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Brain mechanisms: linking cognitive phenomena to neuron activity |
about the book
This book shows how to understand higher cognition in terms of anatomical, physiological and chemical processes in the brain. It provides a more generally accessible version of the ideas described in my earlier academic monograph.
A brain has no resemblance to an electronic system. Nevertheless, how we go about understanding complex electronic systems has some important lessons for how to go about understanding the brain. A computing system can have over 100 billion components like transistors. An engineer does not design a computer or a new feature by simultaneously imagining the activity of all the billions of transistors that could be involved. Rather, the design information is organized in such a way that all design tasks are within the mental bandwidth of a human designer. The techniques to achieve this involve hierarchies of description, carefully managed use of approximation, and the ubiquitous use of just two types of information process: instructions and data read/writes.
Natural selection pressures have resulted in brain architectures to which analogous techniques can be applied. These pressures have resulted in organization of brain resources into modular hierarchies and the ubiquitous presence of two types of information processes in the brain, condition definition/detections and behavioural recommendation definition/integrations. As a result, hierarchies of description can be created to support understanding of cognitive phenomena in terms of the activity of the billions of neurons in the brain.
A brain has no resemblance to an electronic system. Nevertheless, how we go about understanding complex electronic systems has some important lessons for how to go about understanding the brain. A computing system can have over 100 billion components like transistors. An engineer does not design a computer or a new feature by simultaneously imagining the activity of all the billions of transistors that could be involved. Rather, the design information is organized in such a way that all design tasks are within the mental bandwidth of a human designer. The techniques to achieve this involve hierarchies of description, carefully managed use of approximation, and the ubiquitous use of just two types of information process: instructions and data read/writes.
Natural selection pressures have resulted in brain architectures to which analogous techniques can be applied. These pressures have resulted in organization of brain resources into modular hierarchies and the ubiquitous presence of two types of information processes in the brain, condition definition/detections and behavioural recommendation definition/integrations. As a result, hierarchies of description can be created to support understanding of cognitive phenomena in terms of the activity of the billions of neurons in the brain.
Now available
CONTENTS
Chapter 1. Introduction
Chapter 2. What it means to understand a complex system
Chapter 3. The different architectures of computers and brains
Chapter 4. Dividing up experience into information conditions
Chapter 5. Defining and evolving cortical receptive fields
Chapter 6. Accessing information from past sensory experience
Chapter 7. Associating cortical receptive fields with behaviours
Chapter 8. Information processes in neurons
Chapter 9. Information processes performed by the subcortical structures
Chapter 10. Remembering words and facts
Chapter 11. Paying attention
Chapter 12. Processing current experience
Chapter 13. Understanding speech
Chapter 14. Bootstrapping cognition
Chapter 15. Remembering events
Chapter 16. Feelings and emotions
Chapter 17. Speeding up thinking
Chapter 18. Consciousness and self-awareness
Chapter 19. How we solve specific cognitive problems
Chapter 20. Some general implications and conclusions
Appendix 1. How practical considerations force complex control systems into either the instruction architecture or the recommendation architecture
Appendix 2. Designing an artificial general intelligence
Chapter 2. What it means to understand a complex system
Chapter 3. The different architectures of computers and brains
Chapter 4. Dividing up experience into information conditions
Chapter 5. Defining and evolving cortical receptive fields
Chapter 6. Accessing information from past sensory experience
Chapter 7. Associating cortical receptive fields with behaviours
Chapter 8. Information processes in neurons
Chapter 9. Information processes performed by the subcortical structures
Chapter 10. Remembering words and facts
Chapter 11. Paying attention
Chapter 12. Processing current experience
Chapter 13. Understanding speech
Chapter 14. Bootstrapping cognition
Chapter 15. Remembering events
Chapter 16. Feelings and emotions
Chapter 17. Speeding up thinking
Chapter 18. Consciousness and self-awareness
Chapter 19. How we solve specific cognitive problems
Chapter 20. Some general implications and conclusions
Appendix 1. How practical considerations force complex control systems into either the instruction architecture or the recommendation architecture
Appendix 2. Designing an artificial general intelligence