Literature DB >> 15084652

Information tuning of populations of neurons in primary visual cortex.

Kukjin Kang1, Robert M Shapley, Haim Sompolinsky.   

Abstract

Neurons in macaque primary visual cortex (V1) show a diversity of orientation tuning properties, exhibiting a broad distribution of tuning width, baseline activity, peak response, and circular variance (CV). Here, we studied how the different tuning features affect the performance of these cells in discriminating between stimuli with different orientations. Previous studies of the orientation discrimination power of neurons in V1 focused on resolving two nearby orientations close to the psychophysical threshold of orientation discrimination. Here, we developed a theoretical framework, the information tuning curve, that measures the discrimination power of cells as a function of the orientation difference, deltatheta, of the two stimuli. This tuning curve also represents the mutual information between the neuronal responses and the stimulus orientation. We studied theoretically the dependence of the information tuning curve on the orientation tuning width, baseline, and peak responses. Of main interest is the finding that narrow orientation tuning is not necessarily optimal for all angular discrimination tasks. Instead, the optimal tuning width depends linearly on deltatheta. We applied our theory to study the discrimination performance of a population of 490 neurons in macaque V1. We found that a significant fraction of the neuronal population exhibits favorable tuning properties for large deltatheta. We also studied how the discrimination capability of neurons is distributed and compared several other measures of the orientation tuning such as CV with Chernoff distances for normalized tuning curves.

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Mesh:

Year:  2004        PMID: 15084652      PMCID: PMC6729344          DOI: 10.1523/JNEUROSCI.4272-03.2004

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


  22 in total

1.  Untuned suppression makes a major contribution to the enhancement of orientation selectivity in macaque v1.

Authors:  Dajun Xing; Dario L Ringach; Michael J Hawken; Robert M Shapley
Journal:  J Neurosci       Date:  2011-11-02       Impact factor: 6.167

2.  Spatial attention improves the quality of population codes in human visual cortex.

Authors:  Sameer Saproo; John T Serences
Journal:  J Neurophysiol       Date:  2010-05-19       Impact factor: 2.714

3.  Spatio-temporal information analysis of event-related BOLD responses.

Authors:  Galit Fuhrmann Alpert; Fellice T Sun; Daniel Handwerker; Mark D'Esposito; Robert T Knight
Journal:  Neuroimage       Date:  2006-12-22       Impact factor: 6.556

4.  Neural coding of categories: information efficiency and optimal population codes.

Authors:  Laurent Bonnasse-Gahot; Jean-Pierre Nadal
Journal:  J Comput Neurosci       Date:  2008-01-31       Impact factor: 1.621

5.  Level dependence of spatial processing in the primate auditory cortex.

Authors:  Yi Zhou; Xiaoqin Wang
Journal:  J Neurophysiol       Date:  2012-05-16       Impact factor: 2.714

6.  Population coding under normalization.

Authors:  Dario L Ringach
Journal:  Vision Res       Date:  2009-12-23       Impact factor: 1.886

7.  Topological analysis of population activity in visual cortex.

Authors:  Gurjeet Singh; Facundo Memoli; Tigran Ishkhanov; Guillermo Sapiro; Gunnar Carlsson; Dario L Ringach
Journal:  J Vis       Date:  2008-06-30       Impact factor: 2.240

8.  Reassessing optimal neural population codes with neurometric functions.

Authors:  Philipp Berens; Alexander S Ecker; Sebastian Gerwinn; Andreas S Tolias; Matthias Bethge
Journal:  Proc Natl Acad Sci U S A       Date:  2011-02-28       Impact factor: 11.205

9.  Local circuit inhibition in the cerebral cortex as the source of gain control and untuned suppression.

Authors:  Robert M Shapley; Dajun Xing
Journal:  Neural Netw       Date:  2012-09-20

10.  Sample skewness as a statistical measurement of neuronal tuning sharpness.

Authors:  Jason M Samonds; Brian R Potetz; Tai Sing Lee
Journal:  Neural Comput       Date:  2014-02-20       Impact factor: 2.026

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