T4 R-W model Flashcards
Define V
The associative strength between CS and US
How much you know
What does a higher value of V mean?
The stronger the associative learning between CS-US
Define delta V
Change in V - how much has been learnt in each trial
What is the R-W model equation?
alpha X beta X (lambda - sigmaV) = deltaV
Define alpha
Salience of the CS
Define Beta
Salience of the US, always 1 in this course
What are the salience factors of the equation?
alpha and beta
What represents the prediction error term in the equation?
lambda - sigmaV
What is the prediction error term quantifying?
The notion of surprise
What is the prediction error term?
The discrepancy between the expectation and what actually happens in the trial
Define Lambda
Maximum amount of learning that can occur
Define SigmaV
Expectancy of the CS-US pairing
What are the 3 steps used when applying this model to a trial of learning
Step 1: calculate sigmaV before the pairing
Step 2: figuring out how much learning occurs when CS is paired with the US - work out deltaV
Step 3: update the value of V - add original V to deltaV to work out updated V
What happens to the value of deltaV with ongoing trials
It decreases because learning decreases as the animal is becoming less surprised
What effect does higher salience have on learning
Increases the rate of learning
