Electrophysiology Analysis, Bayesian
- Jakob H. MackeAffiliated withMax Planck Institute for Biological Cybernetics and Bernstein Center for Computational Neuroscience Email author
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.
The Bayesian approach to statistics has become an established framework for analysis of empir ...
Reference Work Entry Metrics
Date: 2014 (Latest)History
- 2014 (Latest)
- Electrophysiology Analysis, Bayesian
- Reference Work Title
- Encyclopedia of Computational Neuroscience
- pp 1-5
- Online ISBN
- Springer New York
- Copyright Holder
- Springer Science+Business Media New York
- Industry Sectors
- eBook Packages
- Editor Affiliations
- 2. Department of Biomedical Engineering, Florida International University
- Author Affiliations
- 3. Max Planck Institute for Biological Cybernetics and Bernstein Center for Computational Neuroscience, Tübingen, Germany
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