Transcript COMPOUND CONDITIONING UNDER TEMPORAL UNCERTAINTY Robert J. Polewan & John W. Moore* University of Massachusetts Amherst Neuroscience & Behavior Program Compound Conditioning Under Temporal Uncertainty 

COMPOUND CONDITIONING UNDER
TEMPORAL UNCERTAINTY
Robert J. Polewan & John W. Moore*
University of Massachusetts Amherst
Neuroscience & Behavior Program
Compound Conditioning Under Temporal Uncertainty
 Eyeblink conditioning has long been a model for
understanding behavioral and physiological
processes of learning, memory, and
performance.
 The present research extends our previous
studies of rabbit eyeblink conditioning under
temporal uncertainty to compound conditioning.
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Temporal Uncertainty Training
 Rabbits were trained to make eyeblink
conditioned responses (CRs) to a compound
conditioned stimulus (CS) consisting of a tone
(T) and a light (L) presented simultaneously an
reinforced with an unconditioned stimulus (US).
 This training involved a mixture of two CS-US
intervals. On some trials, the US occurred 300
ms after CS onset; on other trials, the US
occurred 700 ms after CS onset.
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Temporal Uncertainty Training
 Randomly mixing trials with these CS-US
intervals produced bimodal CR waveforms with
amplitude peaks located at the two temporal loci
of the US, temporal windows centered at 300
and 700 ms.
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TD (CSC) model
 Sutton and Barto’s (1990) TD (CSC) model is a
representational system capable of describing
the complex conditioned response waveforms
instilled through training under temporal
uncertainty.
 The model assumes a delay-line timing structure.
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Delay-line Timing Structure

Basic tapped delay-line. Injection of CS input begins sequential
propagation of signal through a delay-line. Each synapse (—<)
introduces a delay; the total delay from activation of the first
element in the delay-line to the last element is a direct function
of the number of sequential synapses. Taps from the delay-line
units send timing information to higher-order processing units.
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Compound Conditioning Under Temporal Uncertainty
 Like the Rescorla-Wagner model, the TD (CSC)
model assumes that CR performance to a
compound stimulus is the sum of the
“associative strengths” of the components.
 In order to test this assumption, it is necessary
to specify how the theoretical indices of CR
associative strength map onto real measures of
performance such as CR amplitude.
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Compound Conditioning Under Temporal Uncertainty
 Summation of CR amplitudes to component
stimuli should reconstitute the CR waveforms
obtained under compound conditioning.
 Deviations from a “simple summation” rule
should indicate shortcomings and point the way
to improving the model.
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Compound Conditioning Under Temporal Uncertainty
 Factors that could challenge a simple summation
rule for reconstituting a compound CR waveform
from its components include
• Configuring/patterning
• Overshadowing
• Transfer from prior training.
 In addition, floor effects (thresholds) and ceiling
effects (saturation) could complicate assessment
of the model in terms of CR amplitudes.
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Pretraining
 Prior to compound conditioning training half of
the 24 rabbits were pretrained to one CS
(predominantly a light) at one of the two CS-US
intervals.
 Pretrained rabbits were run concurrently with
yoked control rabbits.
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Averaged Topographical CR Waveforms
ALL RABBITS
Sessions 16-20
EYELID POSITION (MM)
8
7
6
5
4
3
2
1
0
TL- + 2SEM
n = 24
Peak 1 = 5.7543 mm @ 356 ms; Peak 2 = 5.1005 mm @ 724 ms
8
7
6
5
4
3
2
1
0
L- + 2SEM
Peak 1 = 1.9541 mm @ 432 ms; Peak 2 = 1.9379 mm @ 792 ms
n = 24
8
7
6
5
4
3
2
1
0
T- + 2SEM
n = 24
0
200
Peak 1 = 3.4884 mm @ 384 ms; Peak 2 = 3.2151 mm @ 772 ms
400
600
800
1000
1200
TIME FROM CS ONSET (MS)
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Averaged Topographical CR Waveforms
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Peak Amplitudes in Decomposition
Peak Amplitude (mm)
Pretrained & Controls
8
7
6
5
4
3
2
1
0
TLLT-
PRE Peak 1
PRE Peak 2
CONT Peak 1
CONT Peak 2
Group and Peak Position

Mean peak amplitudes (+SE) to TL-, L-, and T- for the 12
pretrained (PRE) and 12 control rabbits (CONT) at both peak
locations in the fourth session-block of training.
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Decomposition Peak Latencies Shifts
Pretrained & Controls
Peak Latency (ms)
900
800
700
600
500
TL-
400
300
T-
L-
200
100
0
PRE Peak 1
PRE Peak 2
CONT Preak 1
CONT Peak 2
Group and Peak Location

Mean peak latencies (+SE) to TL-, L-, and T- for 12 pretrained
(PRE) and 12 control rabbits (CONT) at both peak locations in the
fourth session-block of training.
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Proportional Contribution
Proportion
Proportional Contribution
1.0
0.9
0.8
0.7
0.6
0.5
0.4
0.3
0.2
0.1
0.0
PRE TCONT T-
1
2
3
4
Session Blocks

Mean proportional contribution of T- to the compound waveform
for both pretrained subjects (PRE) and control subjects (CONT).
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Gain Factors
Gain Factors (N = 24)
3.0
Gain Factor
2.5
2.0
PRE
1.5
CONT
1.0
0.5
0.0
1
2
3
4
Session Blocks

Mean gain factors of T- and L- for pretrained subjects (PRE) and
control subjects (CONT).
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Sum of Squared Deviations
Sum of Squared Deviation for the Combination Rules
Sum of Squared Deviation
4000
3500
Pretrained
3000
Control
2500
2000
1500
1000
500
0
LSR
MRR OSR
SSR MPR
TR
WSR SAR
LR
Comnination Rules

Mean (+SE) Sum of Squared Deviations (SSDs) for pretrained (n
= 12) and control rabbits (n = 12) for nine combination rules in
the last block of sessions.
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Summary of Findings
 Decomposition slowed the initiation of the motor
program representing CR waveforms.
 The latency of initiation was greater for the light
than the tone, consistent with the tone’s greater
salience, as indexed by the tones greater
proportional contribution to the compound.
 Decomposition did not affect other features of
component CR waveforms, as inter-peak
intervals remained unchanged.
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Summary of Findings
 The slower initiation of the motor program did
not result in a later “catching up” such that the
second amplitude peak appeared within the 700ms temporal window. Nor did the slower
initiation result a greater temporal separation of
amplitude peaks.
 In terms of the spreading activation account of
CR topography proposed by the TD (CSC) model,
the speed of propagation remained the
unchanged.
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Discussion
 The slower initiation of component CR waveforms
following compound conditioning may reflect a
“processing cost.”
 Pearce has suggested that compound CSs are
gestalts, and that changes in performance to
component stimuli are “generalization
decrements.”
 If so, the costs of decomposition did not extend
to CR amplitudes, as amplitudes adhered to a
summation combination rule.
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Acknowledgments
Moore Lab
•
•
•
•
•
•
Vanessa Castagna
Jamy Gaynor
Jordan Marks
Tony Rauhut
June-Seek Choi
Marcy Rosenfield
 Thank You
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Summation Experiment
 Rabbits were trained with individual CSs, with
each CS trained at a different CS-US interval
(light at 300 ms and tone at 700 ms).
 The two CSs were only presented together on
probe trials.
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Averaged Summation CR Waveforms
ALL RABBITS
Sessions 16-20
EYELID POSITION (MM)
8
7
6
5
4
3
2
1
0
TL- + 2SEM
n=4
Peak = 4.6648 mm @ 772 ms
8
7
6
5
4
3
2
1
0
L- + 2SEM
Peak = 5.2006 mm @ 368 ms
n=4
8
7
6
5
4
3
2
1
0
T- + 2SEM
n=4
0
Peak = 3.8265 mm @ 824 ms
200
400
600
800
1000
1200
TIME FROM CS ONSET (MS)
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Pretrained & Control Summation Rabbits
CONTROL
Subject B Sessions 21-25
PRETRAINED
Subject A Sessions 21-25
A TL- + 2SEM
8
7
6
5
4
3
2
1
0
A L- + 2SEM
8
7
6
5
4
3
2
1
0
A T- + 2SEM
0
200
8
7
6
5
4
3
2
1
0
peak = 5.0234 mm @ 756 ms
peak = 6.3253 mm @ 368 ms
600
800
TIME FROM CS ONSET (MS)
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A TL- + 2SEM
8
7
6
5
4
3
2
1
0
1200
peak = 7.0509 mm @ 692 ms
A L- + 2SEM
8
7
6
5
4
3
2
1
0
peak amplitude = 3.9108 mm @ 840 ms
400
EYELID POSITION (MM)
EYELID POSITION (MM)
8
7
6
5
4
3
2
1
0
A T- + 2SEM
0
200
400
600
peak = 6.8979 mm @ 352 ms
peak amplitude = 6.8169 mm @ 716 ms
800
1000
1200
TIME FROM CS ONSET (MS)
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Summation Results

Waveforms to compound CS showed a unimodal
peak that was between the component peaks in
both amplitude and latency.

The peak amplitude favored the more salient
tone CS resulting in a “Performance
Overshadowing Effect.”
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Performance Overshadowing/ Summated Generalization
 The characteristic waveform for one stimulus
(tone) is dominated the characteristic waveform
for the other stimulus (light) because of the
tone’s higher salience, even though the light
stimulus is pretrained.
 One possible explanation for the intermediate
temporal position of the peak is summated
generalization, similar to summated
generalization along dimensions such as auditory
frequency (Moore, 1972).
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Effects of Pretraining
Pretrained & Controls
Peak Amplitude (mm)
8
7
6
5
TL-
4
L-
3
T-
2
1
0
PRE Peak 1
Pre Peak 2
CONT Peak 1
CONT Peak 2
Group and Peak Location
 Mean peak amplitudes (+SE) to TL-, L-, and T- for the 6
rabbits pretrained to light at the 300-ms ISI (PRE) and
their 6 yoked controls (CONT) at both peak locations in the
fourth session-block of training.
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