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Computational Modeling of Neural Act...
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Computational Modeling of Neural Activities for Statistical Inference
紀錄類型:
書目-語言資料,印刷品 : Monograph/item
正題名/作者:
Computational Modeling of Neural Activities for Statistical Inference / by Antonio Kolossa.
作者:
Kolossa, Antonio.
面頁冊數:
XXIV, 127 p. 42 illus., 20 illus. in color.online resource. :
Contained By:
Springer Nature eBook
標題:
Neural networks (Computer science) . -
電子資源:
https://doi.org/10.1007/978-3-319-32285-8
ISBN:
9783319322858
Computational Modeling of Neural Activities for Statistical Inference
Kolossa, Antonio.
Computational Modeling of Neural Activities for Statistical Inference
[electronic resource] /by Antonio Kolossa. - 1st ed. 2016. - XXIV, 127 p. 42 illus., 20 illus. in color.online resource.
Basic Principles of ERP Research, Surprise, and Probability Estimation -- Introduction to Model Estimation and Selection Methods -- A New Theory of Trial-by-Trial P300 Amplitude Fluctuations -- Bayesian Inference and the Urn-Ball Task -- Summary and Outlook.
This authored monograph supplies empirical evidence for the Bayesian brain hypothesis by modeling event-related potentials (ERP) of the human electroencephalogram (EEG) during successive trials in cognitive tasks. The employed observer models are useful to compute probability distributions over observable events and hidden states, depending on which are present in the respective tasks. Bayesian model selection is then used to choose the model which best explains the ERP amplitude fluctuations. Thus, this book constitutes a decisive step towards a better understanding of the neural coding and computing of probabilities following Bayesian rules. The target audience primarily comprises research experts in the field of computational neurosciences, but the book may also be beneficial for graduate students who want to specialize in this field. .
ISBN: 9783319322858
Standard No.: 10.1007/978-3-319-32285-8doiSubjects--Topical Terms:
1253765
Neural networks (Computer science) .
LC Class. No.: QA76.87
Dewey Class. No.: 519
Computational Modeling of Neural Activities for Statistical Inference
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