Literature DB >> 2285759

Population coding of stimulus orientation by striate cortical cells.

R Vogels1.   

Abstract

I have examined the performance of a population coding model of visual orientation discrimination, similar to the population coding models proposed for the coding of limb movements. The orientation of the stimulus is not represented by a single unit but by an ensemble of broadly tuned units in a distributed way. Each unit is represented by a vector whose magnitude and direction correspond to the response magnitude and preferred orientation of the unit, respectively. The orientation of the population vector, i.e. the vector sum of the ensemble of units, is the signalled orientation on a particular trial. The accuracy of this population vector orientation coding was determined as a function of a number of parameters by computer simulation. I have shown that even with broadly orientation tuned units possessing considerable response variance, the accuracy of the orientation of the population vector can be as good as behaviorally measured just noticeable differences in orientation. The accuracy of the population code is shown to depend upon the number of units, the average response strength, the orientation band-width, response variability and the response covariance. The results of these simulations were also compared to predictions derived from psychophysical studies of orientation discrimination.

Mesh:

Year:  1990        PMID: 2285759     DOI: 10.1007/bf00203627

Source DB:  PubMed          Journal:  Biol Cybern        ISSN: 0340-1200            Impact factor:   2.086


  20 in total

1.  Cortical processing of hyperacuity tasks.

Authors:  M A Paradiso; T Carney; R D Freeman
Journal:  Vision Res       Date:  1989       Impact factor: 1.886

2.  Population coding of saccadic eye movements by neurons in the superior colliculus.

Authors:  C Lee; W H Rohrer; D L Sparks
Journal:  Nature       Date:  1988-03-24       Impact factor: 49.962

3.  Primate motor cortex and free arm movements to visual targets in three-dimensional space. II. Coding of the direction of movement by a neuronal population.

Authors:  A P Georgopoulos; R E Kettner; A B Schwartz
Journal:  J Neurosci       Date:  1988-08       Impact factor: 6.167

4.  Oscillatory responses in cat visual cortex exhibit inter-columnar synchronization which reflects global stimulus properties.

Authors:  C M Gray; P König; A K Engel; W Singer
Journal:  Nature       Date:  1989-03-23       Impact factor: 49.962

5.  Neuronal population coding of movement direction.

Authors:  A P Georgopoulos; A B Schwartz; R E Kettner
Journal:  Science       Date:  1986-09-26       Impact factor: 47.728

6.  Relationships between horizontal interactions and functional architecture in cat striate cortex as revealed by cross-correlation analysis.

Authors:  D Y Ts'o; C D Gilbert; T N Wiesel
Journal:  J Neurosci       Date:  1986-04       Impact factor: 6.167

7.  The effects of contrast on visual orientation and spatial frequency discrimination: a comparison of single cells and behavior.

Authors:  B C Skottun; A Bradley; G Sclar; I Ohzawa; R D Freeman
Journal:  J Neurophysiol       Date:  1987-03       Impact factor: 2.714

8.  A theory for the use of visual orientation information which exploits the columnar structure of striate cortex.

Authors:  M A Paradiso
Journal:  Biol Cybern       Date:  1988       Impact factor: 2.086

9.  Spatial-frequency adaptation and grating discrimination: predictions of a line-element model.

Authors:  H R Wilson; D Regan
Journal:  J Opt Soc Am A       Date:  1984-11       Impact factor: 2.129

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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  34 in total

1.  Parametric population representation of retinal location: neuronal interaction dynamics in cat primary visual cortex.

Authors:  D Jancke; W Erlhagen; H R Dinse; A C Akhavan; M Giese; A Steinhage; G Schöner
Journal:  J Neurosci       Date:  1999-10-15       Impact factor: 6.167

2.  Cellular mechanisms contributing to response variability of cortical neurons in vivo.

Authors:  R Azouz; C M Gray
Journal:  J Neurosci       Date:  1999-03-15       Impact factor: 6.167

3.  Uncertainty effects in orientation discrimination of foveally seen lines in human observers.

Authors:  B Lindblom; G Westheimer
Journal:  J Physiol       Date:  1992-08       Impact factor: 5.182

4.  Population coding of visual stimuli by cortical neurons tuned to more than one dimension.

Authors:  E Zohary
Journal:  Biol Cybern       Date:  1992       Impact factor: 2.086

5.  Tilt aftereffect from orientation discrimination learning.

Authors:  Nihong Chen; Fang Fang
Journal:  Exp Brain Res       Date:  2011-10-14       Impact factor: 1.972

6.  Internal curvature signal and noise in low- and high-level vision.

Authors:  Timothy D Sweeny; Marcia Grabowecky; Yee Joon Kim; Satoru Suzuki
Journal:  J Neurophysiol       Date:  2011-01-05       Impact factor: 2.714

7.  Specificity of V1-V2 orientation networks in the primate visual cortex.

Authors:  Anna W Roe; Daniel Y Ts'o
Journal:  Cortex       Date:  2015-07-22       Impact factor: 4.027

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.  Quantitative study of striate single unit responses in monkeys performing an orientation discrimination task.

Authors:  R Vogels; G A Orban
Journal:  Exp Brain Res       Date:  1991       Impact factor: 1.972

10.  Computing local edge probability in natural scenes from a population of oriented simple cells.

Authors:  Chaithanya A Ramachandra; Bartlett W Mel
Journal:  J Vis       Date:  2013-12-31       Impact factor: 2.240

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