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Biological Cybernetics

, 99:403 | Cite as

Information transmission in oscillatory neural activity

Original Paper

Abstract

Periodic neural activity not locked to the stimulus or to motor responses is usually ignored. Here, we present new tools for modeling and quantifying the information transmission based on periodic neural activity that occurs with quasi-random phase relative to the stimulus. We propose a model to reproduce characteristic features of oscillatory spike trains, such as histograms of inter-spike intervals and phase locking of spikes to an oscillatory influence. The proposed model is based on an inhomogeneous Gamma process governed by a density function that is a product of the usual stimulus-dependent rate and a quasi-periodic function. Further, we present an analysis method generalizing the direct method (Rieke et al. in Spikes: exploring the neural code. MIT Press, Cambridge, 1999; Brenner et al. in Neural Comput 12(7):1531–1552, 2000) to assess the information content in such data. We demonstrate these tools on recordings from relay cells in the lateral geniculate nucleus of the cat.

Keywords

Spike Train Lateral Geniculate Nucleus Information Rate Surrogate Data Relay Cell 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag 2008

Authors and Affiliations

  1. 1.Redwood Center for Theoretical Neuroscience, Helen Wills Neuroscience InstituteUniversity of California at BerkeleyBerkeleyUSA

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