1. Biological Based Networks

2. Why? Modeling of brain function
Model of very distributed parallel systems
Existence proof for AI

3. Human Brain Neuron Speed - 10-3 seconds per operation
Brain weights about 3 pounds and at rest consumes 20% of the bodies oxygen.
Estimates place neuron count at 1012 to 1014
Connectivity can be 10,000

4. What is the capacity of the brain?
Estimate the MIPS of a brain
Estimate the MIPS needed by a computer to simulate the brain

5. Structure The cortex is estimated to be 6 layers
The brain does recognition type computations is milliseconds
The brain clearly uses some specialized structures.

6. Alan Turing’s Idea X1 X2 1

7. Turing (Cont)
B type link

8. B type link

9. Biowall

10. Structure Cortex is 6 layers A mosaic of hexagons
Top three are internal
Middle in input
Bottom two area output
A mosaic of hexagons
Lots of feedback
Can excite surrounding hexs

11. Language Language develops from a proto language
Full language is structured into clauses and phrases
Brains don’t do syntax!
Parsing is by thematic roles
7 plus or minus 2

12. Igor Aleksander “Impossible Minds, My neurons, My consciousness”
“Seeing is believing: Depictive Neuromodeling of Visual Awareness”

13. Igor Aleksander WISARD and MAGNUS Visual input by arrays of sensors
Neural systems viewed as having a state transition form
Iconic States
Iconic states is the brain state upon perceiving an object

14. Input Z drives learning
Atrophies in time

15. Build a simple creature

20. Magnus

22. Vision Mechanisms
Superior Colliculus – eye movement has direct input from the retina
Vision path goes to V1, V2, V3
Extrastriate Cortex is selected areas of Cortex
Pathway X is a hypothesis for this work

23. Neuro-Physical Model Extrastriate Areas Movable retinal projection
Superior
Colliculus
Main Visual Pathway
Movement
Primary
Areas (V1, V2, …)
Extrastriate Areas
Auditory Triggers
Gaze Locking j
Pathway X
Non-ocular Motor Activity

24. Hypothesis
Feedback loop in the preceding slide is a state machine with learning memory
Recall of detail and shape is related to gaze locking signals

25. Experimental System
24 neural areas
30,000 neurons

26. Experimental System

27. Consciousness What is it? Descartes theater of them mind
An answer to the wrong question?

28. Randall Beer
“Intelligence as Adaptive Behavior”
A simple creature:

29. Leg Controller
P = pacemaker
LC – command
(shared)

30. Pacemaker coupling

31. Studies Produced the same gaits as real insects
Speed control by LC also produced realistic gaits
Lesion studies show survivability

32. M Arbib A two level methodology Neurons at the bottom layer
Schema – Functional Entities
Example Frogs:
Snap a small creatures
Run from larger ones
Behaviors found to happen in different areas

33. Naïve Schema
Eye
Small Obj
Large Obj + +
Jump
Snap
Movement

34. Lesioning Studies
Eye
All Obj
Large Obj + + -
Jump
Snap
Movement

35. William H. Calvin University of Washington in Seattle
‘The Cerebral Code”
“Lingua Ex Machina”

36. Brain Operation as Darwinian
Requires a complex pattern
Pattern must be copied
Variant patterns by chance
Pattern and variant compete
Competition based on multi faceted environment
Most successful patterns survive

37. Jeff Hawkens
“On Intelligence”

38. Criterion Inclusion of time in the brain Feedback
Physical Architecture must be part of the theory

39. Mountcastle Proposal
The algorithm of the cortex is independent of an particular sense or function
The brain uses the same mechanism for all!

40. State Machines
The brain used state machine to sequence patterns of firing
Short term memory
Visual systems

41. Summary The brain is the prototype for intelligence
Brain structure and brain function are being studied
Can a symbol system compete with the brain?
How does symbolic behavior arise from the neural level of the brain?