CS 182
Sections 101 - 104
Created by Eva Mok
Modified by JGM 2/2/05
Q:
What did the hippocampus say during its
retirement speech?
A:
“Thanks for the memories”
Q:
What happens when a neurotransmitter falls in
love with a receptor?
A:
You get a binding relationship.
Q:
What did the Hollywood film director say after he
finished making a movie about myelin?
A:
“That’s a wrap!”
http://faculty.washington.edu/chudler/jokes.html
Announcements
• a2 is out, due next Monday 11:59pm
– play with tlearn
– you can either run it on inst machines or
download it and run on your pc (though this
may give you some headaches…)
• Quiz on Thursday
Where we stand
• Last Week
– Basic idea of learning, Hebb’s rule
– Psycholinguistics experiments
• This Week
– Spreading Activation, triangle nodes
– Connectionist representations
• Coming up
– Backprop (review your Calculus!)
Quiz!
• What are does the Stroop effect show? What was the
point of the eye-tracking experiment?
• Why is Hebb’s rule not the complete story for the
learning that goes on in the brain?
• What’s a McCullough-Pitts neuron? How does it work?
• What does the “They all rose” experiment show? How
can you explain the results computationally?
Two ways of looking at memory:
Memory
Declarative
Episodic
facts about a
situation
Non-Declarative
Semantic
general facts
Procedural
skills
Stroop effect
• takes longer to say what color a word is
printed in if it names a different color
• suggests interaction of form and meaning (as
opposed to an encapsulated ‘language
module’)
‘Word superiority effect’
• it’s easier to remember letters if they are seen
in the context of a word
• militates against ‘bottom-up’ model, where
word recognition is built up from letters
• suggestion: there are top-down and bottom-up
processes which interact
Eye-tracking Experiment
• Three hypothesis for eye-tracking results:
– Cohort theory
– Neighborhood activation model
– TRACE (McClelland & Elman)
Two ways of looking at memory:
Memory
Short Term Memory
Long Term Memory
electrical
changes
structural
changes
LTP
A
X
P
T
G
Q
N
L
W R
V
S
LTP and Hebb’s Rule
• Hebb’s Rule:
neurons that fire together wire together
strengthen
weaken
• Long Term Potentiation (LTP) is the biological
basis of Hebb’s Rule
• Calcium channels is the key mechanism
Why is Hebb’s rule incomplete?
• here’s a contrived example:
tastebud
tastes rotten
eats food
gets sick
drinks water
• should you “punish” all the connections?
The McCullough-Pitts Neuron
yj
wij
xi
f
yi
ti : target
xi = ∑j wij yj
yi = f(xi)
yj: output from unit j
Wij: weight on connection from j to i
xi: weighted sum of input to unit i
Let’s try an example: the OR function
i1
i2
b=1
w01
w02
w0b
x0
f
y0
i1
i2
y0
0
0
0
0
1
1
1
0
1
1
1
1
• Assume you have a threshold function centered at the
origin
• What should you set w01, w02 and w0b to be so that
you can get the right answers for y0?
Many answers would work
y = f (w01i1 + w02i2 + w0bb)
i2
recall the threshold function
the separation happens when
w01i1 + w02i2 + w0bb = 0
i1
move things around and you get
i2 = - (w01/w02)i1 - (w0bb/w02)
“They all rose”
triangle nodes:
when two of the
neurons fire, the
third also fires
model of
spreading activation
How we can model the triangle node
with McCullough-Pitts Neurons?
A
B
C
A
B
C
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