Discrimination learning decreases perceived similarity according to an objective measure

Initial identification discriminations between two sizes and between two slants produced better overall performances on subsequent size and slant same-different discriminations, respectively. This size- and slant-specific transfer was due to an improvement on only the different pairs. Time-duration identification discriminations with the identical stimuli and response assignments improved neither overall same-different performances nor performances on different pairs. A good performance on different pairs relative to same pairs should indicate a low perceived similarity. The literature indicates that A-X and B-Y pairings produce a positive transfer on an A-versus-B discrimination when X and Y are relatively low in similarity, and also indicates that a low perceived (not physical) similarity improves discrimination learning. An increase in salience should have also improved performance on the same pairs. The conclusion: the initial discriminations decreased the perceived similarity of parts (size or slant). This decrease resembles perceptual contrast. A discrimination between two parts also seems to increase the extent to which each part is apprehended as a separate group. Therefore, the conclusion accords with the position that two groups are associated with contrast, including for visibility.     

Connectionism and the learning of probabilistic concepts

Three experiments examine the claim of Gluck and Bower (1986, 1988a, 1988b) that the learning of medical concepts can be simulated by a connectionist network in which the symptoms are the input and the diagnosis is the output. The first experiment replicates the main finding of Gluck and Bower. In this experiment, subjects were required to estimate the probability of each of two diseases, given a particular target symptom. In fact these two probabilities were identical, but because one illness was more common than the other, the target symptom was a better predictor of the rare disease than of the common disease. Contrary to a normative probability judgement account, subjects were biased in that they judged the probability of the rare disease given the target symptom to be greater than the probability of the common disease given the target symptom. Gluck and Bower argued that such a result was predicted by a connectionist network using the Rescorla-Wagner learning rule, but it is argued that Gluck and Bower's network simulation was not appropriate for the experiment they had performed. In fact, it appeared that the connectionist network failed to predict the bias in the subjects' probability estimates.

However, this conclusion rests on an assumption that Gluck and Bower implicitly made. They arranged for P(rare disease/target symptom) and P(com-mon disease/target symptom) to be identical across all trials on which the target symptom occurred, both on its own and with other symptoms present. Gluck and Bower assumed that the subjects were estimating these probabilities. But the results of the second experiment showed instead that the subjects were estimating the probability of each disease given only the target symptom. In the final experiment the design was changed so that this problem might be circumvented. In this experiment, again, the subjects were biased in their probability judgements exactly as the connectionist network predicted. Thus, finally, evidence was found which was compatible with the network model but not with a normative account, but this was true only if the network did not include a layer of hidden units.     

On the status of unconscious memory: Merikle and Reingold (1991) revisited

Four experiments are reported that reevaluate P. M. Merikle and E. M. Reingold's (1991) demonstration of unconscious memory: the greater sensitivity to familiarity (repetition) of an indirect (implicit) memory task than of a comparable direct (explicit) task. At study, participants named the cued member of a pair of visually presented words. At test, new and uncued study words were presented against a background mask. Participants judged whether each word was old or new (direct task) or whether the contrast between the word and the background was high or low (indirect task). Contrary to the original findings, the sensitivity of the indirect task to familiarity never exceeded that of the direct task. These findings pose a challenge to a key pillar of evidence for unconscious influences of memory.     

Frames and MV-algebras

We describe a class of MV-algebras which is a natural generalization of the class of “algebras of continuous functions”. More specifically, we're interested in the algebra of frame maps Hom (Ω(A), K) in the category T of frames, where A is a topological MV-algebra, Ω(A) the lattice of open sets of A, and K an arbitrary frame. Given a topological space X and a topological MV-algebra A, we have the algebra C (X, A) of continuous functions from X to A. We can look at this from a frame point of view. Among others we have the result: if K is spatial, then C(pt(K), A), pt(K) the points of K, embeds into Hom (Ω(A), K) analogous to the case of C (X, A) embedding into Hom (Ω(A), Ω (X)). 1991 Mathematics Subject Classification: 06F20, 06F25, 06D30 Presented by Ewa Orlowska     

Attentional load and implicit sequence learning

A widely employed conceptualization of implicit learning hypothesizes that it makes minimal demands on attentional resources. This conjecture was investigated by comparing learning under single-task and dual-task conditions in the sequential reaction time (SRT) task. Participants learned probabilistic sequences, with dual-task participants additionally having to perform a counting task using stimuli that were targets in the SRT display. Both groups were then tested for sequence knowledge under single-task (Experiments 1 and 2) or dual-task (Experiment 3) conditions. Participants also completed a free generation task (Experiments 2 and 3) under inclusion or exclusion conditions to determine if sequence knowledge was conscious or unconscious in terms of its access to intentional control. The experiments revealed that the secondary task impaired sequence learning and that sequence knowledge was consciously accessible. These findings disconfirm both the notion that implicit learning is able to proceed normally under conditions of divided attention, and that the acquired knowledge is inaccessible to consciousness. A unitary framework for conceptualizing implicit and explicit learning is proposed.     

Individual differences in causal learning and decision making

In judgment and decision making tasks, people tend to neglect the overall frequency of base-rates when they estimate the probability of an event; this is known as the base-rate fallacy. In causal learning, despite people's accuracy at judging causal strength according to one or other normative model (i.e., Power PC, DeltaP), they tend to misperceive base-rate information (e.g., the cause density effect). The present study investigates the relationship between causal learning and decision making by asking whether people weight base-rate information in the same way when estimating causal strength and when making judgments or inferences about the likelihood of an event. The results suggest that people differ according to the weight they place on base-rate information, but the way individuals do this is consistent across causal and decision making tasks. We interpret the results as reflecting a tendency to differentially weight base-rate information which generalizes to a variety of tasks. Additionally, this study provides evidence that causal learning and decision making share some component processes.     

On the role of recognition in decision making

In 2 experiments, the authors sought to distinguish between the claim that recognition of an object is treated simply as a cue among others for the purposes of decision making in a cue-learning task from the claim that recognition is attributed a special status with fundamental, noncompensatory properties. Results of both experiments supported the former interpretation. When recognition had a high predictive validity, it was relied on (solely) by the majority of participants; however, when other cues in the environment had higher validity, recognition was ignored, and these other cues were used. The results provide insight into when, where, and why recognition is used in decision making and also question the elevated status assigned to recognition in some frameworks (e.g., D. G. Goldstein & G. Gigerenzer, 2002).     

Recollection, fluency, and the explicit/implicit distinction in artificial grammar learning

In this article, the authors propose that both implicit memory and implicit learning phenomena can be explained by a common set of principles, in particular via participants' strategic use of recollective and fluency heuristics. In a series of experiments, it was demonstrated that manipulating processing fluency had an impact on classification decisions in an artificial grammar learning task (Experiments 1, 2, 4, and 7), showing that participants were using a fluency heuristic. Under identical conditions, however, this manipulation had no effect on recognition decisions (Experiments 3 and 5), consistent with a greater default reliance on recollection. Most significant, the authors also showed that a fluency effect can be induced in recognition (Experiments 4-6) and can be eliminated in classification (Experiment 7).