computational modeling neural activities de kolossa antonio (26 résultats)

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Paperback. Etat : new. Paperback. 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. 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. Bayesian model selection is then used to choose the model which best explains the ERP amplitude fluctuations. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

Hardcover. Etat : new. Hardcover. 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. 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. Bayesian model selection is then used to choose the model which best explains the ERP amplitude fluctuations. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

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Taschenbuch. Etat : Neu. Neuware -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.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 152 pp. Englisch.

Buch. Etat : Neu. Neuware -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.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 152 pp. Englisch.

Taschenbuch. Etat : Neu. Druck auf Anfrage Neuware - Printed after ordering - This authored monograph supplies empirical evidence for the Bayesian brain hypothesis bymodeling event-related potentials (ERP) of the human electroencephalogram (EEG)during successive trials in cognitive tasks. The employed observer models are useful to computeprobability distributions over observable events and hidden states, depending onwhich are present in the respective tasks. Bayesianmodel selection is then used to choose the model which best explains the ERP amplitudefluctuations.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.

Buch. Etat : Neu. Druck auf Anfrage Neuware - Printed after ordering - This authored monograph supplies empirical evidence for the Bayesian brain hypothesis bymodeling event-related potentials (ERP) of the human electroencephalogram (EEG)during successive trials in cognitive tasks. The employed observer models are useful to computeprobability distributions over observable events and hidden states, depending onwhich are present in the respective tasks. Bayesianmodel selection is then used to choose the model which best explains the ERP amplitudefluctuations.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.

Etat : Sehr gut. Zustand: Sehr gut | Sprache: Englisch | Produktart: Bücher.

Paperback. Etat : New. New. book.

Paperback. Etat : new. Paperback. 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. 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. Bayesian model selection is then used to choose the model which best explains the ERP amplitude fluctuations. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.

Hardcover. Etat : new. Hardcover. 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. 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. Bayesian model selection is then used to choose the model which best explains the ERP amplitude fluctuations. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.

Buch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This authored monograph supplies empirical evidence for the Bayesian brain hypothesis bymodeling event-related potentials (ERP) of the human electroencephalogram (EEG)during successive trials in cognitive tasks. The employed observer models are useful to computeprobability distributions over observable events and hidden states, depending onwhich are present in the respective tasks. Bayesianmodel selection is then used to choose the model which best explains the ERP amplitudefluctuations.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. 152 pp. Englisch.

Taschenbuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This authored monograph supplies empirical evidence for the Bayesian brain hypothesis bymodeling event-related potentials (ERP) of the human electroencephalogram (EEG)during successive trials in cognitive tasks. The employed observer models are useful to computeprobability distributions over observable events and hidden states, depending onwhich are present in the respective tasks. Bayesianmodel selection is then used to choose the model which best explains the ERP amplitudefluctuations.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. 152 pp. Englisch.

Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Provides empirical evidence for the Bayesian brain hypothesis Presents observer models which are useful to compute probability distributions over observable events and hidden states Helps the reader to better understand the neural codin.

Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Provides empirical evidence for the Bayesian brain hypothesis Presents observer models which are useful to compute probability distributions over observable events and hidden states Helps the reader to better understand the neural codin.