Juhani Pallasmaa

Michael A. Arbib

Harry Francis Mallgrave

Architecture and Neuroscience

Associate Professor in the Department of Electrical and Computer Engineering Leonard S Bobrow

Leonard S. Bobrow

Discrete Mathematics: Applied Algebra for Computer and Information Science

A presentation of music and language within an integrative, embodied perspective of brain mechanisms for action, emotion, and social coordination. This book explores the relationships between language, music, and the brain by pursuing four key themes and the crosstalk among them: song and dance as a bridge between music and language; multiple levels of structure from brain to behavior to culture; the semantics of internal and external worlds and the role of emotion; and the evolution and development of language. The book offers specially commissioned expositions of current research accessible both to experts across disciplines and to non-experts. These chapters provide the background for reports by groups of specialists that chart current controversies and future directions of research on each theme. The book looks beyond mere auditory experience, probing the embodiment that links speech to gesture and music to dance. The study of the brains of monkeys and songbirds illuminates hypotheses on the evolution of brain mechanisms that support music and language, while the study of infants calibrates the developmental timetable of their capacities. The result is a unique book that will interest any reader seeking to learn more about language or music and will appeal especially to readers intrigued by the relationships of language and music with each other and with the brain. Contributors Francisco Aboitiz, Michael A. Arbib, Annabel J. Cohen, Ian Cross, Peter Ford Dominey, W. Tecumseh Fitch, Leonardo Fogassi, Jonathan Fritz, Thomas Fritz, Peter Hagoort, John Halle, Henkjan Honing, Atsushi Iriki, Petr Janata, Erich Jarvis, Stefan Koelsch, Gina Kuperberg, D. Robert Ladd, Fred Lerdahl, Stephen C. Levinson, Jerome Lewis, Katja Liebal, Jônatas Manzolli, Bjorn Merker, Lawrence M. Parsons, Aniruddh D. Patel, Isabelle Peretz, David Poeppel, Josef P. Rauschecker, Nikki Rickard, Klaus Scherer, Gottfried Schlaug, Uwe Seifert, Mark Steedman, Dietrich Stout, Francesca Stregapede, Sharon Thompson-Schill, Laurel Trainor, Sandra E. Trehub, Paul Verschure

A Mysterious Relationship

Language, Music, and the Brain

Choice Outstanding Academic Title, 1996. In hundreds of articles by experts from around the world, and in overviews and "road maps" prepared by the editor, The Handbook of Brain Theory and Neural Networks charts the immense progress made in recent years in many specific areas related to great questions: How does the brain work? How can we build intelligent machines? While many books discuss limited aspects of one subfield or another of brain theory and neural networks, the Handbook covers the entire sweep of topics—from detailed models of single neurons, analyses of a wide variety of biological neural networks, and connectionist studies of psychology and language, to mathematical analyses of a variety of abstract neural networks, and technological applications of adaptive, artificial neural networks. Expository material makes the book accessible to readers with varied backgrounds while still offering a clear view of the recent, specialized research on specific topics.

The Handbook of Brain Theory and Neural Networks

Neurosciences Research Program

János Szentágothai

A Report Based on an NRP Work Session Held October 1-3, 1972, and Updated by Participants

Conceptual Models of Neural Organization

Ernest G. Manes

In the 1930s, mathematical logicians studied the notion of "effective comput ability" using such notions as recursive functions, A-calculus, and Turing machines. The 1940s saw the construction of the first electronic computers, and the next 20 years saw the evolution of higher-level programming languages in which programs could be written in a convenient fashion independent (thanks to compilers and interpreters) of the architecture of any specific machine. The development of such languages led in turn to the general analysis of questions of syntax, structuring strings of symbols which could count as legal programs, and semantics, determining the "meaning" of a program, for example, as the function it computes in transforming input data to output results. An important approach to semantics, pioneered by Floyd, Hoare, and Wirth, is called assertion semantics: given a specification of which assertions (preconditions) on input data should guarantee that the results satisfy desired assertions (postconditions) on output data, one seeks a logical proof that the program satisfies its specification. An alternative approach, pioneered by Scott and Strachey, is called denotational semantics: it offers algebraic techniques for characterizing the denotation of (i. e. , the function computed by) a program-the properties of the program can then be checked by direct comparison of the denotation with the specification. This book is an introduction to denotational semantics. More specifically, we introduce the reader to two approaches to denotational semantics: the order semantics of Scott and Strachey and our own partially additive semantics.

Algebraic Approaches to Program Semantics

Pablo Rudomin

Francisco Cervantes-Perez

Ranulfo Romo

The Central Nervous System can be considered as an aggregate of neurons specialized in both the transmission and transformation of information. Information can be used for many purposes, but probably the most important one is to generate a representation of the "external" world that allows the organism to react properly to changes in its external environment. These functions range from such basic ones as detection of changes that may lead to tissue damage and eventual destruction of the organism and the implementation of avoidance reactions, to more elaborate representations of the external world implying recognition of shapes, sounds and textures as the basis of planned action or even reflection. Some of these functions confer a clear survival advantage to the organism (prey or mate recognition, escape reactions, etc. ). Others can be considered as an essential part of cognitive processes that contribute, to varying degrees, to the development of individuality and self-consciousness. How can we hope to understand the complexity inherent in this range of functionalities? One of the distinguishing features of the last two decades has been the availability of computational power that has impacted many areas of science. In neurophysiology, computation is used for experiment control, data analysis and for the construction of models that simulate particular systems. Analysis of the behavior of neuronal networks has transcended the limits of neuroscience and is now a discipline in itself, with potential applications both in the neural sciences and in computing sciences.

Proceedings of a U.S.-Mexico Seminar held in the city of Xalapa in the state of Veracruz on December 9–11, 1991

Neuroscience: From Neural Networks to Artificial Intelligence

Jorg Peter Ewert

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.

Amphibians, Comparisons, Models, and Robots

Visuomotor Coordination

Jörg-Peter Ewert

This volume integrates theory and experiment to place the study of vision within the context of the action systems which use visual information. This theme is developed by stressing: (a) The importance of situating anyone part of the brain in the context of its interactions with other parts of the brain in subserving animal behavior. The title of this volume emphasizes that visual function is to be be viewed in the context of the integrated functions of the organism. (b) Both the intrinsic interest of frog and toad as animals in which to study the neural mechanisms of visuomotor coordination, and the importance of comparative studies with other organisms so that we may learn from an analysis of both similarities and differences. The present volume thus supplements our studies of frog and toad with papers on salamander, bird and reptile, turtle, rat, gerbil, rabbit, and monkey. (c) Perhaps most distinctively, the interaction between theory and experiment.

Visual Structures and Integrated Functions

Suad Alagic

The major goal of this book is to present the techniques of top-down program design and verification of program correctness hand-in-hand. It thus aims to give readers a new way of looking at algorithms and their design, synthesizing ten years of research in the process. It provides many examples of program and proof development with the aid of a formal and informal treatment of Hoare's method of invariants. Modem widely accepted control structures and data structures are explained in detail, together with their formal definitions, as a basis for their use in the design of correct algorithms. We provide and apply proof rules for a wide range of program structures, including conditionals, loops, procedures and recur sion. We analyze situations in which the restricted use of gotos can be justified, providing a new approach to proof rules for such situations. We study several important techniques of data structuring, including arrays, files, records and linked structures. The secondary goal of this book is to teach the reader how to use the programming language Pascal. This is the first text to teach Pascal pro gramming in a fashion which not only includes advanced algorithms which operate on advanced data structures, but also provides the full axiomatic definition of Pascal due to Wirth and Hoare. Our approach to the language is very different from that of a conventional programming text.

The Design of Well-Structured and Correct Programs

Jean-Marc Fellous

Designed by experts in neuroscience and artificial intelligence, this book provides chapters that address questions concerning human and animal emotions, and their possible analogs in the "brains" of robots. It is intended for researchers and graduate students in neuroscience, cognitive science, psychology, robotics and artificial intelligence.

The Brain Meets the Robot

Who Needs Emotions?

Unlike any other species, humans can learn and use language. In this book, Michael Arbib presents the Mirror System Hypothesis, which suggests how complex imitation supported the breakthrough to pantomime, protosign and protospeech and then, through cultural evolution, to fully fledged languages.

The Mirror System Hypothesis

How the Brain Got Language

Mirror neurons may hold the brain's key to social interaction - each coding not only a particular action or emotion but also the recognition of that action or emotion in others. The Mirror System Hypothesis adds an evolutionary arrow to the story - from the mirror system for hand actions, shared with monkeys and chimpanzees, to the uniquely human mirror system for language. In this accessible volume, experts from child development, computer science, linguistics, neuroscience, primatology and robotics present and analyse the mirror system and show how studies of action and language can illuminate each other. Topics discussed in the fifteen chapters include: what do chimpanzees and humans have in common? Does the human capability for language rest on brain mechanisms shared with other animals? How do human infants acquire language? What can be learned from imaging the human brain? How are sign- and spoken-language related? Will robots learn to act and speak like humans?

Action to Language via the Mirror Neuron System

James J. Bonaiuto

A comprehensive, integrated, and accessible textbook presenting core neuroscientific topics from a computational perspective, tracing a path from cells and circuits to behavior and cognition.

From Neuron to Cognition Via Computational Neuroscience

Prudence H. Arbib

Fletcher Jones Professor of Computer Science and Professor of Biological Sciences Biomedical Engineering Neuroscience and Psychology Michael A Arbib

This second edition presents the enormous progress made in recent years in the many subfields related to the two great questions: how does the brain work? and, How can we build intelligent machines? This second edition greatly increases the coverage of models of fundamental neurobiology, cognitive neuroscience, and neural network approaches to language. (Midwest).

Michael Arbib presents When Brains Meet Buildings as an invitation to the science behind architecture, richly illustrated with buildings both famous and domestic. As he converses with the reader, he presents action-oriented perception, memory, and imagination as well as atmosphere, aesthetics, and emotion as keys to analyzing the experience and design of architecture.

When Brains Meet Buildings

The idea that some day robots may have emotions has captured the imagination of many and has been dramatized by robots and androids in such famous movies as 2001 Space Odyssey's HAL or Star Trek's Data. By contrast, the editors of this book have assembled a panel of experts in neuroscience and artificial intelligence who have dared to tackle the issue of whether robots can have emotions from a purely scientific point of view. The study of the brain now usefully informs study of the social, communicative, adaptive, regulatory, and experimental aspects of emotion and offers support for the idea that we exploit our own psychological responses in order to feel others' emotions. The contributors show the many ways in which the brain can be analyzed to shed light on emotions. Fear, reward, and punishment provide structuring concepts for a number of investigations. Neurochemistry reveals the ways in which different "neuromodulators" such as serotonin, dopamine, and opioids can affect the emotional valence of the brain. And studies of different regions such as the amygdala and orbitofrontal cortex provide a view of the brain as a network of interacting subsystems. Related studies in artificial intelligence and robotics are discussed and new multi-level architectures are proposed that make it possible for emotions to be implemented. It is now an accepted task in robotics to build robots that perceive human expressions of emotion and can "express" simulated emotions to ease interactions with humans. Looking towards future innovations, some scientists posit roles for emotion with our fellow humans. All of these issues are covered in this timely and stimulating book which is written for researchers and graduated students in neuroscience, cognitive science, psychology, robotics, and artificial intelligence.

Michael A. Arbib

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