Comparing elemental and configural associative theories in human causal learning: a case for attention

In two causal learning experiments with human participants, the authors compared various associative theories that assumed either elemental (unique cue, modified unique cue, replaced elements model, and Harris' model) or configural processing of stimuli (Pearce's theory and a modification of it). The authors used modified patterning problems initially suggested by Redhead and Pearce (1995). Predictions for all theories were generated by computer simulations. Both configural theories and the unique cue approach failed to account for the observations. The replaced elements model was able to account for part of the data, but only if the replacement parameters could vary across discrimination problems. The Harris model and the modified unique cue approach, assuming that the salience of stimuli decreases with an increasing number of stimuli in a compound, successfully accounted for all of our data. This success implies that attentional factors should be explicitly taken into account in associative learning theory.     

Multimodal discrimination learning in humans: evidence for configural theory

Human contingency learning was used to compare the predictions of configural and elemental theories. In three experiments, participants were required to learn which indicators were associated with an increase in core temperature of a fictitious nuclear plant. Experiments 1 and 2 investigated the rate at which a triple-element stimulus (ABC) could be discriminated from either single-element stimuli (A, B, and C) or double-element stimuli (AB, BC, and AC). Experiment 1 used visual stimuli, whilst Experiment 2 used visual, auditory, and tactile stimuli. In both experiments the participants took longer to discriminate the triple-element stimulus from the more similar double-element stimuli than from the less similar single-element stimuli. Experiment 3 tested for summation with stimuli from either a single or multiple modalities, and summation was found only in the latter case. Thus, the pattern of results seen in Experiments 1 and 2 was not dependent on whether the stimuli were single modal or multimodal, nor was it dependent on whether the stimuli could elicit summation. This pattern of results is consistent with predictions derived from Pearce's (1987, 1994) configural theory.     

Peak Shift on an Artificial Dimension

Blough (1975) proposed an elemental model of generalization and discrimination phenomena in which stimuli from physical dimensions, such as wavelength, are conceptualized as overlapping sets of elements. In order to test predictions generated by this model, we constructed an artificial 'dimension' of stimuli as a series of overlapping sets of arbitrary 'icons' (small, unrelated shapes). In Experiment 1, we trained pigeons to discriminate two neighbouring stimuli from this artificial dimension and then assessed their responses to other stimuli from the dimension. The results of these tests typified those obtained with stimuli from genuine physical dimensions-that is, we obtained positive and negative peak shifts. In Experiment 2, human subjects were given a similar discrimination task and produced an analogous set of results to those of the pigeons. These results support Blough's elemental theory and are not readily accommodated by Pearce's (1987) configural theory. In Experiment 3, both humans and pigeons were trained and tested with stimuli from a real physical dimension (luminance). The pigeons' results were again consistent with Blough's analysis, but those of the humans suggested the use of more sophisticated strategies that are unavailable to pigeons and that lie outside the scope of elemental models of discrimination learning.     

ALTSim: A MATLAB simulator for current associative learning theories

ALTSim is a MATLAB-based simulator of several associative learning models, including Pearce’s configural model, the extended configural model, the Rescorla-Wagner model, the unique cue hypothesis, the modified unique cue hypothesis, the replaced elements model, and Harris’s elemental model. It allows for specifying all relevant parameters, as well as exact stimulus sequences by graphical user interfaces. It is an easy-to-use tool that facilitates evaluating and comparing the featured associative learning models. ALTSim is available free of charge from www.staff.uni-marburg.de/~lachnit/ALTSim/.     

A modified version of the unique cue theory accounts for olfactory compound processing in honeybees

We investigated the capability of honeybees to discriminate between single odorants, binary olfactory mixtures, and ternary olfactory mixtures in olfactory conditioning of the proboscis extension reflex. In Experiment 1, three single odorants (A+, B+, and C+) and three binary mixtures of these odors (AB+, AC+, and BC+) were reinforced while the ternary compound, consisting of all three odors (ABC-), was nonreinforced. In Experiment 2, only one single odorant (A+) and one binary olfactory compound (BC+) were reinforced while the ternary compound (ABC-) consisting of the single odor and the binary compound was nonreinforced. We studied whether bees can solve these problems and whether the course of differentiation can be predicted by the unique cue theory, a modified unique cue theory, or Pearce's configural theory. Honeybees were not able to differentiate reinforced from nonreinforced stimuli in Experiment 1. However, summation to ABC observed at the beginning of training contradicts the predictions of Pearce's configural theory. In Experiment 2, differentiation between the single odorant A and the ternary compound developed more easily than between the binary compound BC and ABC. This pattern of differentiation is in line with a modified unique cue theory and Pearce's configural theory. Summation to ABC at the beginning of training, however, again was at odds with Pearce's configural theory. Thus, olfactory compound processing in honeybees can best be explained by a modified unique cue theory.     

Elemental representations of stimuli in associative learning

This article reviews evidence and theories concerning the nature of stimulus representations in Pavlovian conditioning. It focuses on the elemental approach developed in stimulus sampling theory (R. C. Atkinson & W. K. Estes, 1963; R. R. Bush & F. Mosteller, 1951b) and extended by I. P. L. McLaren and N. J. Mackintosh (2000, 2002) and contrasts this with models that invoke notions of configural representations that uniquely code for different patterns of stimulus inputs (e.g., J. M. Pearce, 1987, 1994; R. A. Rescorla & A. R. Wagner, 1972; A. R. Wagner & S. E. Brandon, 2001). The article then presents a new elemental model that emphasizes interactions between stimulus elements. This model is shown to explain a range of behavioral findings, including those (e.g., negative patterning and biconditional discriminations) traditionally thought to be beyond the explanatory capabilities of elemental models. Moreover, the model offers a ready explanation for recent findings reported by R. A. Rescorla (2000, 2001, 2002b) concerning the way that stimuli with different conditioning histories acquire associative strength when conditioned in compound.     

Discriminating the stimulus elements during human odor-taste learning: a successful analytic stance does not eliminate learning

Odor "sweetness" may arise from experiencing odors and tastes together, resulting in a flavor memory that is later reaccessed by the odor. Forming a flavor memory may be impaired if the taste and odor elements are apparent during exposure, suggesting that configural processing may underpin learning. Using a new procedure, participants made actual flavor discriminations for one odor-taste pair (e.g., Taste A vs. Odor X-Taste A) and mock discriminations for another (e.g., Odor Y-Taste B vs. Odor Y-Taste B). Participants, who were successful at detecting the actual flavor discriminations, demonstrated equal amounts of learning for both odor-taste pairings. These results suggest that although a capacity to discriminate flavor into its elements may be necessary to support learning, whether participants experience a configural or elemental flavor representation may not.     

Development of a computer program to simulate the predictions of the replaced elements model of Pavlovian conditioning

Despite of the apparent simplicity of Pavlovian conditioning, research on its mechanisms has caused considerable debate, such as the dispute about whether the associated stimuli are coded in an "elementistic"(a compound stimuli is equivalent to the sum of its components) or a "configural" (a compound stimuli is a unique exemplar) fashion. This controversy is evident in the abundant research on the contrasting predictions of elementistic and the configural models. Recently, some mixed solutions have been proposed, which, although they have the advantages of both approaches, are difficult to evaluate due to their complexity. This paper presents a computer program to conduct simulations of a mixed model ( replaced elements model or REM). Instructions and examples are provided to use the simulator for research and educational purposes.     

Summation in causal learning: Elemental processing or configural generalization?

Results from human causal learning tasks that employ multiple cues are often interpreted in terms of the elemental theory of Rescorla and Wagner (1972). However, most results can also be successfully interpreted by the configural model proposed by Pearce (1987, 1994). One method of discriminating between these alternatives is through an investigation of summation and overexpectation. Indeed, demonstrations of these phenomena are fundamental to an elemental approach but are generally incompatible with an account that involves configural processing. Using a procedure in which the magnitude of the outcome varied, evidence for both summation and overexpectation was obtained in two experiments.     

Summation in causal learning: elemental processing or configural generalization?

Results from human causal learning tasks that employ multiple cues are often interpreted in terms of the elemental theory of Rescorla and Wagner (1972). However, most results can also be successfully interpreted by the configural model proposed by Pearce (1987, 1994). One method of discriminating between these alternatives is through an investigation of summation and overexpectation. Indeed, demonstrations of these phenomena are fundamental to an elemental approach but are generally incompatible with an account that involves configural processing. Using a procedure in which the magnitude of the outcome varied, evidence for both summation and overexpectation was obtained in two experiments.     

Elemental and Configural Processes in Patterning Discrimination Learning

Three experiments used appetitive conditioning with rats to examine the involvement of elemental and configural processes in positive and negative patterning discriminations. The first experiment demonstrated that negative and, to some extent, positive patterning discriminations were learned more rapidly when these discriminations consisted of stimulus elements that had previously been the reinforced as opposed to the non-reinforced elements of a simple discrimination. Experiment 2 revealed an excitatory summation effect during the early phase of negative patterning learning that depended upon discrimination pretraining. The final experiment demonstrated faster discrimination learning between the compound and the less salient, rather than the more salient, element of an instrumental patterning task. The present set of results were interpreted as reflecting the possibility, consistent with connectionist theory, that internal representations of the conditioned stimuli change over the course of a patterning discrimination.     

Context-sensitive elemental theory

My theories of associative learning, like those of N. J. Mackintosh and almost all learning theorists, have employed elemental representations of the stimuli involved. We must take notice when two important contributors to elemental theory, J. M. Pearce and W. K. Estes, find sufficient problems with the theory type to cause them to defect from it. I will describe some of the essential problems, concerning the substantial influence of context on learning and retrieval, characterize the different responses of Pearce and Estes, and, then, propose a variation on a recently developed elemental model that was similarly inspired. The resulting elemental theory has a close quantitative relationship to the “product-rule” of Estes and D. L. Medin, and may help us to rationalize how the same formal experimental design can sometimes produce results that favour the configural interpretation of Pearce and at other times the elemental interpretation of R. A. Rescorla and A. R. Wagner, as these have often been pitted against each other.     

Multimodal discrimination learning in humans: Evidence for configural theory

Human contingency learning was used to compare the predictions of configural and elemental theories. In three experiments, participants were required to learn which indicators were associated with an increase in core temperature of a fictitious nuclear plant. Experiments 1 and 2 investigated the rate at which a triple-element stimulus (ABC) could be discriminated from either single-element stimuli (A, B, and C) or double-element stimuli (AB, BC, and AC). Experiment 1 used visual stimuli, whilst Experiment 2 used visual, auditory, and tactile stimuli. In both experiments the participants took longer to discriminate the triple-element stimulus from the more similar double-element stimuli than from the less similar single-element stimuli. Experiment 3 tested for summation with stimuli from either a single or multiple modalities, and summation was found only in the latter case. Thus, the pattern of results seen in Experiments 1 and 2 was not dependent on whether the stimuli were single modal or multimodal, nor was it dependent on whether the stimuli could elicit summation. This pattern of results is consistent with predictions derived from Pearce's (1987, 1994) configural theory.     

Extreme elemental processing in a high schizotypy population: Relation to cognitive deficits

The cognitive deficits observed in schizophrenia have been characterized as a failure to utilize task-setting information to guide behaviour, especially in situations in which there is response conflict. Recently, we have provided support for this account; high schizotypy individuals demonstrated inferior biconditional discrimination performance compared to low scorers, but were not impaired on a simple discrimination that did not require the use of task-setting cues. These results may, however, also be explained by the way in which individuals with high schizotypy process stimulus compounds. Here, we examine the initial approaches to solving biconditional and control discrimination tasks of participants with high and low schizotypy scores. In particular, we focus on performance during the first block of training trials to capture processing style before the acquisition of the discrimination tasks. Participants scoring highly on the introvertive anhedonia subscale (which has been allied to the negative and cognitive symptoms of schizophrenia) demonstrated better biconditional performance during the first block of training trials than did low-schizotypy individuals, consistent with a highly elemental approach to stimulus processing. Subsequent recognition tests confirmed this analysis demonstrating that the pattern of performance observed in participants with high schizotypy was associated with a failure to discriminate conjunctions of items that had been seen before from those that had not. These results suggest that the negative/cognitive symptoms of schizophrenia may reflect an extreme bias towards elemental, as opposed to configural, processing of stimulus conjunctions.     

Associative changes in elements and compounds when the other is reinforced.

Four experiments investigated the symmetry of associative changes in stimulus compounds and elements in a Pavlovian conditioned magazine-approach situation with rats. Experiment 1 used multiple groups to examine the associative changes in a conditioned element (A) as a result of its subsequent reinforcement in compound with a neutral X. These were compared with the changes in an AX compound when one of its elements (A) was subsequently reinforced alone. Although reinforcing A enhanced responding to the AX compound, compared with a control compound, reinforcing AX failed to enhance responding to A, compared with a control element. Experiments 2 and 3 made similar comparisons in a fully within-subject design, finding greater changes in a previously trained AX compound when A was subsequently conditioned than in a B element when BY was subsequently conditioned. Experiment 4 found associative decrements in A when it was reinforced in the presence of a moderately conditioned X. The results observed in each of these experiments are more consistent with an elemental model of conditioning than with a recently proposed configural model.     

Elemental and configural encoding of the conditioned stimulus.

Five experiments explored the effect of conditioning AB and CD compounds on responding to transfer AD and BC compounds and to elements. These experiments used several conditioning procedures: flavour aversion and instrumental discriminative learning in rats and autoshaping in pigeons. All of the experiments found greater responding to the trained AB and CD than to the transfer AD and BC compounds, a result that agrees with some configural models, but not with an elemental model. All experiments also found greater responding to the transfer AD and BC compounds than to the elements, a result that agrees with elemental, but not configural, models.     

Asymmetry of generalization decrement in causal learning

Two experiments required volunteers to learn which of various “planes” caused high levels of pollution. Novel test items were then rated as causes of pollution. Items created by adding novel features were rated at the same level as that of the original training items but items created by removing features received reduced ratings. This asymmetry of generalization decrement was not predicted by a well-known configural model of stimulus representation (Pearce, 1987, 1994) but was predicted by a recently proposed model of stimulus representation, the replaced-elements model (Brandon, Vogel, & Wagner, 2000).     

Evaluation and development of a connectionist theory of configural learning

A configural theory of associative learning is described that is based on the assumption that conditioning results in associations between the unconditioned stimulus and a representation of the entire pattern of stimulation that was present prior to its delivery. Configural theory was formulated originally to account for generalization and discrimination in Pavlovian conditioning. The first part of the article demonstrates how this theory can be used to explain results from studies of overshadowing, blocking, summation, and discrimination learning. The second part of the article shows how the theory can be developed to explain a broader range of phenomena, including mediated conditioning, reinforcer devaluation effects, the differential outcomes effect, acquired equivalence, sensory preconditioning, and structural discriminations.     

Some properties of configural learning: an investigation of the transverse-patterning problem.

Little is known about the conditions that encourage animals to learn to use configural associations to guide their behavior or the consequences of such learning for transfer. This study provided some information about these issues by examining how rats solve the transverse-patterning problem, which requires a configural solution (Spence, 1952). Animals had to concurrently solve 3 simultaneous visual discriminations, represented abstractly as A+ versus B-, B+ versus C-, and C+ versus A-. Experiment 1 indicated that rats use a configural solution even when the problems have an elemental solution, provided that the significance of 1 element (e.g., B) shared by 2 problems is ambiguous (e.g., A+/B-; and B+/C-). Experiments 2 and 3 suggested that, when stimulated to use a configural solution by solving the A+/B- and B+/C- problems, rats transfer the configural solution to problems that have no ambiguous elements.