor of two of the limit the spike train could transmit. Moreover, there appeared to be little sign of redundancy in coding: on average, longer response sequences carried at least as much information about the stimulus as would be obtained by adding together the information carried by shorter response sequences considered independently. There also was no direct evidence found for synergy between response sequences. These results could largely, but not entirely, be explained by a simple model of the response in which one filters the stimulus by the cell's impulse response kernel, thresholds the result at a fairly high level, and incorporates a postspike refractory period.

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Year:  2001        PMID: 11731537     DOI: 10.1152/jn.2001.86.6.2789

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


  34 in total

1.  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

Review 2.  Presynaptic frequency- and pattern-dependent filtering.

Authors:  Alex M Thomson
Journal:  J Comput Neurosci       Date:  2003 Sep-Oct       Impact factor: 1.621

3.  Decoding neuronal spike trains: how important are correlations?

Authors:  Sheila Nirenberg; Peter E Latham
Journal:  Proc Natl Acad Sci U S A       Date:  2003-05-29       Impact factor: 11.205

4.  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

5.  A rapid and precise on-response in posterior parietal cortex.

Authors:  James W Bisley; B Suresh Krishna; Michael E Goldberg
Journal:  J Neurosci       Date:  2004-02-25       Impact factor: 6.167

6.  Open-loop organization of thalamic reticular nucleus and dorsal thalamus: a computational model.

Authors:  Adam M Willis; Bernard J Slater; Ekaterina D Gribkova; Daniel A Llano
Journal:  J Neurophysiol       Date:  2015-08-19       Impact factor: 2.714

7.  Dejittered spike-conditioned stimulus waveforms yield improved estimates of neuronal feature selectivity and spike-timing precision of sensory interneurons.

Authors:  Zane N Aldworth; John P Miller; Tomás Gedeon; Graham I Cummins; Alexander G Dimitrov
Journal:  J Neurosci       Date:  2005-06-01       Impact factor: 6.167

8.  Feedforward excitation and inhibition evoke dual modes of firing in the cat's visual thalamus during naturalistic viewing.

Authors:  Xin Wang; Yichun Wei; Vishal Vaingankar; Qingbo Wang; Kilian Koepsell; Friedrich T Sommer; Judith A Hirsch
Journal:  Neuron       Date:  2007-08-02       Impact factor: 17.173

9.  A simple model of retina-LGN transmission.

Authors:  Alexander Casti; Fernand Hayot; Youping Xiao; Ehud Kaplan
Journal:  J Comput Neurosci       Date:  2007-09-01       Impact factor: 1.621

10.  Probing feature selectivity of neurons in primary visual cortex with natural stimuli.

Authors:  T Sharpee; H Sugihara; A V Kurgansky; S Rebrik; M P Stryker; K D Miller
Journal:  Proc SPIE Int Soc Opt Eng       Date:  2004
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