rescorla's correlation experiments note that rescorla referred to his experiments as...

Rescorla's Correlation Rescorla's Correlation *Experiments*Experiments

* Note that Rescorla referred to his experiments as contingency experiments, however since a true contingency (cause-effect relationship) does not exist between the CS & UCS in classical conditioning experiments, they are more properly described as correlation experiments.

CS-UCS relations (correlation) CS-UCS relations (correlation) Contiguity is necessary but NOT sufficient

for classical conditioning to occur There must also be a consistent relationship

or correlation between the CS and the UCS. To experience a reliable correlation

between the CS and the UCS the subjects must be exposed to numerous instances of the CS and UCS, thus many trials are typically necessary for conditioning.

Types of correlations between Types of correlations between the CS and the UCS - #1the CS and the UCS - #1

If the CS is a reliable predictor of the presence of the UCS, then the CS and UCS are positively correlated.

CS

UCS

Types of correlations between Types of correlations between the CS and the UCS - #2the CS and the UCS - #2

If the CS is an unreliable predictor of the UCS, then the CS and UCS are not correlated.

CS

UCS

Types of correlations between Types of correlations between the CS and the UCS -#3the CS and the UCS -#3

If the CS reliably predicts the absence of the UCS, then the CS and UCS are negatively correlated.

CS

UCS

Rescorla’s EquationsRescorla’s Equations

It is inconvenient to draw time lines for experiments with large number of trials.

We will use equations which describe the type of correlation that a subject experiences in a classical conditioning experiment.

Rescorla’s Equation describing a Rescorla’s Equation describing a positive correlation between the positive correlation between the

CS & UCSCS & UCS

the probability (p) of a UCS given that (/) a CS is present *** is GREATER THAN*** the probability (p) of a UCS given that (/) NO CS is present

p (UCS / CS) > p (UCS / No CS)


CS & UCSCS & UCSp (UCS / CS) > p (UCS / No CS)

The left side of the equation simply notes the percentage of CSs that are temporally

contiguous (paired) with a UCS. •If p = 1.0 then 100% of CSs are paired with UCSs

•If p = 0.5 then 50% CSs are paired with UCSs and 50% of CSs are presented alone.

•If p = 0.0 then all the CSs are presented alone, there are no CS-UCS pairings.


CS & UCSCS & UCSp (UCS / CS) > p (UCS / No CS)

The right side of the equation simply notes the percentage of time intervals without a CS in which a UCS occurs.

•If p = 1.0 then UCSs are presented on 100% of the time intervals with No CS present.

•If p = 0.5 then UCSs are presented on 50% of the time intervals with No CS present.

•If p = 0.0 then UCSs are never presented when No CS is present.

Rescorla’s Equation describing Rescorla’s Equation describing positive correlations between positive correlations between

the CS & UCSthe CS & UCS

1.0 > 0

.5 > 0

.4 > .1

.3 > .2

p (UCS / CS) p (UCS / No CS)

When these correlations are used in classical conditioning experiments the subjects show evidence of excitatory conditioning

Notice that the percentage of contiguous CS-UCS pairings decrease from the top example to the bottom example

Rescorla’s Equation describing no Rescorla’s Equation describing no correlation between the CS & UCScorrelation between the CS & UCS

p (UCS / CS) = p (UCS / No CS)

the probability (p) of a UCS given that (/) a CS is present *** is EQUAL to ***the probability (p) of a UCS given that NO CS is present

Rescorla’s Equation describingRescorla’s Equation describing no correlation between no correlation between



.8 = .8

.5 = .5

.4 = .4

.3 = .3

.2 = .2

When these correlations are used in classical conditioning experiments the subjects show no evidence of conditioning

Rescorla’s Equation describing Rescorla’s Equation describing negative correlations between negative correlations between


p (UCS / CS) < p (UCS / No CS)

0 < .5

.2 < .5

.3 < .5

.4 < .5


When these correlations are used in classical conditioning experiments the subjects show evidence of inhibitory conditioning

Calculate Rescorla’s equation Calculate Rescorla’s equation using the time lines below using the time lines below

CS

UCS

First take notice that time line is divided into 12 equal intervals of time.Next we will calculate the left side of the equation

p (UCS / CS) ? p (UCS / No CS)

There are 4 time intervals with a CS

/ 4

A UCS occurs in all 4 CS intervals

4 = 1.0

Therefore the probability of a UCS given the presence of a CS is 1.0


CS

UCS

Next we will calculate the right side of the equation


There are 8 time intervals with No CS

/ 4

A UCS occurs in 0 of these No-CS intervals

4 = 1.0

Therefore the probability of a UCS given the absence of a CS is 0

= 0.0/ 80

>





/ 4

A UCS occurs in only 1 of the CS intervals

1 = 0.25


CS

UCS





/ 4


1 = 0.25

Therefore the probability of a UCS given the absence of a CS is 0.25

= 0.25/ 82

=

CS

UCS





/ 4

A UCS occurs in none of the CS intervals

0 = 0.0


CS

UCS





/ 4


0 = 0.0

Therefore the probability of a UCS given the absence of a CS is 0.38

= 0.38/ 83

<

CS

UCS

SummarySummary When subjects experience CSs and UCSs

that are positively correlated they acquire a conditioned response to the CS; this is called excitatory conditioning.

When subjects experience CSs and UCSs that are negatively correlated responses are inhibited (not performed) when the CS is present; this is called inhibitory conditioning or conditioned inhibition.

SummarySummary continued continued

When subjects experience CSs and UCSs that are NOT correlated they show no evidence of conditioning.

VocabularyVocabulary

positive correlation negative correlation excitatory conditioning inhibitory conditioning or conditioned

inhibition

Using Rescorla’s equations to show differences in Using Rescorla’s equations to show differences in conditioning despite fixed contiguity between groupsconditioning despite fixed contiguity between groups

.4 > 0

.4 > .1

.4 > .2

.4 = .4


CS - Alone Trials after Acquisition

0

0.1

0.2

0.3

0.4

0.5

Supp

ress

ion

Ratio

0 0.1 0.2 0.4

p (UCS | no CS)

Contiguity as necessary but not sufficientContiguity as necessary but not sufficient

The results of the previous experiment, as well as the results of the blocking studies and other experiments, suggest that although contiguity is necessary for classical conditioning to occur it is not enough (not sufficient), the CS and the UCS must be correlated either positively or negatively.

Explanations of Rescorla’s Explanations of Rescorla’s Correlation ExperimentsCorrelation Experiments

COGNITIVE BEHAVIORIST: a correlation is also necessary because the CS must be predictive or informative. 1. When a CS is positively correlated with a UCS the subjects learn that the CS predicts the presence of a UCS. 2. When a CS is negatively correlated with a UCS the subjects learn that the CS predicts the absence of a UCS. This is a highly cognitive explanation of classical conditioning.

Explanations of Rescorla’s Explanations of Rescorla’s Correlation ExperimentsCorrelation Experiments

RADICAL BEHAVIORIST: positive and negative correlations affect the acquisition of conditioned responding because several basic, mechanistic principles are at work. For example, when several UCSs are presented alone to degrade the CS-UCS correlation the context becomes excitatory and blocks conditioning to the CS.

rescorla's correlation experiments note that rescorla referred to his experiments as...

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rescorla's correlation *experiments * note that rescorla referred to his experiments as...

rescorla's correlation experiments note that rescorla referred to his experiments as...