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Synopsis
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.
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From the Back Cover
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.
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Computational Modeling of Neural Activities for Statistical Inference.
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xxiv, 127 p. Hardcover. Versand aus Deutschland / We dispatch from Germany via Air Mail. Einband bestoßen, daher Mängelexemplar gestempelt, sonst sehr guter Zustand. Imperfect copy due to slightly bumped cover, apart from this in very good condition. Stamped. Sprache: Englisch. Seller Inventory # 4394BB
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Computational Modeling of Neural Activities for Statistical Inference
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Computational Modeling of Neural Activities for Statistical Inference
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Computational Modeling of Neural Activities for Statistical Inference
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Computational Modeling of Neural Activities for Statistical Inference (Hardcover)
Published by
Springer International Publishing AG, Cham, 2016
ISBN 10: 3319322842
ISBN 13: 9783319322841
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Hardcover. Condition: 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. Seller Inventory # 9783319322841
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Computational Modeling of Neural Activities for Statistical Inference
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Computational Modeling of Neural Activities for Statistical Inference
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Computational Modeling of Neural Activities for Statistical Inference
Published by
Springer International Publishing Mai 2016, 2016
ISBN 10: 3319322842
ISBN 13: 9783319322841
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Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germany
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Buch. Condition: 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. Seller Inventory # 9783319322841
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Computational Modeling of Neural Activities for Statistical Inference
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Computational Modeling of Neural Activities for Statistical Inference
Published by
Springer International Publishing AG, 2016
ISBN 10: 3319322842
ISBN 13: 9783319322841
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Hardcover
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Condition: New. Num Pages: 127 pages, 22 black & white illustrations, 20 colour illustrations, 10 colour tables, biography. BIC Classification: MQW; PSAN. Category: (G) General (US: Trade). Dimension: 235 x 155 x 10. Weight in Grams: 397. . 2016. Hardback. . . . . Seller Inventory # V9783319322841
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