Are animal models predictive for humans?

It is one of the central aims of the philosophy of science to elucidate the meanings of scientific terms and also to think critically about their application. The focus of this essay is the scientific term predict and whether there is credible evidence that animal models, especially in toxicology and pathophysiology, can be used to predict human outcomes. Whether animals can be used to predict human response to drugs and other chemicals is apparently a contentious issue. However, when one empirically analyzes animal models using scientific tools they fall far short of being able to predict human responses. This is not surprising considering what we have learned from fields such evolutionary and developmental biology, gene regulation and expression, epigenetics, complexity theory, and comparative genomics.     

Paradoxical effects of base rates and representation in category learning

The inverse base rate effect (IBRE) continues to be a puzzling case of decision making on the basis of conflicting information in human category learning. After being trained via feedback over trials to assign combinations of cues to high- and low-frequency categories, participants tend to respond with the low-frequency category to an otherwise perfectly conflicting pair of test cues, contrary to the category base rates. Our Experiment 1 demonstrated that decision making on the basis of an explicit summary of the cue-outcome and outcome base rate information from the standard learning task does not result in the effect. The remaining experimental conditions evaluated the necessary and sufficient conditions for the effect by systematically exploring experimental deviations between the standard learning task and the pure decision-making task. In partial disagreement with both recent theoretical accounts of the effect, these experiments indicate that asymmetric outcome representation and profound base rate neglect are individually necessary and jointly sufficient conditions. Broader theoretical implications are discussed.     

Associationism and cognition: human contingency learning at 25

A major topic within human learning, the field of contingency judgement, began to emerge about 25 years ago following publication of an article on depressive realism by Alloy and Abramson (1979). Subsequently, associationism has been the dominant theoretical framework for understanding contingency learning but this has been challenged in recent years by an alternative cognitive or inferential approach. This article outlines the key conceptual differences between these approaches and summarizes some of the main methods that have been employed to distinguish between them.     

Neuropsychological dissociations between priming and recognition: a single-system connectionist account

A key claim of current theoretical analyses of the memory impairments associated with amnesia is that certain distinct forms of learning and memory are spared. A compelling example is that amnesic patients and controls are indistinguishable in repetition priming but amnesic patients are impaired at recognizing the study items. The authors show that this pattern of results is predicted by a single-system connectionist model of learning in which amnesia is simulated by a reduced learning rate. They also demonstrate that the model can reproduce the converse pattern in which priming but not recognition is impaired if the input is assumed to be additionally degraded in a priming test. The authors conclude that dissociations between priming and recognition do not require functionally or neurally distinct memory systems.     

Does opposition logic provide evidence for conscious and unconscious processes in artificial grammar learning?

The question of whether studies of human learning provide evidence for distinct conscious and unconscious influences remains as controversial today as ever. Much of this controversy arises from the use of the logic of dissociation. The controversy has prompted the use of an alternative approach that places conscious and unconscious influences on memory retrieval in opposition. Here we ask whether evidence acquired via the logic of opposition requires a dual-process account or whether it can be accommodated within a single similarity-based account. We report simulations using a simple neural network model of two artificial grammar learning experiments reported by that dissociated conscious and unconscious influences on classification. The simulations demonstrate that opposition logic is insufficient to distinguish between single- and multiple-system models.     

Attention modulates the learning of multiple contingencies

We employed a novel version of the serial reaction time task to test the idea that human implicit learning allows the simultaneous learning of multiple independent contingencies and that this learning may proceed in the absence of attention. Using probabilistic sequences, we showed that both a primary sequence (the focus of the experimental task) and a statistically independent secondary sequence could be learned across 4,800 target localization trials, provided the perceptual load of the primary task was low. However, learning of the secondary sequence was abolished under conditions of high perceptual load. These findings suggest that there are attentional limitations on the learning of multiple contingencies.     

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.     

Probability judgment in hierarchical learning: a conflict between predictiveness and coherence

Why are people's judgments incoherent under probability formats? Research in an associative learning paradigm suggests that after structured learning participants give judgments based on predictiveness rather than normative probability. This is because people's learning mechanisms attune to statistical contingencies in the environment, and they use these learned associations as a basis for subsequent probability judgments. We introduced a hierarchical structure into a simulated medical diagnosis task, setting up a conflict between predictiveness and coherence. Thus, a target symptom was more predictive of a subordinate disease than of its superordinate category, even though the latter included the former. Under a probability format participants tended to violate coherence and make ratings in line with predictiveness; under a frequency format they were more normative. These results are difficult to explain within a unitary model of inference, whether associative or frequency-based. In the light of this, and other findings in the judgment and learning literature, a dual-component model is proposed.     

Effects of a secondary task on "implicit" sequence learning: learning or performance?

Traditionally, implicit learning has been defined in terms of a lack of awareness of the process and products of learning. In the face of a number of conceptual and empirical difficulties with this definition, it has recently been suggested instead that the critical feature of implicit learning is that it proceeds without making any demands on attentional resources. As disconfirmatory evidence for this, we describe the results of two experiments which each used a sequential reaction time task. With a tone-counting secondary task, measures of sequence learning were significantly affected by whether training occurred under single- or dual-task conditions, regardless of whether testing took place under single- or dual-task conditions.