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This volume collects together peer reviewed versions of most of the papers presented at the Ninth Neural Computation and Psychology Workshop (NCPW9), held in 2004 at the University of Plymouth (England). The conference invited submissions on neural computation models of all cognitive and psychological processes. The special theme of this year's workshop was “Modeling of Language, Cognition and Action. This topic had the aim to extend the conference appeal from the connectionist psychology community to leaders in neuroscience, robotics and cognitive systems design.The chapters cover the breadth of research in neural computation and psychology, with numerous papers that focus on language modeling, this year's special theme. The book includes chapters from internationally renowned researchers in the various fields of cognitive psychology (such as Art Glenberg and Jonathan Evans) as well as computer science and robotics (such as Stefan Wermter & Stefano Nolfi).The proceedings have been selected for coverage in:• Neuroscience Citation Index®• Index to Scientific & Technical Proceedings® (ISTP® / ISI Proceedings)• Index to Scientific & Technical Proceedings (ISTP CDROM version / ISI Proceedings)• Index to Social Sciences & Humanities Proceedings® (ISSHP® / ISI Proceedings)• Index to Social Sciences & Humanities Proceedings (ISSHP CDROM version / ISI Proceedings)• CC Proceedings — Engineering & Physical Sciences• CC Proceedings — Biomedical, Biological & Agricultural Sciences
How do infants learn a language? Why and how do languages evolve? How do we understand a sentence? This book explores these questions using recent computational models that shed new light on issues related to language and cognition. The chapters in this collection propose original analyses of specific problems and develop computational models that have been tested and evaluated on real data. Featuring contributions from a diverse group of experts, this interdisciplinary book bridges the gap between natural language processing and cognitive sciences. It is divided into three sections, focusing respectively on models of neural and cognitive processing, data driven methods, and social issues in language evolution. This book will be useful to any researcher and advanced student interested in the analysis of the links between the brain and the language faculty.
This open access book introduces a general framework that allows natural language researchers to enhance existing competence theories with fully specified performance and processing components. Gradually developing increasingly complex and cognitively realistic competence-performance models, it provides running code for these models and shows how to fit them to real-time experimental data. This computational cognitive modeling approach opens up exciting new directions for research in formal semantics, and linguistics more generally, and offers new ways of (re)connecting semantics and the broader field of cognitive science. The approach of this book is novel in more ways than one. Assuming the mental architecture and procedural modalities of Anderson's ACT-R framework, it presents fine-grained computational models of human language processing tasks which make detailed quantitative predictions that can be checked against the results of self-paced reading and other psycho-linguistic experiments. All models are presented as computer programs that readers can run on their own computer and on inputs of their choice, thereby learning to design, program and run their own models. But even for readers who won't do all that, the book will show how such detailed, quantitatively predicting modeling of linguistic processes is possible. A methodological breakthrough and a must for anyone concerned about the future of linguistics! (Hans Kamp) This book constitutes a major step forward in linguistics and psycholinguistics. It constitutes a unique synthesis of several different research traditions: computational models of psycholinguistic processes, and formal models of semantics and discourse processing. The work also introduces a sophisticated python-based software environment for modeling linguistic processes. This book has the potential to revolutionize not only formal models of linguistics, but also models of language processing more generally. (Shravan Vasishth) .
Interaction between language and cognition remains an unsolved scientific problem. What are the differences in neural mechanisms of language and cognition? Why do children acquire language by the age of six, while taking a lifetime to acquire cognition? What is the role of language and cognition in thinking? Is abstract cognition possible without language? Is language just a communication device, or is it fundamental in developing thoughts? Why are there no animals with human thinking but without human language? Combinations even among 100 words and 100 objects (multiple words can represent multiple objects) exceed the number of all the particles in the Universe, and it seems that no amount of experience would suffice to learn these associations. How does human brain overcome this difficulty? Since the 19th century we know about involvement of Broca’s and Wernicke’s areas in language. What new knowledge of language and cognition areas has been found with fMRI and other brain imaging methods? Every year we know more about their anatomical and functional/effective connectivity. What can be inferred about mechanisms of their interaction, and about their functions in language and cognition? Why does the human brain show hemispheric (i.e., left or right) dominance for some specific linguistic and cognitive processes? Is understanding of language and cognition processed in the same brain area, or are there differences in language-semantic and cognitive-semantic brain areas? Is the syntactic process related to the structure of our conceptual world? Chomsky has suggested that language is separable from cognition. On the opposite, cognitive and construction linguistics emphasized a single mechanism of both. Neither has led to a computational theory so far. Evolutionary linguistics has emphasized evolution leading to a mechanism of language acquisition, yet proposed approaches also lead to incomputable complexity. There are some more related issues in linguistics and language education as well. Which brain regions govern phonology, lexicon, semantics, and syntax systems, as well as their acquisitions? What are the differences in acquisition of the first and second languages? Which mechanisms of cognition are involved in reading and writing? Are different writing systems affect relations between language and cognition? Are there differences in language-cognition interactions among different language groups (such as Indo-European, Chinese, Japanese, Semitic) and types (different degrees of analytic-isolating, synthetic-inflected, fused, agglutinative features)? What can be learned from sign languages? Rizzolatti and Arbib have proposed that language evolved on top of earlier mirror-neuron mechanism. Can this proposal answer the unknown questions about language and cognition? Can it explain mechanisms of language-cognition interaction? How does it relate to known brain areas and their interactions identified in brain imaging? Emotional and conceptual contents of voice sounds in animals are fused. Evolution of human language has demanded splitting of emotional and conceptual contents and mechanisms, although language prosody still carries emotional content. Is it a dying-off remnant, or is it fundamental for interaction between language and cognition? If language and cognitive mechanisms differ, unifying these two contents requires motivation, hence emotions. What are these emotions? Can they be measured? Tonal languages use pitch contours for semantic contents, are there differences in language-cognition interaction among tonal and atonal languages? Are emotional differences among cultures exclusively cultural, or also depend on languages? Interaction of language and cognition is thus full of mysteries, and we encourage papers addressing any aspect of this topic.
First Published in 2007. Routledge is an imprint of Taylor & Francis, an informa company.
Dynamic logic (DL) recently had a highest impact on the development in several areas of modeling and algorithm design. The book discusses classical algorithms used for 30 to 50 years (where improvements are often measured by signal-to-clutter ratio), and also new areas, which did not previously exist. These achievements were recognized by National and International awards. Emerging areas include cognitive, emotional, intelligent systems, data mining, modeling of the mind, higher cognitive functions, evolution of languages and other. Classical areas include detection, recognition, tracking, fusion, prediction, inverse scattering, and financial prediction. All these classical areas are extended to using mixture models, which previously was considered unsolvable in most cases. Recent neuroimaging experiments proved that the brain-mind actually uses DL. „Emotional Cognitive Neural Algorithms with Engineering Applications“ is written for professional scientists and engineers developing computer and information systems, for professors teaching modeling and algorithms, and for students working on Masters and Ph.D. degrees in these areas. The book will be of interest to psychologists and neuroscientists interested in mathematical models of the brain and min das well.
Recent theoretical and experimental research on action and language processing in humans and animals clearly demonstrates the strict interaction and co-dependence between language and action. This has been demonstrated in neuroscientific investigations (e.g. Cappa&Perani, 2003; Pulvermuller 2003; Rizzolatti&Arbib, 1998), psychology experiments (e.g. Glenberg&Kaschak, 2002; Pecher&Zwaan 2005), evolutionary psychology (e.g. Corballis 2002) and computational modelling (e.g. Cangelosi&Parisi 2004; Massera et al. 2008). All these studies have important implication both for the understanding of the action basis of cognition in natural and artificial cognitive systems, as well as for the design of cognitive and communicative capabilities in robots (Cangelosi et al. 2005). The journal “Frontiers in Neurorobotics” is seeking submissions of new articles in the topic of action and language integration both in natural cognitive systems (e.g. humans and animals) and in artificial cognitive agents (robots and simulated agents). Manuscripts can regard new theoretical and computational investigations, as well as new neuroscientific and psychological investigations. Review articles in this topic are also welcome.
Anticipatory behavior in adaptive learning systems continues attracting attention of researchers in many areas, including cognitive systems, neuroscience, psychology, and machine learning. This book constitutes the thoroughly refereed post-workshop proceedings of the 4th International Workshop on Anticipatory Behavior in Adaptive Learning Systems, ABiALS 2008, held in Munich, Germany, in June 2008, in collaboration with the six-monthly Meeting of euCognition 'The Role of Anticipation in Cognition'. The 18 revised full papers presented were carefully selected during two rounds of reviewing and improvement for inclusion in the book. The introductory chapter of this state-of-the-art survey not only provides an overview of the contributions included in this volume but also revisits the current available terminology on anticipatory behavior and relates it to the available system approaches. The papers are organized in topical sections on anticipation in psychology with focus on the ideomotor view, conceptualizations, anticipation and dynamical systems, computational modeling of psychological processes in the individual and social domains, behavioral and cognitive capabilities based on anticipation, and computational frameworks and algorithms for anticipation, and their evaluation.
At the fascinating frontiers of neurobiology, mathematics and psychophysics, this book addresses the problem of human and computer vision on the basis of cognitive modeling. After recalling the physics of light and its transformation through media and optics, Hérault presents the principles of the primate's visual system in terms of anatomy and functionality. Then, the neuronal circuitry of the retina is analyzed in terms of spatio-temporal filtering. This basic model is extended to the concept of neuromorphic circuits for motion processing and to the processing of color in the retina. For more in-depth studies, the adaptive non-linear properties of the photoreceptors and of ganglion cells are addressed, exhibiting all the power of the retinal pre-processing of images as a system of information cleaning suitable for further cortical processing. As a target of retinal information, the primary visual area is presented as a bank of filters able to extract valuable descriptors of images, suitable for categorization and recognition and also for local information extraction such as saliency and perspective. All along the book, many comparisons between the models and human perception are discussed as well as detailed applications to computer vision./a
This comprehensive collection of chapters is written by leading researchers in psycholinguistics from a wide array of subfields.