Contents

The talk is a set of pages organized on two levels, indicated by the indentation in this contents. At the second level, the backward arrow takes you back to the first level and the forward arrow takes you to the next node at the first level.
There are two kinds of pages, diagrams and bullet lists. For diagrams there is a commentary below the diagram and sometimes an audio version of this.

• Overview
  • Problems
    • Future computer systems
  • Solutions
  • Computer science approach
    • Layered representations
    • The computer science of the brain
  • A multidisciplinary enterprise
  • Overview of the talk
• The structure and function of the brain
  • Neural areas and notation used
    • Internal connectivity - the circuitry of the neocortex
    • Cell types in the primate neocortex
    • The layers of the primate neocortex
    • External connectivity of neurons of the neocortex
    • Tracing connections
    • Jones and Powell connectivity
    • Brain slices
    • Theories of the uniform process
  • Dividing brain into four parts
  • Strategy for modeling the brain
  • Functional involvements of cortical areas
  • Areas and connectivity
  • The biological basis of our computational approach
  • How my model implements the biological basis
• My model
  • My initial system model
  • Correspondence of initial model to neocortical areas
    • Side by side correspondence
  • Descriptions and rules
    • Specifying data types for each module
    • Specifying rule sets for each module
  • The structure of a brain module
    • A module as a dataflow processor
• How the model works
  • Perception-action hierarchies
    • Perception and action rules
  • Social plans
    • Interacting brain states
    • Primate social groups
  • Elaboration of plans
    • Model mechanisms
    • The action of rules
• Social interaction scenarios demonstrated with the model
  • Grooming
  • Social conflict
  • Social spacing
• Brain states
  • Instantaneous state of the model
  • Predicted brain area activation patterns for different kinds of processing
  • Viable states
  • Lessons learned
• Time development of my research
  • Time course of my research
  • Reengineering the system
  • The BAD language
• Problem solving using the brain model
  • The choice of the Tower of Hanoi problem
    • Possible strategies for the Tower of Hanoi
  • The Tower of Hanoi problem
  • The Tower of London problem
  • Anzai and Simon strategy sequence
  • Programming the three strategies on the brain model
  • Predicted brain area activation sequences
    • Perceptual strategy saving only current goal
    • Perceptual strategy with goal stacking
  • Frontal lobe phenomena
  • Lessons learned
  • Formal theory
• Learning and memory in the brain
  • Separate learning systems
  • The hippocampus implements episodic memory
    • How the hippocampus may work
    • The rat brain
  • Overview of memory and learning
  • Events and event map
  • Contexts
  • Representing contexts in BAD
  • The dynamic version of the model
  • The basic action of the system
  • Learning by doing
  • Episodic memory mechanisms
  • Learning Tower of Hanoi strategies
    • Other work on TH learning
    • The initial state
    • Available contexts
    • Lessons learned
• Natural language processing
  • Psycholinguistic phenomena
  • Linguistics
  • Computational psycholinguistic models
  • Kempen's psycholinguistic model
    • Lexical frames
    • The use of grammatical features
  • Constructing a parse tree
  • Brain areas corresponding to concurrent modules
  • Representing lexical frames
  • Rules implementing the construction process
  • Lessons learned
• Motivational mechanisms
  • Two level control
    • Complete system diagram for fear behavior
  • Levels of motivational control
  • Table of hypothalamic actions
  • Logical modeling of motivational systems
  • Motivational systems
  • Metabolism of hormones
  • Male neurohormonal system
  • Female neurohormonal system
  • Lessons learned
• Applications
  • Socially intelligent agents
    • Mutual commitment and narrative
  • Social relationship with virtual agents
    • System diagram for face to face interation
  • Intelligent robots
    • Structure of onboard robot software system
    • Hierarchical control system for robot
    • Supervisory control relationship to user
• Discussion
  • Levels below the system level
  • Implications for artificial intelligence
• Conclusions
  • Results so far
    • My current thinking on the brain
    • Towards a computer science of the brain
    • Vision of a brain-computer
  • Summary and conclusion
  • More general summary and conclusion
  
  
  
  Alan Bond
  2002-07-21