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1Laurent Itti: CS564 - Brain Theory and Artificial Intelligence. Introduction and Brain Overview
Laurent Itti: CS564 - Brain Theory and Artificial Intelligence
Lecture 1. Introduction and Brain Overview
Reading Assignments:*TMB2: Chapters 1; 2.4
HBTNN:I.1. Introducing the Neuron (Arbib)
* Unless indicated otherwise, the TMB2 material is the required reading, and the other readings supplementary.
2Laurent Itti: CS564 - Brain Theory and Artificial Intelligence. Introduction and Brain Overview
CS 564: Brain Theory and Artificial Intelligence
URL: http://iLab.usc.edu/classes/2002cs564/ for syllabus, instructor and TA information, handouts, homework and grades
Instructor: Laurent Itti; itti@pollux (Office Hour: Mon 3-5,
HNB30A)TA:
Yoo-Hee Shin [email protected]
This course provides a basic understanding of brain function, and of artificial neural networks which provide tools for a new paradigm for adaptive parallel computation.
No background in neuroscience is required, nor is specific programming expertise, but knowledge of C++ will be useful for homeworks.
3Laurent Itti: CS564 - Brain Theory and Artificial Intelligence. Introduction and Brain Overview
Texts and Grading
Text: M.A. Arbib, 1989, The Metaphorical Brain 2: Neural Networks and Beyond, Wiley-Interscience.
Supplementary reading: M.A. Arbib, Ed., 1995, The Handbook of Brain Theory and Neural Networks, MIT Press (paperback).
One mid-term and a final will cover the entire contents of the readings so far as well as the lectures.
The final exam will cover all of the course, but emphasizing material not covered in the mid-term.
Distribution of Grades:
Homeworks: 40%; Mid-term: 30%; Final Exam: 30%.
4Laurent Itti: CS564 - Brain Theory and Artificial Intelligence. Introduction and Brain Overview
Syllabus Overview
Introduction
Overview
Charting the brain
The Brain as a Network of Neuronsx (t)1
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axon
5Laurent Itti: CS564 - Brain Theory and Artificial Intelligence. Introduction and Brain Overview
Syllabus Overview
Introduction (cont.)
Experimental techniques
Introduction to Vision
Schemas
6Laurent Itti: CS564 - Brain Theory and Artificial Intelligence. Introduction and Brain Overview
Syllabus Overview
Basic Neural Modeling & Adaptive Networks
Didday Model of Winner-Take-All
Hopfield networks
Adaptive networks: Hebbian learning;Perceptrons; landmark learning
E = - ½ ij sisjwij + i sii
7Laurent Itti: CS564 - Brain Theory and Artificial Intelligence. Introduction and Brain Overview
Syllabus Overview
Neural Modeling & Adaptive Networks (cont.)
Adaptive networks: gradient descentand backpropagation
Reinforcement learning
Competition and cooperation
Visual plasticity; self-organizing feature maps; Kohonen maps
8Laurent Itti: CS564 - Brain Theory and Artificial Intelligence. Introduction and Brain Overview
Syllabus Overview
Examples of Large-scale Neural Modeling
System concepts
Model of saccadic eye movements
Feedback and the spinal cord; mass-spring model of muscle
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eye movement
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9Laurent Itti: CS564 - Brain Theory and Artificial Intelligence. Introduction and Brain Overview
Syllabus Overview
Large-scale Neural Models of Vision
Early visual processing
Depth perception
Optic flow
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10Laurent Itti: CS564 - Brain Theory and Artificial Intelligence. Introduction and Brain Overview
Syllabus Overview
Large-scale Neural Models of Vision (cont.)
Visual attention
Object recognition
Scene perception
11Laurent Itti: CS564 - Brain Theory and Artificial Intelligence. Introduction and Brain Overview
AIP
F5
dorsal/ventral streams
Task Constraints (F6)
Working Memory (46)
Instruction Stimuli (F2)
Task Constraints (F6)Working Memory (46?)Instruction Stimuli (F2)
AIP
DorsalStream:Affordances
IT
VentralStream:Recognition
Ways to grab this “thing”
“It’s a mug”PFC
Syllabus Overview
Other Advanced Neural Modeling
Reaching, grasping and affordances
Cerebellar adaptation
Memory and consciousnessVisualCortex
ParietalCortex
InferotemporalCortex
How (dorsal)
What (ventral)
reach programming
grasp programming
12Laurent Itti: CS564 - Brain Theory and Artificial Intelligence. Introduction and Brain Overview
Syllabus Overview
Applications and Outlook
Towards highly-capable robots
Overview and summary
13Laurent Itti: CS564 - Brain Theory and Artificial Intelligence. Introduction and Brain Overview
Three Frameworks
Artificial intelligence (AI): build a “packet of intelligence” into a machine
Cognitive psychology: explain human behavior by interacting processes (schemas) “in the head” but not localized in the brain
Brain Theory: interactions of components of the brain -
- computational neuroscience
- neurologically constrained models: e.g., networks of neurologically localized schemas
and abstracting from them as both Artificial intelligence and Cognitive psychology:
- connectionism: networks of trainable “quasi-neurons” to provide “parallel distributed models” little constrained by neurophysiology
- abstract (computer program or control system) information processing models
14Laurent Itti: CS564 - Brain Theory and Artificial Intelligence. Introduction and Brain Overview
The Aim of the Course
To gain an understanding of biological neurons as the basis for:
Brain Theory: modeling interactions of components of the brain, especially more or less realistic biological neural networks localized in specific brain regions
Connectionism in both Artificial intelligence (AI) and Cognitive psychology: modeling artificial neural networks -- networks of trainable “quasi-neurons” -- to provide “parallel distributed models” of intelligence in humans, animals and machines
This lecture: A tourist’s guide to the brain ;-)
15Laurent Itti: CS564 - Brain Theory and Artificial Intelligence. Introduction and Brain Overview
A motivating theme: Vision
Vision as a progressive change in representation
Marr (1982): through 2 ½ D primal sketch
Because vision is by far the most studied sense (because it is easy to experiment with), we will use it as a basis for many examples of models studied in this course.
16Laurent Itti: CS564 - Brain Theory and Artificial Intelligence. Introduction and Brain Overview
Vision and the brain
Roughly speaking, about half ofthe brain is concerned with vision.Although most of it is highly auto-mated and unconscious, vision henceis a major component of brain function.
Ryback et al, 1998
17Laurent Itti: CS564 - Brain Theory and Artificial Intelligence. Introduction and Brain Overview
Vision, AI and robots
1940s: beginning of Artificial Intelligence
McCullogh & Pitts, 1942i wixi
Perceptron learning rule (Rosenblatt, 1962)
BackpropagationHopfield networks (1982)Kohonen self-organizing maps…
18Laurent Itti: CS564 - Brain Theory and Artificial Intelligence. Introduction and Brain Overview
Vision, AI and Robots
1950s: beginning of computer visionAim: give to machines same or better vision capability as
oursDrive: AI, robotics applications and factory automation
Initially: passive, feedforward, layered and hierarchical process
that was just going to provide input to higher reasoning
processes (from AI)
But soon: realized that could not handle real images
1980s: Active vision: make the system more robust by allowing the
vision to adapt with the ongoing recognition/interpretation
19Laurent Itti: CS564 - Brain Theory and Artificial Intelligence. Introduction and Brain Overview
A tourist’s guide to the brain
Gross anatomy
Non-neural structures
Major cortical areas
20Laurent Itti: CS564 - Brain Theory and Artificial Intelligence. Introduction and Brain Overview
Central vs. Peripheral Nervous System
The brain is not the entire nervous systems; there is also the spinal cord, many peripheral “ganglia” (small clusters of neurons), and neurons extend connections to locations all over the body (e.g., sensory neurons, motor neurons).
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Autonomic Nervous System
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Axes in the brain
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The “Bauplan” for the Mammalian Brain
25Laurent Itti: CS564 - Brain Theory and Artificial Intelligence. Introduction and Brain Overview
Medical Orientation Terms for Slices
26Laurent Itti: CS564 - Brain Theory and Artificial Intelligence. Introduction and Brain Overview
Main Arterial Supply to the Brain
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Arterial Supply is Segmented
Occlusion/damage to one artery will affect specific brainregions. Important to remember for patient studies.
28Laurent Itti: CS564 - Brain Theory and Artificial Intelligence. Introduction and Brain Overview
Ventricular System
Ventricules: Cavities filled with fluid inside and around the brain. One of their functions is to drain garbage out of the brain.
29Laurent Itti: CS564 - Brain Theory and Artificial Intelligence. Introduction and Brain Overview
Cortical Lobes
Sulcus (“fissure” if very large): Grooves in folded cortexGyrus: cortex between two sulci
1 sulcus, many sulci; 1 gyrus, many gyri
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32Laurent Itti: CS564 - Brain Theory and Artificial Intelligence. Introduction and Brain Overview
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36Laurent Itti: CS564 - Brain Theory and Artificial Intelligence. Introduction and Brain Overview
Neurons
Cell body (soma): where computation takes placeDendrites: input branchesAxon: unique output (but may branch out)Synapse: connection between presynaptic axon and
postsynaptic dendrite (in general).
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Electron Micrograph of a Real Neuron
38Laurent Itti: CS564 - Brain Theory and Artificial Intelligence. Introduction and Brain Overview
Neurons and Synapses
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Grey and White Matters
Grey matter: neurons (cell bodies), at outer surface of brain
White matter: interconnections, inside the brainDeep nuclei: clusters of neurons deep inside the brain
40Laurent Itti: CS564 - Brain Theory and Artificial Intelligence. Introduction and Brain Overview
Major Functional Areas
Primary motor: voluntary movementPrimary somatosensory: tactile, pain, pressure, position, temp., mvt.Motor association: coordination of complex movementsSensory association: processing of multisensorial informationPrefrontal: planning, emotion, judgementSpeech center (Broca’s area): speech production and articulationWernicke’s area: comprehen-
sion of speechAuditory: hearingAuditory association: complex
auditory processingVisual: low-level visionVisual association: higher-level
vision
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Major Functional Areas
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A View of the Monkey Brain
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44Laurent Itti: CS564 - Brain Theory and Artificial Intelligence. Introduction and Brain Overview
http://www.radiology.wisc.edu/Med_Students/neuroradiology/fmri/
45Laurent Itti: CS564 - Brain Theory and Artificial Intelligence. Introduction and Brain Overview
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49Laurent Itti: CS564 - Brain Theory and Artificial Intelligence. Introduction and Brain Overview
50Laurent Itti: CS564 - Brain Theory and Artificial Intelligence. Introduction and Brain Overview
51Laurent Itti: CS564 - Brain Theory and Artificial Intelligence. Introduction and Brain Overview
52Laurent Itti: CS564 - Brain Theory and Artificial Intelligence. Introduction and Brain Overview
Limbic System
Cortex “inside” the brain.Involved in emotions, sexual behavior, memory, etc(not very well known)
53Laurent Itti: CS564 - Brain Theory and Artificial Intelligence. Introduction and Brain Overview
Major Functional Areas
54Laurent Itti: CS564 - Brain Theory and Artificial Intelligence. Introduction and Brain Overview
Visual Input to the Brain
55Laurent Itti: CS564 - Brain Theory and Artificial Intelligence. Introduction and Brain Overview
Eye and retina
56Laurent Itti: CS564 - Brain Theory and Artificial Intelligence. Introduction and Brain Overview
Human Visual System
57Laurent Itti: CS564 - Brain Theory and Artificial Intelligence. Introduction and Brain Overview
Primary Visual Pathway
58Laurent Itti: CS564 - Brain Theory and Artificial Intelligence. Introduction and Brain Overview
Layered Organization of Cortex
Cortex is 1 to 5mm-thick, folded at the surface of the brain (grey matter), and organized as 6 superimposed layers.
Layer names:1: Molecular layer2: External granular layer3: External pyramidal layer4: internal granular layer5: Internal pyramidal layer6: Fusiform layer
Basic layer functions:Layers 1/2: connectivityLayer 4: InputLayers 3/5: Pyramidal cell bodiesLayers 5/6: Output
59Laurent Itti: CS564 - Brain Theory and Artificial Intelligence. Introduction and Brain Overview
Layered Organization of Cortex
60Laurent Itti: CS564 - Brain Theory and Artificial Intelligence. Introduction and Brain Overview
Slice through the thickness of cortex
1
2
3
4
5
6
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Columnar Organization
Very general principle in cortex: neurons processing similar “things” are grouped together in small patches, or “columns,” or cortex.
In primary visual cortex… as in higher (object recognition) visual areas…
and in many, non-visual, areas as well (e.g., auditory, motor, sensory, etc).
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Retinotopy
Many visual areas are organized as retinotopic maps: locations next to each other in the outside world are represented by neurons close to each other in cortex.Although the topology is thus preserved, the mapping typically is highly non-linear (yielding large deformations in representation).
Stimulus shown on screen… and corresponding activity in cortex!
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Retinotopy
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Mammalian and Frog Visual Systems
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Felleman & Van Essen, 1991
Interconnect
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Interconnect… (other source)
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More on Connectivity
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Frog
Snake
Horse
Primitive Mammal
Catfish
Alligator
Goose
Varieties of Vertebrate Brains
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Outlook
There is a lot to learn about the brain!… but don’t feel overwhelmed, we will smoothly
introduce all new concepts.
Principled theoretical and engineering methods will allow us to abstract some of these complications.
Starting with fundamental techniques, we will then study fairly complex, large-scale neural models.