User:Y-S.Ko/free study/Psychology

Cognitive science

J.L. Bermudez - Cognitive Science: An Introduction to the Science of the Mind (2014)

• The prehistory of cognitive science
  • The reaction against behaviorism in psychology
  • The theory of computation and the idea of an algorithm
  • Linguistics and the formal analysis of language
  • Information-processing models in psychology
  • Connections and points of contact
• The discipline matures: Three milestones
  • Language and micro-worlds
  • How do mental images represent?
  • An interdisciplinary model of vision
• The turn to the brain
  • Cognitive systems as functional systems
  • The anatomy of the brain and the primary visual pathway
  • Extending computational modeling to the brain
  • Mapping the stages of lexical processing
• Cognitive science and the integration challenge
  • Cognitive science: An interdisciplinary endeavor
  • Levels of explanation: The contrast between psychology and neuroscience
  • The integration challenge
  • Local integration I: Evolutionary psychology and the psychology of reasoning
  • Local integration II: Neural activity and the BOLD signal
• Tackling the integration challenge
  • Intertheoretic reduction and the integration challenge
  • Marr’s tri-level hypothesis and the integration challenge
  • Models of mental architecture
• Physical symbol systems and the language of thought
  • The physical symbol system hypothesis
  • From physical symbol systems to the language of thought
  • The Chinese room argument
• Applying the symbolic paradigm
  • Expert systems, machine learning, and the heuristic search hypothesis
  • ID3: An algorithm for machine learning
  • WHISPER: Predicting stability in a block world
  • Putting it all together: SHAKEY the robot
• Neural networks and distributed information processing
  • Neurally inspired models of information processing
  • Single-layer networks and Boolean functions
  • Multilayer networks
  • Information processing in neural networks: Key features
• Neural network models of cognitive processes
  • Language and rules: The challenge for information-processing models
  • Language learning in neural networks
  • Object permanence and physical reasoning in infancy
  • Neural network models of children’s physical reasoning
  • Conclusion: The question of levels
• How are cognitive systems organized?
  • Architectures for intelligent agents
  • Fodor on the modularity of mind
  • The massive modularity hypothesis
  • Hybrid architectures
• Strategies for brain mapping
  • Structure and function in the brain
  • Studying cognitive functioning: Techniques from neuroscience
  • Combining resources I: The locus of selection problem
  • Combining resources II: Networks for attention
  • From data to maps: Problems and pitfalls
• A case study: Exploring mindreading
  • Pretend play and metarepresentation
  • Metarepresentation, autism, and theory of mind
  • The mindreading system
  • Understanding false belief
  • Mindreading as simulation
  • The cognitive neuroscience of mindreading
• New horizons: Dynamical systems and situated cognition
  • Cognitive science and dynamical systems
  • Applying dynamical systems: Two examples from child development
  • Situated cognition and biorobotics
  • From subsumption architectures to behavior-based robotics
• The cognitive science of consciousness
  • The challenge of consciousness: Leibniz's Mill
  • Consciousness and information processing: The Knowledge argument
  • Information processing without conscious awareness: Some basic data
  • So what is consciousness for?
  • Two types of consciousness and the hard problem
  • The global workspace theory of consciousness
  • Conclusion
• Looking ahead: Challenges and applications
  • Exploring the connectivity of the brain: The connectome and the BRAIN initiative
  • Understanding what the brain is doing when it appears not to be doing anything
  • Building artificial brain systems?
  • Enhancing education
  • Building bridges to economics and the law