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Population codes, correlations and coding uncertainty

MPS-Authors
http://pubman.mpdl.mpg.de/cone/persons/resource/persons84260

Tolias,  AS
Department Physiology of Cognitive Processes, Max Planck Institute for Biological Cybernetics, Max Planck Society;

http://pubman.mpdl.mpg.de/cone/persons/resource/persons83896

Ecker,  A
Research Group Computational Vision and Neuroscience, Max Planck Institute for Biological Cybernetics, Max Planck Society;

http://pubman.mpdl.mpg.de/cone/persons/resource/persons84007

Keliris,  GA
Department Physiology of Cognitive Processes, Max Planck Institute for Biological Cybernetics, Max Planck Society;

http://pubman.mpdl.mpg.de/cone/persons/resource/persons84966

Panagiotaropolulos F, Panzeri,  S
Max Planck Institute for Biological Cybernetics, Max Planck Society;

http://pubman.mpdl.mpg.de/cone/persons/resource/persons84063

Logothetis,  NK
Department Physiology of Cognitive Processes, Max Planck Institute for Biological Cybernetics, Max Planck Society;

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Citation

Tolias, A., Ecker, A., Keliris, G., Panagiotaropolulos F, Panzeri, S., & Logothetis, N. (2007). Population codes, correlations and coding uncertainty. Poster presented at Neural Coding, Computation and Dynamics (NCCD 07), Hossegor, France.


Cite as: http://hdl.handle.net/11858/00-001M-0000-0013-CC1B-9
Abstract
Despite progress in systems neuroscience the neural code still remains elusive. 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 imperative to characterize the correlations between neurons and the impact that these correlations have on the amount of information encoded by populations of neurons. We use chronically implanted tetrode arrays to record simultaneously from many neurons in the primary visual cortex (V1) of awake, behaving macaques. We find that the correlations in the trialto- trial fluctuations of their firing rates between neurons under the same stimulation conditions (noise correlations) in V1 were very small (around 0.01 in 500 ms bin window) during passive viewing of sinusoidal grating stimuli. We are also measuring correlations in extrastriate visual areas and investigating the impact of correlations on encoding stimulus uncertainty by neuronal populations, under different stimulus and behavioral conditions.