Computational Modeling of Neural Activities for Statistical Inference

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 obse...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor principal: Kolossa, Antonio (Autor)
Autor Corporativo: SpringerLink (Online service)
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Cham : Springer International Publishing : Imprint: Springer, 2016.
Edición:1st ed. 2016.
Temas:
Neural networks (Computer science) .
Biomedical engineering.
Neurosciences.
Biomathematics.
Computer simulation.
Mathematical Models of Cognitive Processes and Neural Networks.
Biomedical Engineering and Bioengineering.
Neuroscience.
Mathematical and Computational Biology.
Computer Modelling.
Acceso en línea:Texto Completo
Tabla de Contenidos:
  • 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.

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