Rescorla-Wagner Model

Rescorla-Wagner Model

Rescorla-Wagner Model US-processing model Can account for some Pavlovian Conditioning phenomena: acquisition blocking unblocking with an upshift conditioned inhibition US-pre-exposure effect Cannot account for some Pavlovian Conditioning

phenomena: extinction (i.e., spontaneous recovery) unblocking with a downshift latent inhibition temporal factors (i.e., CS-US interval) Pearce-Hall Model attention model of conditioning a CS-processing model according to the model, it is highly adaptive to pay pay attention to, or process, CSs that could become

valid predictors of important outcomes (i.e., USs) it is also adaptive not to pay attention to, or process, CSs when the important event is already predicted by something else Pearce-Hall Model also based on the concept of surprise when the subject is surprised, attention to, or processing of the CS occurs as the US becomes predicted by a CS, and is less surprising, processing of the CS declines

The amount of processing, that is associability of a CS, changes on each trial depending on whether the US was predicted (on the previous trial) If the US was predicted, then attention to the CS declines If the US was not predicted, then attention to the CS increases Pearce-Hall Model Recall from the RW Model, VA = k( VT) k = constant; salience or associability of the CS

With the PH Model, k changes across trials (CS processing model, not a US processing model) Pearce-Hall Model kAN = N-1 VAN-1 kAN = associative strength or associability of CSA on trial N N-1 = strength of the US on previous trial VAN-1 = strength of CSA on previous trial (could become VT if more than one CS) Important point: k depends on what happened on the

previous trial; on first exposure, novelty causes some attention Pearce-Hall Model kAN = N-1 VAN-1 Early in training, when the strength of the CS is low (i.e., V is high) see high k value and thus, more attention to the CS When the CS is strong in later trials (i.e., V is small) attention to the CS is low The important point is that attention to the CS

changes across trials Pearce-Hall Model Attention to, or processing of, the CS can be measured in terms of an OR (i.e., looking at a L) This is different than the CR Support for the PH Model comes from the finding that subjects orient towards novel stimuli and maintain their orientation, provided the stimulus is a poor predictor of the US

Kaye & Pearce compared the OR in 3 groups of rats Group 1: L alone Group 2: L Group 3: L condensed milk milk/no milk (inconsistent/random) Looked at OR to L Attention (OR) was high on the first trial since the L is novel

Group 3 OR to L Group 2 Group 1 Blocks of Training Trials kAN = N-1 VAN-1 Group 1: L alone

k stays low (decrease attention) Group 2: L milk VA gets bigger over time which makes the total term smaller (this means small k and decrease in attention) Group 3: L milk/no milk

Attention remains high since VA is low When the CS is not a good predictor, rats maintained their attention to the cue If the CS is a good predictor (of the US or no US), then attention decreases Pearce-Hall Model and Blocking like the RW Model, all CSs combine to predict the US

if one CS already predicts the US, then pay less attention to all CSs on that trial when a new CS is added, should pay attention to it because it is novel therefore, should see some conditioning to the new cue on the first trial based on the salience of the CS Pearce-Hall Model and Blocking only after first trial is over would the animal know that nothing new had happened

according to the model, should see blocking from trial 2 and onwards however, in most cases see blocking right from the start Pearce-Hall Model and Unblocking kAN = N-1 VAN-1 when subjects encounter a US that is not well predicted, or is surprising (either bigger or smaller), then subjects should pay attention to all CSs on that trial and get unblocking

because the formula includes the absolute value of N-1 VAN-1 it doesnt matter if the US is bigger or smaller if the US changes well see increase in attention and thus, learning Pearce-Hall Model and latent inhibition When the CS is given by itself, see decrease in attention to the CS over trials ( = 0)) However, a problem with the model is that it cannot explain the context-specificity of LI

If CS pre-exposures are given in one context, and conditioning occurs in a second context, there is no retardation of learning According to the model, k should be low regardless of context The Comparator Hypothesis developed by Ralph Miller this is a model of performance, not learning according to Miller, all CSs have excitatory power; there is no separate inhibitory process

the strength of performance (or CR) depends on the relative strength of the various excitatory associations a subject compares the excitatory strength of the explicit CS to the strength of other cues present in the situation, such as apparatus cues The Comparator Hypothesis when the strength of a CS is relatively greater than the background cues, get a measurable CR when the strength of a CS is weaker than the background cues, get weakened level of excitation (what

others might call inhibition) according to the theory, the competition between two excitatory reactions controls performance The Comparator Hypothesis during normal excitatory, get CS-US pairings but the US is also paired with background cues and these background cues are the comparator stimuli because these background cues are also present during the no-US condition, they are typically weaker than the explicit CS

so, under normal conditioning procedures, the CS has stronger excitatory strength than the comparator cues The Comparator Hypothesis during inhibitory conditioning, the CS is weak relative to the background cues during inhibitory conditioning, have CS no US pairings; but the background cues are paired with the US and the absence of the US thus, the CS is weaker than the background cues and see little CR to the CS

The Comparator Hypothesis Prediction After training one can manipulate the excitatory value of the context and this will affect the excitatory value of the CS E.g. After conditioning, give repeated exposure to the context alone followed by exposure to CS One will see greater responding to CS

Temporal Factor Models designed to explain the effects of time in conditioning effects of time not considered in US-processing models like the RW model nor in CS-processing models like the PH model CS-US interval is one important temporal variable a more critical temporal variable appears to be the ratio of the ISI to ITI Midterm Exam Thursday, Feb. 17, 20)0)5

-covers everything up to and including todays lecture -in the case of a storm, the exam will take place during the very next class

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