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  • Издательство: The MIT Press
  • Год: 2006
  • ISBN: 0-262-06253-4
  • Кол-во страниц: 357
  • Загружен: 28 Dec 2009 17:24
  • Размер файла: Неизвестно
  • Просмотров: 1476
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  • Соответствие оригиналу: нет
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  • Язык: Английский

Содержание (оглавление)

Preface
Acknowledgments
I Embodied Information Processing
1 The Mystery of Embodied Language
2 The Information Processing Perspective
3 Computational Models
II How the Brain Computes
4 Neurons and Other Cells
5 The Society of Neurons
6 Nature and Nurture
III How the Mind Computes
7 Connections in the Mind
8 Embodied Concepts and Their Words
9 The Computational Bridge
IV Learning Concrete Words
10 First Words
11 Conceptual Schemas and Cultural Frames
12 Learning Spatial Relation Words
V Learning Words for Actions
13 Embodied Knowledge of Actions
14 Learning Action Words
VI Abstract and Metaphorical Words
15 Conceptual Systems
16 Metaphors and Meaning
17 Understanding as Simulation
VII Understanding Stories
18 The Structure of Action and Events
19 Belief and Inference
20 Understanding News Stories
VIII Combining Form and Meaning
21 Combining Forms—Grammar
22 The Language Wars
23 Combining Meanings—Embodied Construction Grammar
IX Embodied Language
24 Embodied Language Understanding
25 Learning Constructions
26 Remaining Mysteries
27 All Together Now
References and Further Reading
Index

  Загрузить Feldman J.A. From Molecule to Metaphor. A Neural Theory of Language

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Скриншот
Information processing is my organizing theme. Language and thought are inherently about how information is acquired, used, and transmitted.
Chapter 1 lays out some of the richness of language and its relation to experience. The central mechanism in my approach to the neural language problem is neural computation. Chapters 2 and 3 provide a general introduction to neural computation. Chapters 4 through 6 provide the minimal biological background on neurons, neural circuits, and how they develop.
We focus on those properties of molecules, cells, and brain circuits that determine the character of our thinking and language.
Chapters 7 and 8 consider thought from the external perspective and look at the brain/mind as a behaving system. With all of this background, chapter 9 introduces the technical tools that are used to model how various components of language and thought are realized in the brain. A fair amount of mechanism is required for my approach, which involves building computational models that actually exhibit the required behavior while remaining consistent with the findings from all disciplines. I refer to such systems as adequate computational models, which I believe are the only hope for scientifically linking brain and behavior. There is no guarantee that an adequate model is correct, but any correct model must be adequate in the sense defined here.
The specific demonstrations begin with a study of how children learn their first words. This involves some general review (chapter 10) and a more thorough study of conceptual structure (chapter 11) needed for word learning.
The first detailed model is presented in chapter 12, which describes Terry Regier’s program that learns words for spatial relation concepts across languages. This theme of concrete word learning is then extended to cover words for simple actions in chapters 13 and 14, which describes David Bailey’s demonstration system.
The next section extends the discussion to words for abstract and metaphorical concepts. In chapters 15 and 16, we look further at the structure of conceptual systems and how they arise through metaphorical mappings from direct experience. Chapter 17 takes the informal idea of understanding as imaginative simulation and shows how it can be made the basis for a concrete theory. This theory is shown in chapter 18 to be sufficiently rich to describe linguistic aspect—the shape of events. This is enough to capture the direct effects of hearing a sentence, but for the indirect consequences, we need one more computational abstraction of neural activity—belief networks, described in chapter 19. All of these ideas are brought together in Srinivas Narayanan’s program for understanding news stories, discussed in chapter 20.
Chapters 21 through 25 are about language form, that is, grammar—how grammar is learned and how grammatical processing works. Chapter 21 lays out the basic facts about the form of language that any theory must explain. Chapter 22 is partly a digression; it discusses the hotbutton issues surrounding how much of human grammar is innate. We see that classical questions become much different in an explicitly embodied neural theory of language and that such theories can be expressed in standard formalisms (chapter 23).
Chapter 24 shows how the formalized version of neural grammar can be used scientifically and to build software systems for understanding natural language. The poster child for the entire theory is Nancy Chang’s program (chapter 25) that models how children learn their early grammar—as explicit mappings (constructions) relating linguistic form to meaning.
Chapter 26 discusses two questions that are not currently answerable: the evolution of language and the nature of subjective experience. Finally, chapter 27 summarizes the book and suggests that further progress will require a broadly based unified cognitive science. But the scientific progress to date does support a range of practical and intellectual applications and should allow us to understand ourselves a bit better.



Психологический юмор, анекдоты