Journal article
Characterizing the fine structure of a neural sensory code through information distortion
Journal of computational neuroscience, Vol.30(1), pp.163-179
02/2011
Handle:
https://hdl.handle.net/2376/109521
PMID: 20730481
Abstract
We present an application of the information distortion approach to neural coding. The approach allows the discovery of neural symbols and the corresponding stimulus space of a neuron or neural ensemble simultaneously and quantitatively, making few assumptions about the nature of either code or relevant features. The neural codebook is derived by quantitizing sensory stimuli and neural responses into small reproduction sets, and optimizing the quantization to minimize the information distortion function. The application of this approach to the analysis of coding in sensory interneurons involved a further restriction of the space of allowed quantitizers to a smaller family of parametric distributions. We show that, for some cells in this system, a significant amount of information is encoded in patterns of spikes that would not be discovered through analyses based on linear stimulus-response measures.
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Details
- Title
- Characterizing the fine structure of a neural sensory code through information distortion
- Creators
- Alexander G Dimitrov - Department of Mathematics and WSU Vancouver Science Programs, Washington State University, Vancouver, WA 98686, USA. alex.dimitrov@vancouver.wsu.eduGraham I CumminsAditi BakerZane N Aldworth
- Publication Details
- Journal of computational neuroscience, Vol.30(1), pp.163-179
- Academic Unit
- Mathematics and Statistics, Department of
- Publisher
- United States
- Identifiers
- 99900547027901842
- Language
- English
- Resource Type
- Journal article