Brain-mind machinery brain-inspired computing and mind opening
| Autor principal: | |
|---|---|
| Formato: | Libro electrónico |
| Idioma: | Inglés |
| Publicado: |
Hackensack, NJ :
World Scientific
c2009.
|
| Colección: | EBSCO Academic eBook Collection Complete.
|
| Acceso en línea: | Conectar con la versión electrónica |
| Ver en Universidad de Navarra: | https://innopac.unav.es/record=b31381376*spi |
Tabla de Contenidos:
- Cover
- CONTENTS
- Preface
- Acknowledgement
- Chapter 1: The Brain
- How is the Brain Organized? Specificity Implies Regionalization and Specialization
- How Does the Brain Wire Itself?
- What is the 8220;computational power8221; of the brain?
- Summary
- Chapter 2: Neurons and Synapses
- How Do Neurons Communicate and Affect Our Learning and Memory?
- How Does Synaptic Plasticity Give Rise to Learning and Memory?
- Modeling the Neurons and Synapses
- Chapter 3: The Cortex Architecture
- How is the Cortex Structurally Arranged?
- Other Design Factors in the Cortex
- Computational Model of the Cortex Architecture 8212; Model After the Hierarchical Structure
- Case Study 8212; Why the Brain Can Discriminate and Recognize Pictures in a Glance
- How Does the Prefrontal Cortex Perform Decision-Making?
- Summary
- Chapter 4: Many Faces of Memories 8212; Investigating the Human Multiple Memory Systems
- Memory Systems Based on Information Storage Time
- Memory Systems Based on the Type of Information Stored
- Declarative Memory
- Semantic Memory
- Episodic Memory
- Non-Declarative Memory
- Role of Hippocampus in Memory
- Let Us Sleep Over It
- Interesting Observation of Human Memory
- Human Memory in Chronological Age
- Summary
- Chapter 5: Learning Like a Human
- How Do Humans Learn?
- How Plasticity and Stability Give Rise to Learning
- Forms of Human Learning
- Perceptual Learning
- Stimulus-Response Learning (S-R Learning)
- Computational Techniques Based on S-R Learning
- Motor Learning
- Relational Learning
- Dopamine8217;s Role in Learning
- Cognitive Learning
- Summary
- Chapter 6: Emotion and Cognition
- Introduction
- What are the Emotions?
- What is the Possible Emotional Circuitry in the Brain?
- What is Emotional State?
- How Can We Model Emotion and Cognition?
- How Do Emotions Affect Our Cognitive Abilities?
- Conclusions
- Chapter 7: Laminar Computing
- What, How, and Why Laminar Computing?
- The Neocortex has a Laminar Pattern
- Top Down, Bottom-Up, and Horizontal Interactions
- Shunting Networks
- Folded Feedback
- Complementary Properties
- The 8220;Drum-up8221; to Laminar Computing
- From Vision to Cognition
- Chapter 8: Probabilistic Computing
- Probabilistic Model of Cognitive Process
- Bayesian Networks
- Conclusions
- Chapter 9: Thinking Machine
- Can a Machine Think and Have a Mind?
- Multiple Layers of Machinery
- Multiple Intelligences
- Triarchic Theory of Intelligence
- Conceptual Blending Theory
- Commonsense Knowledge Representation
- The Wise Machine 8212; AI with Wisdom
- Summary
- Chapter 10: Modeling the Entire Brain
- Integrated Cognitive Architecture
- SOAR Architecture
- ACT-R Architecture
- ICARUS Architecture
- BDI Architecture
- Subsumption Architecture
- CLARION Architecture
- Functional Comparison of the Six Cognitive Architectures
- Conclusions
- Chapter 11: Are We There? What Can the Computer Do Today and Tomorrow?
- Data and Communication Capability
- Physical Capabilitya
- Vision Capability
- Artistic Capability
- Mental Capability
- General Task Capabilityb
- Could a Machine Pass the Turing Test?
- Chapter 12: Brain 8212; A Forest Not Totall.
