This book is concerned with sensory cue integration both within and between sensory modalities, and focuses on the emerging way of thinking about cue combination in terms of uncertainty. The probabilistic approaches elaborated in Sensory Cue Integration aim to formalize the uncertainty of cues. They describecue combination as the nervous system's attempt to minimize uncertainty in its estimates and to choose successful actions. This book provides an introduction into both computational models and experimental paradigms that are concerned with sensory cue integration both within and between sensory modalities. Importantly, across behavioral, electrophysiological and theoretical approaches, Bayesian statistics is emerging as a common language in which cue-combination problems can be expressed. This book focuses on the emerging probabilistic wayof thinking about these problems. These approaches derive fromthe realization that all our sensors are noisy and moreover are often affected by ambiguity. For example, mechanoreceptor outputs are variable and they cannot distinguish if a perceived force is caused by the weight of an object or by force we are producing ourselves. The computational approachesdescribed in this book aim at formalizing the uncertainty of cues. They describe cue combination as the nervous system>'s attempt to minimize uncertainty in its estimates and to choose successful actions. Some computational approaches described in the chapters of this book are concerned with the applicationof such statistical ideas to real-world cue-combination problems, such as shape and depth perception. Other parts of the book ask how uncertainty may be represented in the nervoussystem and used for cue combination.The broadening scope of probabilistic approaches to cue combination is highlighted in the breadth of topics covered in this book: the chapters summarize and discuss computational approaches and behavioral evidence aimed at understanding the combination of visual, auditory, proprioceptive, and haptic cues. Somechapters address the combination of cues within a single sensory modality while others address the combination across sensory modalities. Neural implementation, behavior, and theory areconsidered. The unifying aspect of this book is the focus on the uncertainty intrinsic to sensory cues and the underlying question of how the nervous system deals with this uncertainty.The book is intended as a reference text for graduate students and professionals in perceptual psychology, computational neuroscience, cognitive neuroscience and sensory neurophysiology. INDICE: Preface I. Theory and Fundamentals 1. Ideal-Observer Models of CueIntegration Landy, Banks, & Knill 2. Causal Inference in Sensorimotor Learning and Control Wei & Krding 3. The Role of Generative Knowledge in Object Perception Battaglia, Kersten, & Schrater 4. Generative Probabilistic Modeling: Understanding Causal Sensorimotor Integration Vijayakumar, Hospedales, & Haith 5. Modeling Cue Integration in Clutter Sahani & Whiteley 6. Recruitment of New Visual Cues for Perceptual Appearance Backus 7. Combining image signals before 3D reconstruction: The Intrinsic Constraint Model of Cue Integration Domini & Caudek 8. Cue Combination: Beyond So-Called "Optimality" Rosas & Wichmann II. Behavioral Studies 9. Priors and Learning in Cue Integration Seydell, Knill, & Trommershuser 10. Combining Vision With Audition and Touch, In Adults and In Children Burr, Binda, & Gori 11. The Statistical Relationship
- ISBN: 978-0-19-538724-7
- Editorial: Oxford University
- Encuadernacion: Cartoné
- Páginas: 456
- Fecha Publicación: 13/10/2011
- Nº Volúmenes: 1
- Idioma: Inglés