Depth Perception in Frogs and Toads provides a comprehensive exploration of the phenomenon of depth perception in frogs and toads, as seen from a neuro-computational point of view. Perhaps the most important feature of the book is the development and presentation of two neurally realizable depth perception algorithms that utilize both monocular and binocular depth cues in a cooperative fashion. One of these algorithms is specialized for computation of depth maps for navigation, and the other for the selection and localization of a single prey for prey catching. The book is also unique in that it thoroughly reviews the known neuroanatomical, neurophysiological and behavioral data, and then synthesizes, organizes and interprets that information to explain a complex sensory-motor task. The book will be of special interest to that segment of the neural computing community interested in understanding natural neurocomputational structures, particularly to those working in perception and sensory-motor coordination. It will also be of interest to neuroscientists interested in exploring the complex interactions between the neural substrates that underly perception and behavior.

Depth Perception in Frogs and Toads provides a comprehensive exploration of the phenomenon of depth perception in frogs and toads, as seen from a neuro-computational point of view. Perhaps the most important feature of the book is the development and presentation of two neurally realizable depth perception algorithms that utilize both monocular and binocular depth cues in a cooperative fashion. One of these algorithms is specialized for computation of depth maps for navigation, and the other for the selection and localization of a single prey for prey catching. The book is also unique in that it thoroughly reviews the known neuroanatomical, neurophysiological and behavioral data, and then synthesizes, organizes and interprets that information to explain a complex sensory-motor task. The book will be of special interest to that segment of the neural computing community interested in understanding natural neurocomputational structures, particularly to those working in perception and sensory-motor coordination. It will also be of interest to neuroscientists interested in exploring the complex interactions between the neural substrates that underly perception and behavior.

The three-volume work Perceiving in Depth is a sequel to Binocular Vision and Stereopsis and to Seeing in Depth, both by Ian P. Howard and Brian J. Rogers. This work is much broader in scope than the previous books and includes mechanisms of depth perception by all senses, including aural, electrosensory organs, and the somatosensory system. Volume 1 reviews sensory coding, psychophysical and analytic procedures, and basic visual mechanisms. Volume 2 reviews stereoscopic vision. Volume 3 reviews all mechanisms of depth perception other than stereoscopic vision. The three volumes are extensively illustrated and referenced and provide the most detailed review of all aspects of perceiving the three-dimensional world. Volume 3 addresses all depth-perception mechanisms other than stereopsis. The book starts with an account of monocular cues to depth, including accommodation, vergence eye movements, perspective, interposition, shading, and motion parallax. A chapter on constancies in depth perception, such as the ability to perceive the sizes and shapes of objects as they move or rotate in depth, is followed by a chapter on the ways in which depth cues interact. The next chapter reviews sources of information, such as changing disparity, image looming, and vergence eye movements, used in the perception of objects moving in depth. Various pathologies of depth perception, including visual neglect, stereoanomalies, and albanism are reviewed. Visual depth-perception mechanisms through the animal kingdom are described, starting with insects and progressing through crustaceans, fish, amphibians, reptiles, birds, and mammals. The chapter includes a discussion of how stereoscopic vision may have evolved. The next chapter describes how visual depth perception is used to guide reaching movements of the hand, avoiding obstacles, and walking to a distant object. The next three chapters review non-visual mechanisms of depth perception. Auditory mechanisms include auditory localization, echolocation in bats and marine mammals, and the lateral-line system of fish. Some fish emit electric discharges and then use electric sense organs to detect distortions of the electric field produced by nearby objects. Some beetles and snakes use heat-sensitive sense organs to detect sources of heat. The volume ends with a discussion of mechanisms used by animals to navigate to a distant site. Ants find their way back to the nest by using landmarks and by integrating their walking movements. Several animals navigate by the stars or by polarized sunlight. It seems that animals in several phyla navigate by detecting the Earths magnetic field.

The science associated with the development of artificial sen sory systems is occupied primarily with determining how information about the world can be extracted from sensory data. For example, computational vision is, for the most part, concerned with the de velopment of algorithms for distilling information about the world and recognition of various objects in the environ (e. g. localization ment) from visual images (e. g. photographs or video frames). There are often a multitude of ways in which a specific piece of informa tion about the world can be obtained from sensory data. A subarea of research into sensory systems has arisen which is concerned with methods for combining these various information sources. This field is known as data fusion, or sensor fusion. The literature on data fusion is extensive, indicating the intense interest in this topic, but is quite chaotic. There are no accepted approaches, save for a few special cases, and many of the best methods are ad hoc. This book represents our attempt at providing a mathematical foundation upon which data fusion algorithms can be constructed and analyzed. The methodology that we present in this text is mo tivated by a strong belief in the importance of constraints in sensory information processing systems. In our view, data fusion is best un derstood as the embedding of multiple constraints on the solution to a sensory information processing problem into the solution pro cess.

The goal of this book is to put together some of the main interdisciplinary aspects that play a role in visual attention and cognition. The book is aimed at researchers and students with interdisciplinary interest. In the first chapter a general discussion of the influential scanpath theory and its implications for human and robot vision is presented. Subsequently, four characteristic aspects of the general theme are dealt with in topical chapters, each of which presents some of the different viewpoints of the various disciplines involved. They cover neuropsychology, clinical neuroscience, modeling, and applications. Each of the chapters opens with a synopsis tying together the individual contributions.

Various brain areas of mammals can phyletically be traced back to homologous structures in amphibians. The amphibian brain may thus be regarded as a kind of "microcosm" of the highly complex primate brain, as far as certain homologous structures, sensory functions, and assigned ballistic (pre-planned and pre-pro grammed) motor and behavioral processes are concerned. A variety of fundamental operations that underlie perception, cognition, sensorimotor transformation and its modulation appear to proceed in primate's brain in a way understandable in terms of basic principles which can be investigated more easily by experiments in amphibians. We have learned that progress in the quantitative description and evaluation of these principles can be obtained with guidance from theory. Modeling - supported by simulation - is a process of transforming abstract theory derived from data into testable structures. Where empirical data are lacking or are difficult to obtain because of structural constraints, the modeler makes assumptions and approximations that, by themselves, are a source of hypotheses. If a neural model is then tied to empirical data, it can be used to predict results and hence again to become subject to experimental tests whose resulting data in tum will lead to further improvements of the model. By means of our present models of visuomotor coordination and its modulation by state-dependent inputs, we are just beginning to simulate and analyze how external information is represented within different brain structures and how these structures use these operations to control adaptive behavior.

Development of Perception: Psychobiological Perspectives, Volume 2, The Visual System, is the second of two-part series covering vision, audition, olfaction, taste, tactile sensitivity, and sensory-motor activity during ontogenesis. The focus is on approaches to perceptual development that incorporate a psychobiological perspective. The present volume brings together several topics of critical importance to the process of understanding the visual system. The book is organized into three parts. Part A addresses the theoretical and interpretive issues involved in designing and drawing conclusions from research on the development of the visual system. Part B on animal studies of visual development covers the neural and behavioral characteristics of the cat and monkey visual system during the early postnatal period. Part C examines visual development in human infants. Together, these three parts offer a comprehensive coverage of major issues in the structure and function of the developing mammalian visual system. Each chapter emphasizes the behavioral consequences of developing visual functions.

More than sixty contributions in From Animals to Animats 2 byresearchers in ethology, ecology, cybernetics, artificial intelligence, robotics, and related fieldsinvestigate behaviors and the underlying mechanisms that allow animals and, potentially, robots toadapt and survive in uncertain environments. Jean-Arcady Meyer is Director of Research, CNRS, Paris.Herbert L. Roitblat is Professor of Psychology at the University of Hawaii at Manoa. Stewart W.Wilson is a scientist at The Rowland Institute for Science, Cambridge,Massachusetts. Topics covered: The Animat Approach to Adaptive Behavior,Perception and Motor Control, Action Selection and Behavioral Sequences, Cognitive Maps and InternalWorld Models, Learning, Evolution, Collective Behavior.