Literature DB >> 9497396

Coding strategies in monkey V1 and inferior temporal cortices.

E D Gershon1, M C Wiener, P E Latham, B J Richmond.   

Abstract

We would like to know whether the statistics of neuronal responses vary across cortical areas. We examined stimulus-elicited spike count response distributions in V1 and inferior temporal (IT) cortices of awake monkeys. In both areas, the distribution of spike counts for each stimulus was well described by a Gaussian distribution, with the log of the variance in the spike count linearly related to the log of the mean spike count. Two significant differences in response characteristics were found: both the range of spike counts and the slope of the log(variance) versus log(mean) regression were larger in V1 than in IT. However, neurons in the two areas transmitted approximately the same amount of information about the stimuli and had about the same channel capacity (the maximum possible transmitted information given noise in the responses). These results suggest that neurons in V1 use more variable signals over a larger dynamic range than IT neurons, which use less variable signals over a smaller dynamic range. The two coding strategies are approximately as effective in transmitting information.

Mesh:

Year:  1998        PMID: 9497396     DOI: 10.1152/jn.1998.79.3.1135

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


  26 in total

1.  Interspike intervals, receptive fields, and information encoding in primary visual cortex.

Authors:  D S Reich; F Mechler; K P Purpura; J D Victor
Journal:  J Neurosci       Date:  2000-03-01       Impact factor: 6.167

2.  Postsynaptic variability of firing in rat cortical neurons: the roles of input synchronization and synaptic NMDA receptor conductance.

Authors:  A Harsch; H P Robinson
Journal:  J Neurosci       Date:  2000-08-15       Impact factor: 6.167

3.  Consistency of encoding in monkey visual cortex.

Authors:  M C Wiener; M W Oram; Z Liu; B J Richmond
Journal:  J Neurosci       Date:  2001-10-15       Impact factor: 6.167

4.  Decoding spike trains instant by instant using order statistics and the mixture-of-Poissons model.

Authors:  Matthew C Wiener; Barry J Richmond
Journal:  J Neurosci       Date:  2003-03-15       Impact factor: 6.167

Review 5.  The temporal resolution of neural codes: does response latency have a unique role?

Authors:  M W Oram; D Xiao; B Dritschel; K R Payne
Journal:  Philos Trans R Soc Lond B Biol Sci       Date:  2002-08-29       Impact factor: 6.237

6.  A model-based approach for the analysis of neuronal information transmission in multi-input and -output systems.

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

7.  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

8.  The integration of multiple stimulus features by V1 neurons.

Authors:  Alexander Grunewald; Evelyn K Skoumbourdis
Journal:  J Neurosci       Date:  2004-10-13       Impact factor: 6.167

9.  Dynamics and specificity of cortical map reorganization after retinal lesions.

Authors:  Dimitrios V Giannikopoulos; Ulf T Eysel
Journal:  Proc Natl Acad Sci U S A       Date:  2006-07-03       Impact factor: 11.205

10.  The influence of cortical feature maps on the encoding of the orientation of a short line.

Authors:  K N Shokhirev; T Kumar; D A Glaser
Journal:  J Comput Neurosci       Date:  2006-04-22       Impact factor: 1.621

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