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Joel L. Davis

Joel L. Davis is Program Officer, Cognitive, Neural, and Biomolecular Science and Technology Division, Office of Naval Research.

Titles by This Editor

A Model System for Computational Neuroscience

Computational neuroscientists have recently turned to modeling olfactory structures because these are likely to have the same functional properties as currently popular network designs for perception and memory. This book provides a useful survey of current work on olfactory system circuitry, including connections of this system to brain structures involved in cognition and memory, and describes the computational models of olfactory processing that have been developed to date.

Contributions cover empirical investigations of the neurobiology of the olfactory systems (anatomy, physiology, synaptic plasticity, behavioral physiology) as well as the application of computer models to understanding these systems. Fundamental issues in olfactory processing by the nervous systems such as experimental strategies in the study of olfaction, stages of odor processing, and critical questions in sensory coding are considered across empirical/applied boundaries and throughout the contributions.

Contributors: 1. Fundamental Anatomy, Physiology, and Plasticity of the Olfactory System. Gordon M. Shepherd. John S. Kauer, S. R. Neff, Kathryn A. Hamilton, and Angel R. Cinelli. Kevin L. Ketchum, Lewis B. Haberly. Joseph L. Price, S. Thomas Carmichael, Ken M. Carnes, MarieChristine Clugnet, Masaru Kuroda, and James P. Ray. Michael Leon, Donald A. Wilson, and Kathleen M. Guthrie. Gary Lynch and Richard Granger. Howard Eichenbaum, Tim Otto, Cynthia Wible, and jean Piper. II. Developments in Computational Models of the Olfactory System. DeLiang Wang, Joachim Buhmann, and Christoph von der Marlsburg. Walter Freeman. Richard Granger, Ursula Staubi, José Ambrose-Ingersoll, and Gary Lynch. James M. Bower. Dan Hammerstrom and Eric Means.

Large-Scale Neuronal Theories of the Brain brings together thirteen original contributions by some of the top scientists working in neuroscience today. It presents models and theories that will most likely shape and influence the way we think about the brain, the mind, and interactions between the two in the years to come. Chapters consider global theories of the brain from the bottom up—providing theories that are based on real nerve cells, their firing properties, and their anatomical connections. This contrasts with attempts that have been made by psychologists and by theorists in the artificial intelligence community to understand the brain strictly from a psychological or computational point of view.

The authors encompass a broad background, from biophysics and electrophysiology to psychophysics, neurology, and computational vision. However, all the chapters focus on a common issue: the role of the primate (including human) cerebral cortex in memory, visual perception, focal attention, and awareness.

Contributors: Horace Barlow; Patricia Churchland; V. S. Ramachandran and Terrence J. Sejnowski; Antonio R. Damasio and Hanna Damasio; Robert Desimone, Earl K. Miller, and Leonardo Chelazzi; Christof Koch and Francis Crick; Rodolfo, R. Llinas, and Urs Ribary; David Mumford; Tomaso Poggio and Anya Hurlbert; Michael I. Posner and Mary K. Rothbart; Wolf Singer; Charles F. Stevens; Shimon Ullman; David C. Van Essen, Charles W. Anderson, and Bruno A. Olshausen.

Molecular, Cellular, and Functional Aspects

Synaptic Plasticity presents an up-to-date overview of the current status of research on the full scope of synaptic plasticity, including synaptic remodeling in response to damage, long-term depression and long-term potentiation, and learning and memory.The contributions are written by leading experts in the field and cover approaches from biochemical, anatomical, physiological, behavioral, and computational levels. They offer hypotheses concerning the molecular and cellular mechanisms that are responsible for the various manifestations of synaptic plasticity and propose models explaining how these cellular events can be linked to the functional and behavioral expressions of these adaptive principles.Michel Baudry is Associate Professor in the Department of Biological Sciences at the University of Southern California. Richard F. Thompson is Director of the Neuroscience Program and Keck Professor of Psychology and Biological Sciences at the University of Southern California. Joel L. Davis is Scientific Officer for Computational Neuroscience at the Office of Naval Research.Contents: Introduction. Molecular Correlates of Activity-dependent Development and Synaptic Plasticity, S. Hockfield. Molecular Sorting in Neurons, 0. Steward. Molecular and Morphological Responses to Deafferentation in Rodents, C. E. Finch, T. H. McNeill. Forms of Long-term Potentiation Induced by NMDA and Non–NMDA Receptor Activation, T. Teyler, L. Grover. Long-term Potentiation: Biochemical Mechanisms, M. Baudry, G. Lynch. Cerebellar Mechanisms of Long-Term Depression, M. Ito. Long-term Depression: Related Mechanisms in Cerebellum, Neocortex, and Hippocampus, A. Artola, W. Singer. Theory of Synaptic Plasticity in Visual Cortex, N. Intrator, M. F. Bear, L. N. Cooper, M. A. Paradiso. A Theoretical and Experimental Strategy for Realizing a Biologically Based Model of the Hippocampus, T. W. Berger et al. Synaptic Plasticity, Learning, and Memory, S. P. Rose. Synaptic Plasticity and Memory Storage, R. F. Thompson et al.

The goal of neurotechnology is to confer the performance advantages of animal systems on robotic machines. Biomimetic robots differ from traditional robots in that they are agile, relatively cheap, and able to deal with real-world environments. The engineering of these robots requires a thorough understanding of the biological systems on which they are based, at both the biomechanical and physiological levels.

This book provides an in-depth overview of the field. The areas covered include myomorphic actuators, which mimic muscle action; neuromorphic sensors, which, like animal sensors, represent sensory modalities such as light, pressure, and motion in a labeled-line code; biomimetic controllers, based on the relatively simple control systems of invertebrate animals; and the autonomous behaviors that are based on an animal's selection of behaviors from a species-specific behavioral "library." The ultimate goal is to develop a truly autonomous robot, one able to navigate and interact with its environment solely on the basis of sensory feedback without prompting from a human operator.

The neurobiology and psychology of attention have much to learn from each other. Neurobiologists recognize that responses in sensory cortex depend on the behavioral relevance of a stimulus, but have few ways to study how perception changes as a result. Psychologists have the conceptual and methodological tools to do just that, but are confounded by the multiple interpretations and theoretical ambiguities. This book attempts to bridge the two fields and to derive a comprehensive theory of attention from both neurobiological and psychological data. It highlights situations where attention can be seen to alter both neural activity and psychophysical performance/phenomenal experience. This "bicultural" approach contributes not only to attention research but to the larger goal of linking neural activity to conscious experience.

The book focuses mainly on the effects of visual attention on the ventral and dorsal streams of visual cortex in humans and monkeys and the associated changes in visual performance. Several larger findings emerge: attention may involve more than one neural system; attention modulates all stages of cortical visual processing; the effect of attention is constrained by the intrinsic connectivity of cortex and the resulting contextual interactions; and the notion of a "saliency map" remains central to thinking about visual attention. The book also considers several approaches to evaluating the same variable through different methods, such as behavioral measurements, functional imaging, and single-unit recording.

Narcisse P. Bichot, Erik Blaser, Geoffrey M. Boynton, Jochen Braun Maurizio Corbetta, Sean M. Culhane, Florin Cutzu, Sophie Deneve, Robert Desimone, John Duncan, Sunil P. Gandhi, Charles D. Gilbert, David J. Heeger, James W. Holsapple, Alexander C. Huk, Minami Ito, Laurent Itti, Christof Koch, Peter E. Latham, Nilli Lavie, D. Kathleen Lee, Zhong-Lin Lu, John H. R. Maunsell, Carrie J. McAdams, Brad C. Motter, Alexandre Pouget, Adam Reeves, John H. Reynolds, Jeffrey D. Schall, Christian Scheier, Shinsuke Shimojo, Gordon L. Shulman, George Sperling, Kirk G. Thompson, John K. Tsotsos, Katsumi Watanabe, Erich Weichselgartner, Gerald Westheimer.

Many neurons exhibit plasticity; that is, they can change structurally or functionally, often in a lasting way. Plasticity is evident in such diverse phenomena as learning and memory, brain development, drug tolerance, sprouting of axon terminals after a brain lesion, and various cellular forms of activity-dependent synaptic plasticity such as long-term potentiation and long-term depression. This book, a follow-up to the editors' Synaptic Plasticity (MIT Press, 1993), reports on the most recent trends in the field. The levels of analysis range from molecular to cellular and network, the unifying theme being the nature of the relationships between synaptic plasticity and information processing and storage.

Contributors: Yael Amitai, Michel Baudry, Theodore W. Berger, Pierre-Alain Buchs, A. K. Butler, Franck A. Chaillan, Gilbert A. Chauvet, Marie-Françoise Chesselet, Barry W. Connors, Taraneh Ghaffari, Jay R. Gibson, Ziv Gil, Michel Khrestchatisky, Dietmar Kuhl, Carole E. Landisman, Gilles Laurent, Jim-Shih Liaw, David J. Linden, Katrina MacLeod, Henry Markram, W. V. Morehouse, Dominique Muller, J. A. Napieralski, Santiago Rivera, François S. Roman, Bernard Soumireu-Mourat, Oswald Steward, Mark Stopfer, F. G. Szele, Richard F. Thompson, Nicolas Toni, Bernard Truchet, Misha Tsodyks, K. Uryu, Ascher Uziel, Christopher S. Wallace, Yun Wang, Michael Wehr, Paul F. Worley, Xiaping Xie.

This is the third volume in a series of books devoted to the mechanisms and functional significance of two forms of synaptic plasticity, Long-Term Potentiation (LTP) and Long-Term Depression (LTD), which are widely assumed to play critical roles in information processing and storage in the brain. Long-Term Potentiation offers the most recent hypotheses concerning the molecular and cellular mechanisms underlying LTP and LTD, discusses the functional significance of LTP and LTD in neuronal networks, and reviews several examples of network simulations incorporating LTP- and LTD-like rules of synaptic modification.

The book is organized into several sections covering different aspects of the field ranging from molecular and cellular processes to network models. The often deliberately controversial contributions are from the leading laboratories in the field and reflect contemporary multidisciplinary approaches.

Recent years have seen a remarkable expansion of knowledge about the anatomical organization of the part of the brain known as the basal ganglia, the signal processing that occurs in these structures, and the many relations both to molecular mechanisms and to cognitive functions. This book brings together the biology and computational features of the basal ganglia and their related cortical areas along with select examples of how this knowledge can be integrated into neural network models.

Organized in four parts—fundamentals, motor functions and working memories, reward mechanisms, and cognitive and memory operations—the chapters present a unique admixture of theory, cognitive psychology, anatomy, and both cellular- and systems- level physiology written by experts in each of these areas. The editors have provided commentaries as a helpful guide to each part.

Many new discoveries about the biology of the basal ganglia are summarized, and their impact on the computational role of the forebrain in the planning and control of complex motor behaviors discussed. The various findings point toward an unexpected role for the basal ganglia in the contextual analysis of the environment and in the adaptive use of this information for the planning and execution of intelligent behaviors. Parallels are explored between these findings and new connectionist approaches to difficult control problems in robotics and engineering.

James L. Adams, P. Apicella, Michael Arbib, Dana H. Ballard, Andrew G. Barto, J. Brian Burns, Christopher I. Connolly, Peter F. Dominey, Richard P. Dum, John Gabrieli, M. Garcia-Munoz, Patricia S. Goldman-Rakic, Ann M. Graybiel, P. M. Groves, Mary M. Hayhoe, J. R. Hollerman, George Houghton, James C. Houk, Stephen Jackson, Minoru Kimura, A. B. Kirillov, Rolf Kotter, J. C. Linder, T. Ljungberg, M. S. Manley, M. E. Martone, J. Mirenowicz, C. D. Myre, Jeff Pelz, Nathalie Picard, R. Romo, S. F. Sawyer, E. Scarnati, Wolfram Schultz, Peter L. Strick, Charles J. Wilson, Jeff Wickens, Donald J. Woodward, S. J. Young.