Literature DB >> 11588193

Consistency of encoding in monkey visual cortex.

M C Wiener1, M W Oram, Z Liu, B J Richmond.   

Abstract

Are different kinds of stimuli (for example, different classes of geometric images or naturalistic images) encoded differently by visual cortex, or are the principles of encoding the same for all stimuli? We examine two response properties: (1) the range of spike counts that can be elicited from a neuron in epochs representative of short periods of fixation (up to 400 msec), and (2) the relation between mean and variance of spike counts elicited by different stimuli, that together characterize the information processing capabilities of a neuron using the spike count code. In monkey primary visual cortex (V1) complex cells, we examine responses elicited by static stimuli of four kinds (photographic images, bars, gratings, and Walsh patterns); in area TE of inferior temporal cortex, we examine responses elicited by static stimuli in the sample, nonmatch, and match phases of a delayed match-to-sample task. In each area, the ranges of mean spike counts and the relation between mean and variance of spike counts elicited are sufficiently similar across experimental conditions that information transmission is unaffected by the differences across stimulus set or behavioral conditions [although in 10 of 27 (37%) of the V1 neurons there are statistically significant but small differences, the median difference in transmitted information for these neurons was 0.9%]. Encoding therefore appears to be consistent across experimental conditions for neurons in both V1 and TE, and downstream neurons could decode all incoming signals using a single set of rules.

Mesh:

Year:  2001        PMID: 11588193      PMCID: PMC6763869     

Source DB:  PubMed          Journal:  J Neurosci        ISSN: 0270-6474            Impact factor:   6.167


  45 in total

1.  Stochastic nature of precisely timed spike patterns in visual system neuronal responses.

Authors:  M W Oram; M C Wiener; R Lestienne; B J Richmond
Journal:  J Neurophysiol       Date:  1999-06       Impact factor: 2.714

2.  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

3.  Task difficulty: ignoring, attending to, and discriminating a visual stimulus yield progressively more activity in inferior temporal neurons.

Authors:  H Spitzer; B J Richmond
Journal:  Exp Brain Res       Date:  1991       Impact factor: 1.972

4.  Coding strategies in monkey V1 and inferior temporal cortices.

Authors:  E D Gershon; M C Wiener; P E Latham; B J Richmond
Journal:  J Neurophysiol       Date:  1998-03       Impact factor: 2.714

5.  Variability and correlated noise in the discharge of neurons in motor and parietal areas of the primate cortex.

Authors:  D Lee; N L Port; W Kruse; A P Georgopoulos
Journal:  J Neurosci       Date:  1998-02-01       Impact factor: 6.167

6.  Nature and precision of temporal coding in visual cortex: a metric-space analysis.

Authors:  J D Victor; K P Purpura
Journal:  J Neurophysiol       Date:  1996-08       Impact factor: 2.714

7.  The response variability of striate cortical neurons in the behaving monkey.

Authors:  R Vogels; W Spileers; G A Orban
Journal:  Exp Brain Res       Date:  1989       Impact factor: 1.972

8.  Naturalistic stimuli increase the rate and efficiency of information transmission by primary auditory afferents.

Authors:  F Rieke; D A Bodnar; W Bialek
Journal:  Proc Biol Sci       Date:  1995-12-22       Impact factor: 5.349

9.  The dependence of response amplitude and variance of cat visual cortical neurones on stimulus contrast.

Authors:  D J Tolhurst; J A Movshon; I D Thompson
Journal:  Exp Brain Res       Date:  1981       Impact factor: 1.972

10.  The statistical reliability of signals in single neurons in cat and monkey visual cortex.

Authors:  D J Tolhurst; J A Movshon; A F Dean
Journal:  Vision Res       Date:  1983       Impact factor: 1.886

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  7 in total

1.  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 2.  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

3.  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

4.  Neural selectivity in anterior inferotemporal cortex for morphed photographic images during behavioral classification or fixation.

Authors:  Yan Liu; Bharathi Jagadeesh
Journal:  J Neurophysiol       Date:  2008-01-30       Impact factor: 2.714

5.  The local and non-local components of the local field potential in awake primate visual cortex.

Authors:  Timothy J Gawne
Journal:  J Comput Neurosci       Date:  2010-02-24       Impact factor: 1.621

6.  Behavioral demand modulates object category representation in the inferior temporal cortex.

Authors:  Nazli Emadi; Hossein Esteky
Journal:  J Neurophysiol       Date:  2014-07-30       Impact factor: 2.714

7.  Medial temporal lobe activity at recognition increases with the duration of mnemonic delay during an object working memory task.

Authors:  Marco Picchioni; Pall Matthiasson; Matthew Broome; Vincent Giampietro; Mick Brammer; Birgit Mathes; Paul Fletcher; Steven Williams; Philip McGuire
Journal:  Hum Brain Mapp       Date:  2007-11       Impact factor: 5.038

  7 in total

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