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 Networkscharts the immense progress made in recent years in many specific areas related to two great questions: How does the brain work? and How can we build intelligent machines? While many books have appeared on limited aspects of one subfield or another of brain theory and neural networks, the (...) Handbookcovers 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. The excitement, and the frustration, of these topics is that they span such a broad range of disciplines including mathematics, statistical physics and chemistry, neurology and neurobiology, and computer science and electrical engineering as well as cognitive psychology, artificial intelligence, and philosophy. Thus, much effort has gone into making the Handbookaccessible to readers with varied backgrounds while still providing a clear view of much of the recent, specialized research in specific topics. The heart of the book, part III, comprises of 267 original articles by leaders in the various fields, arranged alphabetically by title. Parts I and II, written by the editor, are designed to help readers orient themselves to this vast range of material. Part I, Background, introduces several basic neural models, explains how the present study of brain theory and neural networks integrates brain theory, artificial intelligence, and cognitive psychology, and provides a tutorial on the concepts essential for understanding neural networks as dynamic, adaptive systems. Part II, Road Maps, provides entry into the many articles of part III through an introductory "Meta-Map" and twenty-three road maps, each of which tours all the Part III articles on the chosen theme. (shrink)

We focus on the evolution of action capabilities which set the stage for language, rather than analyzing how further brain evolution built on these capabilities to yield a language-ready brain. Our framework is given by the Mirror System Hypothesis, which charts a progression from a monkey-like mirror neuron system (MNS) to a chimpanzee-like mirror system that supports simple imitation and thence to a human-like mirror system that supports complex imitation and language. We present the MNS2 model, a new model of (...) action recognition learning by mirror neurons of the macaque brain and augmented competitive queuing, a model of opportunistic scheduling of action sequences as background for analysis of modeling strategies for simple imitation as seen in the great apes and complex/goal-directed imitation as seen in humans. Implications for the study of language are briefly noted. (shrink)

马忠林(1914~ ),东北师范大学数学系教授,中国数学会会员,吉林省数学会常务理事,日本三大学数学教育学研究会名誉会长.

Neural organization: Structure, function, and dynamics shows how theory and experiment can supplement each other in an integrated, evolving account of the brain's structure, function, and dynamics. Structure: Studies of brain function and dynamics build on and contribute to an understanding of many brain regions, the neural circuits that constitute them, and their spatial relations. We emphasize Szentágothai's modular architectonics principle, but also stress the importance of the microcomplexes of cerebellar circuitry and the lamellae of hippocampus. Function: Control of eye (...) movements, reaching and grasping, cognitive maps, and the roles of vision receive a functional decomposition in terms of schemas. Hypotheses as to how each schema is implemented through the interaction of specific brain regions provide the basis for modeling the overall function by neural networks constrained by neural data. Synthetic PET integrates modeling of primate circuitry with data from human brain imaging. Dynamics: Dynamic system theory analyzes spatiotemporal neural phenomena, such as oscillatory and chaotic activity in both single neurons and neural networks, the self-organizing development and plasticity of ordered neural structures, and learning and memory phenomena associated with synaptic modification. Rhythm generation involves multiple levels of analysis, from intrinsic cellular processes to loops involving multiple brain regions. A variety of rhythms are related to memory functions. The Précis presents a multifaceted case study of the hippocampus. We conclude with the claim that language and other cognitive processes can be fruitfully studied within the framework of neural organization that the authors have charted with John Szentágothai. (shrink)

In this book, Michael Arbib, a researcher in artificial intelligence and brain theory, joins forces with Mary Hesse, a philosopher of science, to present an integrated account of how humans 'construct' reality through interaction with the social and physical world around them. The book is a major expansion of the Gifford Lectures delivered by the authors at the University of Edinburgh in the autumn of 1983. The authors reconcile a theory of the individual's construction of reality as a network (...) of schemas 'in the head' with an account of the social construction of language, science, ideology and religion to provide an integrated schema-theoretic view of human knowledge. The authors still find scope for lively debate, particularly in their discussion of free will and of the reality of God. The book integrates an accessible exposition of background information with a cumulative marshalling of evidence to address fundamental questions concerning human action in the world and the nature of ultimate reality. (shrink)

How might a human communication system be bootstrapped in the absence of conventional language? We argue that motivated signs play an important role (i.e., signs that are linked to meaning by structural resemblance or by natural association). An experimental study is then reported in which participants try to communicate a range of pre-specified items to a partner using repeated non-linguistic vocalization, repeated gesture, or repeated non-linguistic vocalization plus gesture (but without using their existing language system). Gesture proved more effective (measured (...) by communication success) and more efficient (measured by the time taken to communicate) than non-linguistic vocalization across a range of item categories (emotion, object, and action). Combining gesture and vocalization did not improve performance beyond gesture alone. We experimentally demonstrate that gesture is a more effective means of bootstrapping a human communication system. We argue that gesture outperforms non-linguistic vocalization because it lends itself more naturally to the production of motivated signs. (shrink)

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. (shrink)

The article analyzes the neural and functional grounding of language skills as well as their emergence in hominid evolution, hypothesizing stages leading from abilities known to exist in monkeys and apes and presumed to exist in our hominid ancestors right through to modern spoken and signed languages. The starting point is the observation that both premotor area F5 in monkeys and Broca's area in humans contain a “mirror system” active for both execution and observation of manual actions, and that F5 (...) and Broca's area are homologous brain regions. This grounded the mirror system hypothesis of Rizzolatti and Arbib (1998) which offers the mirror system for grasping as a key neural “missing link” between the abilities of our nonhuman ancestors of 20 million years ago and modern human language, with manual gestures rather than a system for vocal communication providing the initial seed for this evolutionary process. The present article, however, goes “beyond the mirror” to offer hypotheses on evolutionary changes within and outside the mirror systems which may have occurred to equip Homo sapiens with a language-ready brain. Crucial to the early stages of this progression is the mirror system for grasping and its extension to permit imitation. Imitation is seen as evolving via a so-called simple system such as that found in chimpanzees (which allows imitation of complex “object-oriented” sequences but only as the result of extensive practice) to a so-called complex system found in humans (which allows rapid imitation even of complex sequences, under appropriate conditions) which supports pantomime. This is hypothesized to have provided the substrate for the development of protosign, a combinatorially open repertoire of manual gestures, which then provides the scaffolding for the emergence of protospeech (which thus owes little to nonhuman vocalizations), with protosign and protospeech then developing in an expanding spiral. It is argued that these stages involve biological evolution of both brain and body. By contrast, it is argued that the progression from protosign and protospeech to languages with full-blown syntax and compositional semantics was a historical phenomenon in the development of Homo sapiens, involving few if any further biological changes. Key Words: gestures; hominids; language evolution; mirror system; neurolinguistics; primates; protolanguage; sign language; speech; vocalization. (shrink)

A new, dramatically updated edition of the classic resource on the constantly evolving fields of brain theory and neural networks.

An introduction to Jean-Luc Marion's philosophical and theological work in the form of a conversation with the author. Marion reflects on major 20th century French figures and their varied influence on his work, while giving an overview of his writings in the history of philosophy, theology, and phenomenology.

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. (shrink)

Thirty years ago, I elaborated on a position that could be seen as a compromise between an "extreme," symbol-based AI, and a "neurochemical reductionism" in AI. The present article recalls aspects of the espoused framework of schema theory that, it suggested, could provide a better bridge from human psychology to brain theory than that offered by the symbol systems of A. Newell and H. A. Simon.

Intermediate constructs are required as bridges between complex behaviors and realistic models of neural circuitry. For cognitive scientists in general, schemas are the appropriate functional units; brain theorists can work with neural layers as units intermediate between structures subserving schemas and small neural circuits.After an account of different levels of analysis, we describe visuomotor coordination in terms of perceptual schemas and motor schemas. The interest of schemas to cognitive science in general is illustrated with the example of perceptual schemas in (...) high-level vision and motor schemas in the control of dextrous hands.Rana computatrix, the computational frog, is introduced to show how one constructs an evolving set of model families to mediate flexible cooperation between theory and experiment. Rana computatrix may be able to do for the study of the organizational principles of neural circuitry what Aplysia has done for the study of subcellular mechanisms of learning. Approach, avoidance, and detour behavior in frogs and toads are analyzed in terms of interacting schemas. Facilitation and prey recognition are implemented as tectal-pretectal interactions, with the tectum modeled by an array of tectal columns. We show how layered neural computation enters into models of stereopsis and how depth schemas may involve the interaction of accommodation and binocular cues in anurans. (shrink)

Quelle place l'infinité divine occupe-t-elle dans la philosophie cartésienne? Peut-elle éclairer la situation de Descartes dans le temps long de l'histoire de la métaphysique ou révéler une béance toujours sise au coeur de son concept? Loin d'être une innovation cartésienne, l'infinité de Dieu constitue une conquête de l'histoire de la métaphysique, qui, en prenant pour objet le concept d'ens, s'est approprié Dieu sous la figure de l'ens infinitum. Et parce que la philosophia prima des Meditationes a pour premier principe le (...) cogito, l'idea infiniti ne peut que s'ordonner à l'univocité de la cogitatio et se soumettre au régime métaphysique de la représentation, qu'elle prolonge et accomplit. Mais Descartes confère à l'infini une autre détermination, qui contredit sa portée métaphysique : car, en toute rigueur, l'infini ne se donne pas tant en une représentation, qu'il n'excède toute représentation pour la conditionner. Ainsi Descartes démontre-t-il l'existence de Dieu au moyen du nom qui énonce d'abord sa transcendance à toute démonstration ; ainsi l'idée d'infini est-elle plus "lourde" que l'ego qui la porte et qu'elle creuse d'une antériorité à jamais irrécupérable. Descartes a donc associé en un même nom - l'infini - une détermination métaphysique et une détermination non métaphysique de Dieu. Mais cette double détermination traduit l'ambiguïté même de l'infini dans l'histoire de la métaphysique, s'il est vrai que c'est aussi bien comme infini que Dieu y est entré (Duns Scot) et qu'il en est sorti (Levinas). L'infinité divine peut dès lors accomplir chez Descartes la sortie de la métaphysique depuis la métaphysique elle-même, puisqu'elle nomme l'au-delà de la représentation apparu depuis la représentation : la métaphysique se trouverait alors contemporaine de sa fin, qui toujours en sourdine la double et la défait. En la déployant sans nuances, Descartes fait accéder à sa visibilité la plus haute l'ambiguïté de l'infini : sa métaphysique en acquiert une ambivalence à laquelle nous n'avons pas voulu demeurer aveugle. D. A. (shrink)

Quel type de releve pour la metaphysique l'ethique envisagee comme - philosophie premiere - propose-t-elle? La phenomenologie peut-elle ressaisir le fondement de tout phenomene, obeir a une demarche encore transcendantale tout en destituant l'ego de sa principialite sans cesse reconduite depuis Descartes? La requalification des categories theologiques imposee par la distance de l'autrement qu'etre peut-elle laisser inchange le nom meme de Dieu auquel elle nous ordonne comme a notre definitive tache? Ces questions, Levinas aura contribue a les formaliser et a (...) en imposer l'urgence avec une radicalite a nulle autre pareille. Cet ouvrage se propose d'en eclairer quelques unes a partir d'analyses genetiques de sa pensee, de confrontations avec quelques hautes figures de la tradition philosophique (Husserl et Heidegger, mais aussi Descartes, Spinoza, Derrida, etc.) et de la reactivation de quaestiones disputatae lourdes d'enjeux. Car l'ethique dispense une lumiere propre, sans laquelle nombre de questions nous resteraient durablement insoupconnees; cette lumiere elle-meme doit etre decomposee et se preter a analyse. Lumiere jetee par l'ethique, lumiere jetee sur l'ethique: telle est, en son double genitif, la lucidite de l'ethique.". (shrink)

Computational modeling of the macaque brain grounds hypotheses on the brain of LCA-m. Elaborations thereof provide a brain model for LCA-c. The Mirror System Hypothesis charts further steps via imitation and pantomime to protosign and protolanguage on the path to a "language-ready brain" in Homo sapiens, with the path to speech being indirect. The material poses new challenges for both experimentation and modeling.