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With the goal of drawing inferences about underlying processes from fits of theoretical models to cognitive data, we examined the tradeoff of risks of depending on model fits to individual performance versus risks of depending on fits to averaged data with respect to estimation of values of a model's parameters. Comparisons based on several models applied to experiments on recognition and categorization and to artificial, computer-generated data showed that results of using the two types of model fitting are strongly determined by two factors: model complexity and number of subjects. Reasonably accurate information about true parameter values was found only for model fits to individual performance and then only for some of the parameters of a complex model. Suggested guidelines are given for circumventing a variety of obstacles to successful recovery of useful estimates of a model's parameters from applications to cognitive data.

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Starting from the premise that the purpose of cognitive modeling is to gain information about the cognitive processes of individuals, we develop a general theoretical framework for assessment of models on the basis of tests of the models' ability to yield information about the true performance patterns of individual subjects and the processes underlying them. To address the central problem that observed performance is a composite of true performance and error, we present formal derivations concerning inference from noisy data to true performance. Analyses of model fits to simulated data illustrate the usefulness of our approach for coping with difficult issues of model identifiability and testability.

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The authors investigated the recognizability of recently studied word and nonword stimuli in relation to both experimentally controlled prior frequency of occurrence and, for words, normative frequency (assessed by counts of occurrences in printed English). The interaction between these variables was small and nonsignificant across all conditions of 2 experiments. Patterns of recognition measures in relation to controlled prior frequency, but not normative frequency, appeared interpretable in terms of response biases generated by long-term priming. Application of a global memory model and analyses of correlations among item categories yielded evidence for a lexicality dimension underlying normative-frequency effects and an implication that "word-frequency effects" on recognition are better termed lexicality effects.

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It is proposed that the products of investigations of learning, memory, and decision over the last half century that are most likely to endure have resulted from interactions between models and experimental research. In this article, some of the traps that must be coped with to make fruitful interactions possible are examined and illustrated with case studies from research on probability learning, category learning, and recognition memory. Topics addressed include functions of models in research; the logic of model testing; fitting models to signal plus noise; values and hazards of averaging data; and potential contributions of neural science to the development of cognitive models.

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Because nearly all human behavior depends to some degree on functioning of the memory system, progress in understanding the diverse psychopathological effects of trauma must be expected to reflect the state of research and theory on human memory. An informal survey of literature on research in psychopathology reveals increasing attention to processes of memory and cognition but an absence of citations of the models of memory that subsume research results and mediate their applications. In this article, a series of steps is taken with the aim of redressing this situation. The first is an overview of contemporary models of memory. From these a set of widely supported assumptions about basic processes and structures is abstracted to form a composite model, which is illustrated in application to several major research paradigms. Finally, consideration is given to implications of the composite model for effects of psychopathological trauma and for some aspects of the maturation and decline of memory functions throughout the life span.

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Subsequent recognition of stimuli perceived in a given situation was studied in relation to stimulus familiarity as determined by frequency in observers' prior experience. To distinguish direct and indirect frequency effects, on the basis of selective memory retrieval and selective attention during learning, respectively, rigorous controls were imposed on stimulus rehearsability and learning conditions. As predicted by a global memory model, both hits and false alarms on recognition tests increased as a function of prior frequency in a concordant pattern that indicates a direct effect, in contrast with the usual indirect effect of varying normative word frequency. Understanding the role of experiential stimulus frequency in recognition may further the interpretation of research in such paradigms as eyewitness testimony.

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The author proposes that many forms of memory distortion, including the progressive changes in recollection of a learning experience often observed over successive tests, are due to the same processes that yield veridical recollection in some circumstances and memory loss and recovery in others. In a framework for interpreting all of these aspects of memory, the author assumes that the objects and events of a learning experience are encoded in parallel in traces of their perceptual attributes, which are basic to recognition, and in traces of reactions made to the events during or following learning, which are basic to recall. Random perturbation of remembered attribute values in both types of traces over retention intervals is a pervasive cause of both loss and distortions of memory.

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Continuous old-new recognition was studied in relation to 3 factors that have been relatively neglected in previous research-stimulus attributes, old-new base rates, and informative feedback following responses. Under all conditions, both hits and false alarms increased over trials and all measures of recognition depended strongly on stimulus properties, notably interitem similarity. In contrast to expectations based on earlier results, both hit and false-alarm levels proved independent of old-new base rate when tests were given without feedback; with feedback added, false-alarm rates tended to approach true old-stimulus base rates with some types of stimuli, though not with words. The findings are compatible, in general, with current composite-memory models and were predicted in detail by an array-similarity model deriving from categorization theory.

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The relationship between basic research with nonhumans and applied behavior analysis is illustrated by our work on activity anorexia. When rats are fed one meal a day and allowed to run on an activity wheel, they run excessively, stop eating, and die of starvation. Convergent evidence, from several different research areas, indicates that the behavior of these animals and humans who self-starve is functionally similar. A biobehavioral theory of activity anorexia is presented that details the cultural contingencies, behavioral processes, and physiology of anorexia. Diagnostic criteria and a three-stage treatment program for activity-based anorexia are outlined. The animal model permits basic research on anorexia that for practical and ethical reasons cannot be conducted with humans. Thus, basic research can have applied importance.

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Exemplar-memory and adaptive network models were compared in application to category learning data, with special attention to base rate effects on learning and transfer performance. Subjects classified symptom charts of hypothetical patients into disease categories, with informative feedback on learning trials and with the feedback either given or withheld on test trials that followed each fourth of the learning series. The network model proved notably accurate and uniformly superior to the exemplar model in accounting for the detailed course of learning; both the parallel, interactive aspect of the network model and its particular learning algorithm contribute to this superiority. During learning, subjects' performance reflected both category base rates and feature (symptom) probabilities in a nearly optimal manner, a result predicted by both models, though more accurately by the network model. However, under some test conditions, the data showed substantial base-rate neglect, in agreement with Gluck and Bower (1988b).

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A cognitive-distance model for choice, obtained by specializing a general class of models for categorization, was tested in a situation simulating the task of controlling speed of a vehicle in tasks defined by different relations between speed and probability of delay. Subjects exhibited significant learning whenever delay schedules permitted greater-than-chance performance, but on the average they did not approach optimal performance in the sense of choosing speeds so as to maximize distance attained in allowed time. Evidence was obtained that subjects encoded information about probabilities of delay and distributions of distance attained at different speeds quite accurately in memory and that suboptimal performance was due primarily to imperfect discrimination among representations of choice alternatives on a cognitive scale of expected distance.

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The detailed course of learning is studied for categorization tasks defined by independent or contingent probability distributions over the features of category exemplars. College-age subjects viewed sequences of bar charts that simulated symptom patterns and responded to each chart with a recognition and a categorization judgment. Fuzzy, probabilistically defined categories were learned relatively rapidly when individual features were correlated with category assignment, more slowly when only patterns carried category information. Limits of performance were suboptimal, evidently because of capacity limitations on judgmental processes as well as limitations on memory. Categorization proved systematically related to feature and exemplar probabilities, under different circumstances, and to similarity among exemplars of categories. Unique retrieval cues for exemplar patterns facilitated recognition but entered into categorization only at retention intervals within the range of short-term memory. The findings are interpreted within the framework of a general array model that yields both exemplar-similarity and feature-frequency models as special cases and provides quantitative accounts of the course of learning in each of the categorization tasks studied.

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Three levels of association theory are distinguished: (a) empirical laws relating operationally definable units; (b) theoretical concepts of association, supported by converging lines of evidence; and (c) theories assimilating concepts of association into more elaborate structures. These levels correspond roughly to stages in the evolution of association theory from the mid-19th century to the present. Ebbinghaus's major contribution as a theorist was to accomplish the transition from the first level to the second. The analysis of serial learning in terms of his conception of multiple types of associations may prove to have greater generality than has yet been realized. However, to account for many phenomena of practical and theoretical interest, this model requires augmentation by a control concept that provides a basis for organization beyond serial linkages of units.

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Subjects asked to simulate decision makers in a competitive bidding situation chose repeatedly between two alternatives; reward probability varied according to a sine wave function of time for one alternative but was held constant over time for the other. Learning functions for choice probability exhibited the wavelike pattern predicted by a statistical learning model. However, on later transfer trials, when success probability was independent of subjects' choices, their choice behavior continued to follow a wavelike function rather than approaching the constant .5 level predicted by the learning model. A possible basis in memory for the transfer performance was revealed in subjects' sketches of the remembered pattern of variation in reward probabilities. It is concluded that choice performance is controlled by a mixture of local feedback, in a manner described by the learning model, and more global information encoded in an abstract memory representation, with the balance of the influence shifting toward the latter when local feedback becomes uninformative.

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Lateral interference between letters in the visual field is a joint function of their similarity and physical separation. Data needed to evaluate hypothesis about the processes implicated in these effects were obtained from two experiments in which the task was identification of a target letter always presented in the center of a three-letter display. Variation of target-flanker similarity, the primary variable, was combined factorially with spacing of target and flanker, location of the display in the visual field, delay of patterned postmasks, and exposure duration. The effect of target-flanker similarity on target identification yielded a nonmonotonic function with a minimum at an intermediate degree of similarity. Data from same-different judgments regarding target-flanker similarity indicate that some information about similarity is available even at levels of visibility that do not permit identification of individual letters. All of the findings could be accommodated by a model assuming that only variables determining visibility--exposure duration, mask properties, location in the visual field, separation of letters--influence extraction of featural information pertaining to letter identification. In contrast, visual similarity influences performance by way of sometimes subtle effects on subjects' criteria or response biases and by effects on the encoding and retention of information regarding relative positions of characters in the visual field. The varying effects of similarity reported in the literature on letter identification all appear to be interpretable in these terms.

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With a two-choice detection procedure, identifiability of signal letters was determined in backgrounds of words, nonword letter strings, or homogeneous noise characters. Under high performance conditions of exposure duration and pre- and postmasks, there was a substantial advantage in identifiability of letters presented alone over letters embedded in words; under low performance conditions there were generally no differences between the two types of context, but some interactive effects appeared involving particular letters with serial position and type of background. No differences were obtained between word and nonword contexts. The disparities between these findings and those reported by Reicher (1969) and Wheeler (1970) may be related to the more complete elimination under the present procedures of effects of redundancy on response selection.