Sensory Cue Integration
Sensory Cue Integration

Author: Julia Trommershauser

Publisher: Oxford University Press

Published: 2011-09-21

Total Pages: 461

ISBN-13: 019987476X

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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. These probabilistic approaches derive from the realization that 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 probabilistic approaches elaborated 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 application of such statistical ideas to real-world cue-combination problems. Others ask how uncertainty may be represented in the nervous system and used for cue combination. Importantly, across behavioral, electrophysiological and theoretical approaches, Bayesian statistics is emerging as a common language in which cue-combination problems can be expressed.

Sensory Cue Integration
Sensory Cue Integration

Author: Julia Trommershauser

Publisher: Computational Neuroscience

Published: 2011

Total Pages: 461

ISBN-13: 0195387244

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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. These probabilistic approaches derive from the realization that 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 probabilistic approaches elaborated 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 application of such statistical ideas to real-world cue-combination problems. Others ask how uncertainty may be represented in the nervous system and used for cue combination. Importantly, across behavioral, electrophysiological and theoretical approaches, Bayesian statistics is emerging as a common language in which cue-combination problems can be expressed

The Neural Bases of Multisensory Processes
The Neural Bases of Multisensory Processes

Author: Micah M. Murray

Publisher: CRC Press

Published: 2011-08-25

Total Pages: 800

ISBN-13: 1439812179

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It has become accepted in the neuroscience community that perception and performance are quintessentially multisensory by nature. Using the full palette of modern brain imaging and neuroscience methods, The Neural Bases of Multisensory Processes details current understanding in the neural bases for these phenomena as studied across species, stages of development, and clinical statuses. Organized thematically into nine sub-sections, the book is a collection of contributions by leading scientists in the field. Chapters build generally from basic to applied, allowing readers to ascertain how fundamental science informs the clinical and applied sciences. Topics discussed include: Anatomy, essential for understanding the neural substrates of multisensory processing Neurophysiological bases and how multisensory stimuli can dramatically change the encoding processes for sensory information Combinatorial principles and modeling, focusing on efforts to gain a better mechanistic handle on multisensory operations and their network dynamics Development and plasticity Clinical manifestations and how perception and action are affected by altered sensory experience Attention and spatial representations The last sections of the book focus on naturalistic multisensory processes in three separate contexts: motion signals, multisensory contributions to the perception and generation of communication signals, and how the perception of flavor is generated. The text provides a solid introduction for newcomers and a strong overview of the current state of the field for experts.

Multisensory Flavor Perception
Multisensory Flavor Perception

Author: Betina Piqueras-Fiszman

Publisher: Woodhead Publishing

Published: 2016-04-14

Total Pages: 378

ISBN-13: 008100351X

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Multisensory Flavor Perception: From Fundamental Neuroscience Through to the Marketplace provides state-of-the-art coverage of the latest insights from the rapidly-expanding world of multisensory flavor research. The book highlights the various types of crossmodal interactions, such as sound and taste, and vision and taste, showing their impact on sensory and hedonic perception, along with their consumption in the context of food and drink. The chapters in this edited volume review the existing literature, also explaining the underlying neural and psychological mechanisms which lead to crossmodal perception of flavor. The book brings together research which has not been presented before, making it the first book in the market to cover the literature of multisensory flavor perception by incorporating the latest in psychophysics and neuroscience. - Authored by top academics and world leaders in the field - Takes readers on a journey from the neurological underpinnings of multisensory flavor perception, then presenting insights that can be used by food companies to create better flavor sensations for consumers - Offers a wide perspective on multisensory flavor perception, an area of rapidly expanding knowledge

Sensory Integration and the Unity of Consciousness
Sensory Integration and the Unity of Consciousness

Author: David Bennett

Publisher: MIT Press

Published: 2022-06-07

Total Pages: 421

ISBN-13: 026254573X

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Philosophers and cognitive scientists address the relationships among the senses and the connections between conscious experiences that form unified wholes. In this volume, cognitive scientists and philosophers examine two closely related aspects of mind and mental functioning: the relationships among the various senses and the links that connect different conscious experiences to form unified wholes. The contributors address a range of questions concerning how information from one sense influences the processing of information from the other senses and how unified states of consciousness emerge from the bonds that tie conscious experiences together. Sensory Integration and the Unity of Consciousness is the first book to address both of these topics, integrating scientific and philosophical concerns. A flood of recent work in both philosophy and perception science has challenged traditional conceptions of the sensory systems as operating in isolation. Contributors to the volume consider the ways in which perceptual contact with the world is or may be “multisensory,” discussing such subjects as the modeling of multisensory integration and philosophical aspects of sensory modalities. Recent years have seen a similar surge of interest in unity of consciousness. Contributors explore a range of questions on this topic, including the nature of that unity, the degree to which conscious experiences are unified, and the relationship between unified consciousness and the self. Contributors Tim Bayne, David J. Bennett, Berit Brogaard, Barry Dainton, Ophelia Deroy, Frederique de Vignemont, Marc Ernst, Richard Held, Christopher S. Hill, Geoffrey Lee, Kristan Marlow, Farid Masrour, Jennifer Matey, Casey O'Callaghan, Cesare V. Parise, Kevin Rice, Elizabeth Schechter, Pawan Sinha, Julia Trommershaeuser, Loes C. J. van Dam, Jonathan Vogel, James Van Cleve, Robert Van Gulick, Jonas Wulff

Multisensory Development
Multisensory Development

Author: Andrew J. Bremner

Publisher: Oxford University Press

Published: 2012-06-21

Total Pages: 393

ISBN-13: 0199586055

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We perceive and understand our environment using many sensory systems-vision, touch, hearing, taste, smell, and proprioception. These multiple sensory modalities give us complementary sources of information about the environment. This book explores how we develop the ability to integrate our senses.

Computational Models of Brain and Behavior
Computational Models of Brain and Behavior

Author: Ahmed A. Moustafa

Publisher: John Wiley & Sons

Published: 2017-09-11

Total Pages: 588

ISBN-13: 1119159075

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A comprehensive Introduction to the world of brain and behavior computational models This book provides a broad collection of articles covering different aspects of computational modeling efforts in psychology and neuroscience. Specifically, it discusses models that span different brain regions (hippocampus, amygdala, basal ganglia, visual cortex), different species (humans, rats, fruit flies), and different modeling methods (neural network, Bayesian, reinforcement learning, data fitting, and Hodgkin-Huxley models, among others). Computational Models of Brain and Behavior is divided into four sections: (a) Models of brain disorders; (b) Neural models of behavioral processes; (c) Models of neural processes, brain regions and neurotransmitters, and (d) Neural modeling approaches. It provides in-depth coverage of models of psychiatric disorders, including depression, posttraumatic stress disorder (PTSD), schizophrenia, and dyslexia; models of neurological disorders, including Alzheimer’s disease, Parkinson’s disease, and epilepsy; early sensory and perceptual processes; models of olfaction; higher/systems level models and low-level models; Pavlovian and instrumental conditioning; linking information theory to neurobiology; and more. Covers computational approximations to intellectual disability in down syndrome Discusses computational models of pharmacological and immunological treatment in Alzheimer's disease Examines neural circuit models of serotonergic system (from microcircuits to cognition) Educates on information theory, memory, prediction, and timing in associative learning Computational Models of Brain and Behavior is written for advanced undergraduate, Master's and PhD-level students—as well as researchers involved in computational neuroscience modeling research.

Multisensory Processes
Multisensory Processes

Author: Adrian Kuo Ching Lee

Publisher:

Published: 2019

Total Pages:

ISBN-13: 9783030104603

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Auditory behavior, perception, and cognition are all shaped by information from other sensory systems. This volume examines this multi-sensory view of auditory function at levels of analysis ranging from the single neuron to neuroimaging in human clinical populations. Visual Influence on Auditory Perception Adrian K.C. Lee and Mark T. Wallace Cue Combination within a Bayesian Framework David Alais and David Burr Toward a Model of Auditory-Visual Speech Intelligibility Ken W. Grant and Joshua G. W. Bernstein An Object-based Interpretation of Audiovisual Processing Adrian K.C. Lee, Ross K. Maddox, and Jennifer K. Bizley Hearing in a "Moving" Visual World: Coordinate Transformations Along the Auditory Pathway Shawn M. Willett, Jennifer M. Groh, Ross K. Maddox Multisensory Processing in the Auditory Cortex Andrew J. King, Amy Hammond-Kenny, Fernando R. Nodal Audiovisual Integration in the Primate Prefrontal Cortex Bethany Plakke and Lizabeth M. Romanski Using Multisensory Integration to Understand Human Auditory Cortex Michael S. Beauchamp Combining Voice and Face Content in the Primate Temporal Lobe Catherine Perrodin and Christopher I. Petkov Neural Network Dynamics and Audiovisual Integration Julian Keil and Daniel Senkowski Cross-Modal Learning in the Auditory System Patrick Bruns and Brigitte Röder Multisensory Processing Differences in Individuals with Autism Spectrum Disorder Sarah H. Baum Miller, Mark T. Wallace Adrian K.C. Lee is Associate Professor in the Department of Speech & Hearing Sciences and the Institute for Learning and Brain Sciences at the University of Washington, Seattle Mark T. Wallace is the Louise B McGavock Endowed Chair and Professor in the Departments of Hearing and Speech Sciences, Psychiatry, Psychology and Director of the Vanderbilt Brain Institute at Vanderbilt University, Nashville Allison B. Coffin is Associate Professor in the Department of Integrative Physiology and Neuroscience at Washington State University, Vancouver, WA Arthur N. Popper is Professor Emeritus and research professor in the Department of Biology at the University of Maryland, College Park Richard R. Fay is Distinguished Research Professor of Psychology at Loyola University, Chicago.

Near-sensor and In-sensor Computing
Near-sensor and In-sensor Computing

Author: Yang Chai

Publisher: Springer Nature

Published: 2022-10-27

Total Pages: 237

ISBN-13: 3031115066

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This book provides a detailed introduction to near-sensor and in-sensor computing paradigms, their working mechanisms, development trends and future directions. The authors also provide a comprehensive review of current progress in this area, analyze existing challenges in the field, and offer possible solutions. Readers will benefit from the discussion of computing approaches that intervene in the vicinity of or inside sensory networks to help process data more efficiently, decreasing power consumption and reducing the transfer of redundant data between sensing and processing units. Provides readers with a detailed introduction to the near-sensor and in-sensor computing paradigms; Includes in-depth and comprehensive summaries of the state-of-the-art development in this field; Discusses and compares various neuromorphic sensors and neural networks: Describes integration technology for near-/in-sensor computing; Reveals the relationship between near-/in-sensor computing and other computing paradigms, such as neuromorphic computing, edge computing, intuitive computing, and in-memory computing.

Bayesian Brain
Bayesian Brain

Author: Kenji Doya

Publisher: MIT Press

Published: 2007

Total Pages: 341

ISBN-13: 026204238X

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Experimental and theoretical neuroscientists use Bayesian approaches to analyze the brain mechanisms of perception, decision-making, and motor control.