Theories Of Conditioning Flashcards
The Rascorla Wagner model
- The Rescorla-Wagner model focuses on the surprise value of the US to explain learning
- The Rescorla-Wagner model ‘predicts’ the typical profiles of acquisition, extinction and inhibitory learning
The makintosh model uses
Attentional variables
Pearce hall model deals with
CS salience
Pavlov temporal contiguity theory
Closeness in time certainly helps animals to form associations between events
But temporal contiguity has to be inadequate as a complete theoretical account of classical conditioning
And studies of taste aversion show it isn’t necessary either
(see my last lecture: 3. Mechanisms of conditioning)
Pavlov temporal contiguity theory
Conditioned taste aversion over long delays
Smith and Roll 1967
Kamins blocking experiment
Design and results
Rescorla Wagner 1972
- Originally focused on the surprisingness of the US; or discrepancy between obtained and expected reinforcement
- Pairing CS with unexpected US will increase strength of connection between them to a maximum determined by the magnitude of the US
- In later version, the surprisingness of the CS was also taken into account
- Rescorla-Wagner (1972)
- Subsequent capacity of CS to activate US representation held to depend on strength of association between them (measured as strength of CR)
- On each CSUS pairing, variable increase in associative strength, depending on current associative strength of CS and max. supportable by US
- So learning should be most rapid early in conditioning, rate should level off later
Rescorla-Wagner (1972)
Equation used to express theory formally:
∆V = (-V)
V: strength of CS-US association
∆V: change in strength of association on a particular trial
: set by magnitude of US and sets maximum strength CS-US association can reach
: reflects salience of CS and is invariant throughout conditioning
Rescorla-Wagner (1972): ∆V = (-V)
Acquisition Assuming is set at 0.20 and at 100: Trial 1 For novel CS, V is zero because the CS has no associative strength, so ∆V = 0.20(100-0) ∆V = 20 Trial 2 After trial 1, V is now 20, so ∆V = 0.20(100-20) ∆V = 16
The effect of US magnitude on learning
Lower asymptote cf. sensory preconditioning - behaviourally silent
The effect of CS salience on learning
Overshadowing, CS intensity relative to background, depressed acquisition function resembles that seen with a conditioned inhibitor
Rescorla-Wagner (1972): ∆V = (-V)
Extinction lis now zero because the US is absent and (in our example) the associative strength of the US reached 100: Trial 1 ∆V = 0.20(0-100) ∆V = -20 Trial 2 ∆V = 0.20(0-80) ∆V = -16
Conditioning with compound stimuli
Rescorla Wagner 1972
US surprisingness will now depend on how well this event is predicted by all the available stimuli
VALL = algebraic sum of all CSs present on any given trial
So for CSA on a single compound conditioning trial, ∆VA = A( - VALL)
Conditioned inhibition (CI) aka inhibitory learning
Phase 1: CSL -> US; VL approaches value = 1
Phase 2: (CIN + CSL) -> no US; = 0;
ΣV (sum of associative strengths of L and N) approaches zero