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  Structure of interneuronal correlations in the primary visual cortex of the Rhesus macaque

Tolias, A., Keliris, G., Ecker, A., Siapas, A., Smirnakis, S., & Logothetis, N. (2005). Structure of interneuronal correlations in the primary visual cortex of the Rhesus macaque. Talk presented at 35th Annual Meeting of the Society for Neuroscience (Neuroscience 2005). Washington, DC, USA. 2005-11-12 - 2005-11-16.

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Item Permalink: http://hdl.handle.net/11858/00-001M-0000-0013-D3DF-D Version Permalink: http://hdl.handle.net/21.11116/0000-0005-40E0-5
Genre: Talk

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Tolias, AS1, 2, Author              
Keliris, GA1, 2, Author              
Ecker, AS2, 3, Author              
Siapas, AG, Author
Smirnakis, SM1, 2, Author              
Logothetis, NK1, 2, Author              
Affiliations:
1Department Physiology of Cognitive Processes, Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497798              
2Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497794              
3Research Group Computational Vision and Neuroscience, Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497805              

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 Abstract: Despite recent progress in systems neuroscience, basic properties of the neural code still remain obscure. For instance, the responses of single neurons are both highly variable and ambiguous (similar responses can be elicited by different types of stimuli). This variability/ambiguity has to be resolved by considering the joint pattern of firing of multiple single units responding simultaneously to a stimulus. Therefore, in order to understand the underlying principles of the neural code it is important to characterize the correlations between neurons and the impact that these correlations have on the amount of information that can be encoded by populations of neurons. Here we applied the technique of chronically implanted, multiple tetrodes to record simultaneously from a number of neurons in the primary visual cortex (V1) of the awake behaving macaque, and to measure the correlations in the trial-to-trial fluctuations of their firing rates under the same stimulation conditions (noise correlations). We find that, contrary to widespread belief, noise correlations in V1 are very small (around 0.01) and do not change systematically neither as a function of cortical distance (up to 600 m) nor as a function of the similarity in stimulus preference between the neurons (uniform correlation structure). Interestingly, a uniform correlation structure is predicted by theory to increase the achievable encoding accuracy of a neuronal population and may reflect a universal principle for population coding throughout the cortex. Support Contributed By: MPI, NEI(NIH)

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 Dates: 2005-11
 Publication Status: Published in print
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 Identifiers: BibTex Citekey: 3723
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Title: 35th Annual Meeting of the Society for Neuroscience (Neuroscience 2005)
Place of Event: Washington, DC, USA
Start-/End Date: 2005-11-12 - 2005-11-16

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Title: 35th Annual Meeting of the Society for Neuroscience (Neuroscience 2005)
Source Genre: Proceedings
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Pages: - Volume / Issue: - Sequence Number: 591.12 Start / End Page: - Identifier: -