Encyclopedia of Computational Neuroscience

Living Edition
| Editors: Dieter Jaeger, Ranu Jung

Electrophysiology Analysis, Bayesian

  • Jakob H. MackeEmail author
Living reference work entry
DOI: https://doi.org/10.1007/978-1-4614-7320-6_448-1



Bayesian analysis of electrophysiological data refers to the statistical processing of data obtained in electrophysiological experiments (i.e., recordings of action potentials or voltage measurements with electrodes or imaging devices) which utilize methods from Bayesian statistics. Bayesian statistics is a framework for describing and modelling empirical data using the mathematical language of probability to model uncertainty. Bayesian statistics provides a principled and flexible framework for combining empirical observations with prior knowledge and for quantifying uncertainty. These features are especially useful for analysis questions in which the dataset sizes are small in comparison to the complexity of the model, which is often the case in neurophysiological data analysis.

Detailed Description


The Bayesian approach to statistics has become an established framework for analysis of...


Posterior Distribution Prior Distribution Receptive Field Bayesian Approach Marginal Likelihood 
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Copyright information

© Springer Science+Business Media New York 2014

Authors and Affiliations

  1. 1.Max Planck Institute for Biological Cybernetics and Bernstein Center for Computational NeuroscienceTübingenGermany