Computational Modeling of Neural Activities for Statistical Inference

Nonfiction, Science & Nature, Mathematics, Applied, Technology, Engineering
Cover of the book Computational Modeling of Neural Activities for Statistical Inference by Antonio Kolossa, Springer International Publishing
View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart
Author: Antonio Kolossa ISBN: 9783319322858
Publisher: Springer International Publishing Publication: May 12, 2016
Imprint: Springer Language: English
Author: Antonio Kolossa
ISBN: 9783319322858
Publisher: Springer International Publishing
Publication: May 12, 2016
Imprint: Springer
Language: English

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.

 

View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart

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.

 

More books from Springer International Publishing

Cover of the book Intelligent Network Integration of Distributed Renewable Generation by Antonio Kolossa
Cover of the book Passive and Active Measurement by Antonio Kolossa
Cover of the book Shape Casting by Antonio Kolossa
Cover of the book Complex Networks X by Antonio Kolossa
Cover of the book Excel 2010 for Environmental Sciences Statistics by Antonio Kolossa
Cover of the book Military Logistics by Antonio Kolossa
Cover of the book VLSI-SoC: System-on-Chip in the Nanoscale Era – Design, Verification and Reliability by Antonio Kolossa
Cover of the book Advances in Information and Communication Technologies for Adapting Agriculture to Climate Change by Antonio Kolossa
Cover of the book Street-Frequenting Young People in Fiji by Antonio Kolossa
Cover of the book Land and Credit by Antonio Kolossa
Cover of the book Manis Valuations and Prüfer Extensions II by Antonio Kolossa
Cover of the book Obsessive-Compulsive Symptoms in Schizophrenia by Antonio Kolossa
Cover of the book Handbook of Cerebrovascular Disease and Neurointerventional Technique by Antonio Kolossa
Cover of the book Knowledge Discovery, Knowledge Engineering and Knowledge Management by Antonio Kolossa
Cover of the book An Introduction to Integrable Techniques for One-Dimensional Quantum Systems by Antonio Kolossa
We use our own "cookies" and third party cookies to improve services and to see statistical information. By using this website, you agree to our Privacy Policy