The role of cue information in the outcome-density effect: Evidence from neural network simulations and a causal learning experiment (original) (raw)

Contrasting cue-density effects in causal and prediction judgments

Many theories of contingency learning assume (either explicitly or implicitly) that predicting whether an outcome will occur should be easier than making a causal judgment. Previous research suggests that outcome predictions would depart from normative standards less often than causal judgments, which is consistent with the idea that the latter are based on more numerous and complex processes. However, only indirect evidence exists for this view. The experiment presented here specifically addresses this issue by allowing for a fair comparison of causal judgments and outcome predictions, both collected at the same stage with identical rating scales. Cue density, a parameter known to affect judgments, is manipulated in a contingency learning paradigm. The results show that, if anything, the cue-density bias is stronger in outcome predictions than in causal judgments. These results contradict key assumptions of many influential theories of contingency learning

The Outcome Specificity of Learned Predictiveness Effects: Parallels Between Human Causal Learning and Animal Conditioning

Journal of Experimental Psychology: Animal Behavior Processes, 2005

Two experiments examined the outcome specificity of a learned predictiveness effect in human causal learning. Experiment 1 indicated that prior experience of a cue-outcome relation modulates learning about that cue with respect to a different outcome from the same affective class but not with respect to an outcome from a different affective class. Experiment 2 ruled out an interpretation of this effect in terms of context specificity. These results indicate that learned predictiveness effects in human causal learning index an associability that is specific to a particular class of outcomes. Moreover, they mirror demonstrations of the reinforcer specificity of analogous effects in animal conditioning, supporting the suggestion that, under some circumstances, human causal learning and animal conditioning reflect the operation of common associative mechanisms.

Blocking in human causal learning is affected by outcome assumptions manipulated through causal structure

Learning & Behavior, 2014

Additivity-related assumptions have been proven to modulate blocking in human causal learning. Typically, these assumptions are manipulated by means of pretraining phases (including exposure to different outcome magnitudes), or through explicit instructions. In two experiments, we used a different approach that involved neither pretraining nor instructional manipulations. Instead, we manipulated the causal structure in which the cues were embedded, thereby appealing directly to the participants' prior knowledge about causal relations and how causes would add up to yield stronger outcomes. Specifically, in our "different-system" condition, the participants should assume that the outcomes would add up, whereas in our "same-system" condition, a ceiling effect would prevent such an assumption. Consistent with our predictions, Experiment 1 showed that, when two cues from separate causal systems were combined, the participants did expect a stronger outcome on compound trials, and blocking was found, whereas when the cues belonged to the same causal system, the participants did not expect a stronger outcome on compound trials, and blocking was not observed. The results were partially replicated in Experiment 2, in which this pattern was found when the cues were tested for the second time. This evidence supports the claim that prior knowledge about the nature of causal relations can affect human causal learning. In addition, the fact that we did not manipulate causal assumptions through pretraining renders the results hard to account for with associative theories of learning.

Structural awareness mitigates the effect of delay in human causal learning

Memory & Cognition, 2013

Many studies have demonstrated that reinforcement delays exert a detrimental influence on human judgments of causality. In a free-operant procedure, the trial structure is usually only implicit, and delays are typically manipulated via trial duration, with longer trials tending to produce both longer experienced delays and also lower objective contingencies. If, however, a learner can become aware of this trial structure, this may mitigate the effects of delay on causal judgments. Here we tested this "structural-awareness" hypothesis by manipulating whether response-outcome contingencies were clearly identifiable as such, providing structural information in real time using an auditory tone to delineate consecutive trials. A first experiment demonstrated that providing cues to indicate trial structure, but without an explicit indication of their meaning, significantly increased the accuracy of causal judgments in the presence of delays. This effect was not mediated by changes in response frequency or timing, and a second experiment demonstrated that it cannot be attributed to the alternative explanation of enhanced outcome salience. In a third experiment, making trial structure explicit and unambiguous, by telling participants that the tones indicated trial structure, completely abolished the effect of delays. We concluded that, with sufficient information, a continuous stream of causes and effects can be perceived as a series of discrete trials, the contingency nature of the input may be exploited, and the effects of delay may be eliminated. These results have important implications for human contingency learning and in the characterization of temporal influences on causal inference.