scholarly journals The redundancy effect is related to a lack of conditioned inhibition: Evidence from a task in which excitation and inhibition are symmetrical

2019 ◽  
Vol 73 (2) ◽  
pp. 260-278
Author(s):  
Tara Zaksaite ◽  
Peter M Jones
Keyword(s):  
Associative Strength ◽  
Individual Variation ◽  
Conditioned Inhibition ◽  
Causal Learning ◽  
Learning Effects ◽  
Inhibitory Effects ◽  
Wagner Model ◽  
Opposite Pattern ◽  
Redundancy Effect ◽  
Human Causal Learning

Rescorla and Wagner’s model of learning describes excitation and inhibition as symmetrical opposites. However, tasks used in human causal learning experiments, such as the allergist task, generally involve learning about cues leading to the presence or absence of the outcome, which may not reflect this assumption. This is important when considering learning effects which provide a challenge to this model, such as the redundancy effect. The redundancy effect describes higher causal ratings for the blocked cue X than for the uncorrelated cue Y in the design A+/AX+/BY+/CY–, the opposite pattern to that predicted by the Rescorla–Wagner model, which predicts higher associative strength for Y than for X. Crucially, this prediction depends on cue C gaining some inhibitory associative strength. In this article, we used a task in which cues could have independent inhibitory effects on the outcome, to investigate whether a lack of inhibition was related to the redundancy effect. In Experiment 1, inhibition for C was not detected in the allergist task, supporting this possibility. Three further experiments using the alternative task showed that a lack of inhibition was related to the redundancy effect: the redundancy effect was smaller when C was rated as inhibitory. Individual variation in the strength of inhibition for C also determined the size of the redundancy effect. Given that weak inhibition was detected in the alternative scenario but not in the allergist task, we recommend carefully choosing the type of task used to investigate associative learning phenomena, as it may influence results.

Generality of the Summation Effect in Human Causal Learning

2009 ◽  
Vol 62 (5) ◽  
pp. 877-889 ◽  
Author(s):  
Fabian A. Soto ◽  
Edgar H. Vogel ◽  
Ramón D. Castillo ◽  
Allan R. Wagner
Keyword(s):  
Associative Strength ◽  
Causal Learning ◽  
Summation Test ◽  
Average Strength ◽  
Simple Method ◽  
Performance Constraints ◽  
Summation Effect ◽  
Considerable Research ◽  
Human Causal Learning ◽  
Theoretical Predictions

Considerable research has examined the contrasting predictions of the elemental and configural association theories proposed by Rescorla and Wagner (1972) and Pearce (1987), respectively. One simple method to distinguish between these approaches is the summation test, in which the associative strength attributed to a novel compound of two separately trained cues is examined. Under common assumptions, the configural view predicts that the strength of the compound will approximate to the average strength of its components, whereas the elemental approach predicts that the strength of the compound will be greater than the strength of either component. Different studies have produced mixed outcomes. In studies of human causal learning, Collins and Shanks (2006) suggested that the observation of summation is encouraged by training, in which different stimuli are associated with different submaximal outcomes, and by testing, in which the alternative outcomes can be scaled. The reported experiments further pursued this reasoning. In Experiment 1, summation was more substantial when the participants were trained with outcomes identified as submaximal than when trained with simple categorical (presence/absence) outcomes. Experiments 2 and 3 demonstrated that summation can also be obtained with categorical outcomes during training, if the participants are encouraged by instruction or the character of training to rate the separately trained components with submaximal ratings. The results are interpreted in terms of apparent performance constraints in evaluations of the contrasting theoretical predictions concerning summation.

scholarly journals Representing uncertainty in the Rescorla-Wagner model: Blocking, the redundancy effect, and outcome base rate

2021 ◽  
pp. 14-21
Author(s):  
Stuart G. Spicer ◽  
Andy J. Wills ◽  
Peter M. Jones ◽  
Chris J. Mitchell ◽  
Lenard Dome
Keyword(s):  
Associative Learning ◽  
Associative Strength ◽  
Open Science ◽  
Base Rate ◽  
Cue Competition ◽  
Wagner Model ◽  
Modified Model ◽  
Redundancy Effect ◽  
Causal Status ◽  
Intermediate Value

It is generally assumed that the Rescorla and Wagner (1972) model adequately accommodates the full results of simple cue competition experiments in humans (e.g. Dickinson et al., 1984), while the Bush and Mosteller (1951) model cannot. We present simulations that demonstrate this assumption is wrong in at least some circumstances. The Rescorla-Wagner model, as usually applied, fits the full results of a simple forward cue-competition experiment no better than the Bush-Mosteller model. Additionally, we present a novel finding, where letting the associative strength of all cues start at an intermediate value (rather than zero), allows this modified model to provide a better account of the experimental data than the (equivalently modified) Bush-Mosteller model. This modification also allows the Rescorla-Wagner model to account for a redundancy effect experiment (Uengoer et al., 2013); something that the unmodified model is not able to do. Furthermore, the modified Rescorla-Wagner model can accommodate the effect of varying the proportion of trials on which the outcome occurs (i.e. the base rate) on the redundancy effect (Jones et al., 2019). Interestingly, the initial associative strength of cues varies in line with the outcome base rate. We propose that this modification provides a simple way of mathematically representing uncertainty about the causal status of novel cues within the confines of the Rescorla-Wagner model. The theoretical implications of this modification are discussed. We also briefly introduce free and open resources to support formal modelling in associative learning. Keywords: associative learning, prediction error, uncertainty, modelling, blocking, redundancy effect, open science.

Blocking of Conditioned Inhibition in Human Causal Learning

2009 ◽  
Vol 56 (6) ◽  
pp. 381-385 ◽  
Author(s):  
Anja Lotz ◽  
Bram Vervliet ◽  
Harald Lachnit
Keyword(s):  
Conditioned Inhibition ◽  
Causal Learning ◽  
Cue Competition ◽  
Learning Study ◽  
Human Causal Learning

Compared to blocking of conditioned excitation, which is one of the most investigated cue competition phenomena, blocking of conditioned inhibition has more or less been neglected in conditioning research. We conducted a human causal learning study and found evidence for blocking of conditioned inhibition. The results favor the view that inhibition is the symmetrical opposite of excitation, underlying the same general principles.

Higher-Order Retrospective Revaluation in Human Causal Learning

2002 ◽  
Vol 55 (2b) ◽  
pp. 137-151 ◽  
Author(s):  
Jan De Houwer ◽  
Tom Beckers
Keyword(s):  
Higher Order ◽  
Second Order ◽  
Causal Learning ◽  
Retrospective Revaluation ◽  
Wagner Model ◽  
Third Order ◽  
Contrast Model ◽  
Human Causal Learning ◽  
Causal Status ◽  
Comparator Model

Previous studies demonstrated that participants will retrospectively adjust their ratings about the relation between a target cue and an outcome on the basis of information about the causal status of a competing cue that was previously paired with the target cue. We demonstrate that such retrospective revaluation effects occur not only for target cues with which the competing cue was associated directly, but also for target cues that were associated indirectly with the competing cue. These second-order and third-order retrospective revaluation effects are compatible with certain implementations of the probabilistic contrast model and with a modified, extended comparator model, but cannot be explained on the basis of a revised Rescorla—Wagner model or a revised SOP model.

scholarly journals The redundancy effect in human causal learning: No evidence for changes in selective attention

2018 ◽  
Vol 71 (8) ◽  
pp. 1748-1760 ◽  
Author(s):  
Peter M Jones ◽  
Tara Zaksaite
Keyword(s):  
Selective Attention ◽  
Associative Learning ◽  
Learning Task ◽  
Causal Learning ◽  
Eye Tracker ◽  
Initial Training ◽  
Learning Models ◽  
Redundancy Effect ◽  
Overt Attention ◽  
Human Causal Learning

Several recent papers have reported a difference in associative learning for two kinds of redundant cues, such that a blocked cue (e.g., X in A+ AX+) apparently forms a stronger association with the outcome than an uncorrelated cue (e.g., Y in BY+ CY-). This difference is referred to as the redundancy effect, and is of interest because it is contrary to the predictions of a number of popular learning models. One way of reconciling these models with the redundancy effect is to assume that the amount of attention paid to redundant cues changes as a result of experience, and that these changes in attention influence subsequent learning. Here, we present two experiments designed to evaluate this idea, in which we measured overt attention using an eye tracker while participants completed a learning task that elicited the redundancy effect. In both experiments, gaze duration was longer for uncorrelated cues than for blocked cues, but this difference disappeared when we divided gaze durations by trial durations. In Experiment 2, we failed to observe any difference in gaze duration when blocked and uncorrelated cues were subsequently presented together. While the observed difference in gaze duration for the two types of redundant cue may contribute to differences in learning during initial training, we suggest that the principal causes of the redundancy effect are likely to lie elsewhere.

Inhibition of Shuttlebox-Avoidance Behavior Resulting from a Reduction in the Magnitude of Reinforcement

1982 ◽  
Vol 51 (2) ◽  
pp. 499-506 ◽  
Author(s):  
M. M. Cotton ◽  
K. Green ◽  
A. Trlin
Keyword(s):  
Avoidance Response ◽  
Shock Intensity ◽  
Avoidance Behavior ◽  
Conditioned Inhibition ◽  
Conditioning Phase ◽  
Shuttlebox Avoidance ◽  
Inhibitory Effects ◽  
Wagner Model ◽  
Conditioned Inhibitor ◽  
Inhibitory Conditioning

Three experiments studied inhibitory conditioning in an unsignalled shuttlebox-avoidance preparation with rats. Following a Pavlovian conditioning phase and using a summation test in which test stimuli were superimposed on a previously established ongoing shuttlebox-avoidance response, it was found in Exp. 1 that a light could be established as an inhibitor of avoidance when it signalled the absence of shock. Exp. 2 established that a light could become a conditioned inhibitor when it signalled a reduction in shock intensity rather than its complete absence. Exp. 3 confirmed this general finding but did not yield differential inhibitory effects with different degrees of reduction in shock intensity for the particular parameters chosen. The findings can be adequately interpreted in terms of the Rescorla-Wagner model of conditioned inhibition.

scholarly journals Representing uncertainty in the Rescorla-Wagner model: blocking, the redundancy effect, and outcome base rate

2021 ◽  
Author(s):  
Stuart Spicer ◽  
Andy Wills ◽  
Peter M Jones ◽  
Chris Mitchell ◽  
Lenard Dome
Keyword(s):  
Associative Strength ◽  
Base Rate ◽  
Cue Competition ◽  
Wagner Model ◽  
Modified Model ◽  
Redundancy Effect ◽  
Causal Status ◽  
Intermediate Value ◽  
Effect Experiment ◽  
Better Than

It is generally assumed that the Rescorla and Wagner (1972) model adequately accommodates the full results of simple cue competition experiments in humans (e.g. Dickinson et al., 1984), while the Bush and Mosteller (1951) model cannot. We present simulations that demonstrate this assumption is wrong in at least some circumstances. The Rescorla-Wagner model, as usually applied, fits the full results of a simple forward cue-competition experiment no better than the Bush-Mosteller model. Additionally, we present a novel finding, where letting the associative strength of all cues start at an intermediate value (rather than zero), allows this modified model to provide a better account of the experimental data than the (equivalently modified) Bush-Mosteller model. This modification also allows the Rescorla-Wagner model to account for a redundancy effect experiment (Uengoer et al., 2013); something that the unmodified model is not able to do. Furthermore, the modified Rescorla-Wagner model can accommodate the effect of varying the proportion of trials on which the outcome occurs (i.e. the base rate) on the redundancy effect (Jones et al., 2019). Interestingly, the initial associative strength of cues varies in line with the outcome base rate. We propose that this modification provides a simple way of mathematically representing uncertainty about the causal status of novel cues within the confines of the Rescorla-Wagner model. The theoretical implications of this modification are discussed. We also briefly introduce free and open resources to support formal modelling in associative learning.

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