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Titlebook: Computational Modeling of Neural Activities for Statistical Inference; Antonio Kolossa Book 2016 Springer International Publishing Switzer

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A New Theory of Trial-by-Trial P300 Amplitude Fluctuations,s with a brief overview of the models known from literature and of the approach proposed in this work. After a description of the employed variant of the oddball task and specific methods for capturing trial-by-trial fluctuations in the P300 amplitudes .(.), the models and response functions constit
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Bayesian Inference and the Urn-Ball Task,ledge about the distributions over the random variables contained in the task. The Bayesian observer model adjusts internal beliefs about hidden states in the environment and predictions about observable events. The scope of the analyzed data is extended to the complete late positive complex (P3a, P
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Computational Modeling of Neural Activities for Statistical Inference978-3-319-32285-8
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tep 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.. .978-3-319-81243-4978-3-319-32285-8
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Book 2016e of practicing science at the end of the 20th and early 21st centuries in Argentina, a country located far away from the world’s leading scientific centers. In the book, I summarize the intricacies of the pineal gland (“the stone of madness”) as historical, mystical and medical entity and its entry
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Structure and Stress Evolution Due to Medium Energy Ion Bombardment of Silicon,sure are used to study the structure and damage evolution. Stresses are calculated using a force balance method and approach 1.7GPa and 1.3GPa in the 700eV and 500eV cases respectively after about 125 impacts. Continuum descriptions of the damaged surface are obtained from atomistic coordinate data using a silicon probe atom method.
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