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CS 182 Sections 101 - 104. 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.
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CS 182Sections 101 - 104 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 Created by Eva Mok Modified by JGM 2/2/05
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?
Memory Declarative Non-Declarative Episodic Semantic Procedural Two ways of looking at memory: facts about a situation general facts 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)
Memory Short Term Memory Long Term Memory Two ways of looking at memory: electrical changes structural changes LTP
A X P T G Q N L W R V S
strengthen weaken LTP and Hebb’s Rule • Hebb’s Rule: neurons that fire together wire together • Long Term Potentiation (LTP) is the biological basis of Hebb’s Rule • Calcium channels is the key mechanism
tastebud tastes rotten eats food gets sick drinks water Why is Hebb’s rule incomplete? • here’s a contrived example: • should you “punish” all the connections?
yj wij yi xi f ti : target xi = ∑j wij yj yi = f(xi) The McCullough-Pitts Neuron yj: output from unit j Wij: weight on connection from j to i xi: weighted sum of input to unit i
i1 w01 w02 i2 y0 b=1 w0b x0 f Let’s try an example: the OR function • 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?
i2 i1 Many answers would work y = f (w01i1 + w02i2 + w0bb) recall the threshold function the separation happens when w01i1 + w02i2 + w0bb = 0 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
A B C How we can model the triangle node with McCullough-Pitts Neurons? A B C
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