Postural change effects on infants' AB task performance: visual, postural, or spatial?

Smith and colleagues (Smith, L. B., Thelen, E., Titzer, R., & McLin, D. (1999). Knowing in the context of acting: The task dynamics of the A-not-B error. Psychological Review, 106, 235-260) demonstrated that 10-month-olds succeed on a Piagetian AB search task if they are moved from a sitting position to a standing position between A and B trials. These authors explained this result by suggesting that because the reach must be executed by different muscle forces from the standing position, an appropriate reach to B is programmed without the memory of the previous reach interfering with the current reach. In the main study reported here, the influences of postural and spatial factors are separated by adding a condition in which the table containing the hiding wells is moved up at the same time as the infant is shifted to standing, thereby allowing a postural change without a change in the spatial relations between the hand and hiding locations. Results showed that in both a standard control condition and the sitting-to-standing condition in which the table also moved up, performance was poor. Only in the sitting-to-standing condition in which the spatial relation between the hand and apparatus was altered were infants successful. These outcomes demonstrate that perseveration effects are likely to occur at the level of reach planning rather than at the level of execution, thereby narrowing the gap between explanations of improvements in AB performance with age that emphasize prefrontal maturation as opposed to improvements in reaching ability.     

Inexact Knowledge with Introspection

Standard Kripke models are inadequate to model situations of inexact knowledge with introspection, since positive and negative introspection force the relation of epistemic indiscernibility to be transitive and euclidean. Correlatively, Williamson’s margin for error semantics for inexact knowledge invalidates axioms 4 and 5. We present a new semantics for modal logic which is shown to be complete for K45, without constraining the accessibility relation to be transitive or euclidean. The semantics corresponds to a system of modular knowledge, in which iterated modalities and simple modalities are not on a par. We show how the semantics helps to solve Williamson’s luminosity paradox, and argue that it corresponds to an integrated model of perceptual and introspective knowledge that is psychologically more plausible than the one defended by Williamson. We formulate a generalized version of the semantics, called token semantics, in which modalities are iteration-sensitive up to degree n and insensitive beyond n. The multi-agent version of the semantics yields a resource-sensitive logic with implications for the representation of common knowledge in situations of bounded rationality.     

A model of working memory capacity in the radial-arm maze task

The radial arm maze is one of the most commonly used tests for assessing working memory in laboratory animals. However, to date, there exists no quantitative method of estimating working memory capacity from performance on this task. Here, we present a mathematical model of performance on the radial arm maze from which we can derive estimates of capacity. We derive explicit results for the two most commonly used measures of performance as functions of number of arms in the maze and memory capacity, assuming a uniform random search. We simulate random non-uniform search strategies. Comparing our model to previous experiments, we show that our model predicts a working memory capacity in the range of 3-9 at the level of performance observed in these experiments. This estimate is within the typical estimate of human working memory capacity. Performance of rats on large mazes (e.g. 48 arms) has been used as evidence that the working memory capacity of rats may be significantly larger than that of humans. We report that memory capacity in the range 3-9 is sufficient to explain the performance of rats in very large radial mazes. Furthermore, when we simulate non-uniform random search strategies observed in the experiments, the resulting estimates do not differ significantly from those assuming a uniform random search. We conclude that a list-based model of working memory with modest capacity is more powerful than previously expected.     

Random error in holistic evaluations and additive decompositions of multiattribute utility — an empirical comparison

This paper details the results of an empirical investigation of the random errors associated with decomposition estimates of multiattribute utility. In a riskless setting, two groups of subjects were asked to evaluate multiattribute alternatives both holistically and with the use of an additive decomposition. For one group, the alternatives were described in terms of three attributes, and for the other in terms of five. Estimates of random error associated with the various elicitations (holistic, single-attribute utility, scaling constants, or weights) were obtained using a test-retest format. It was found for both groups that the additive decomposition had significantly smaller levels of random error than the holistic evaluation. However, the number of attributes did not seem to make a significant difference to the amount of random error associated with the decomposition estimates. The levels of error found in the various elicitations were consistent with theoretical bounds that have recently been proposed in the literature. These results show that the structure imposed on the problem through decomposition results in measurable improvement in quality of the multiattribute utility judgements, and contribute to a greater understanding of the decomposition method in decision analysis.     

Choice As A Function Of Reinforcement Ratios In Delayed Matching-to-sample

Pigeons were studied in two experiments using a delayed matching-to-sample task. In Experiment 1, 4 subjects were exposed to a task in which the proportion of reinforcement associated with matching and nonmatching, and the overall proportion of reinforcement associated with selecting each choice, regardless of the sample stimulus, were varied. Choice was sensitive to both proportions. A least squares regression analysis showed that Wixted's (1989) proportions of reinforcement model closely fit the data from Experiment 1; however, the model failed to make accurate qualitative predictions for some test conditions. In Experiment 2, 4 subjects were exposed to a delayed matching-to-sample task in which the retention intervals and the reduction in delay to reinforcement signaled by the onset of the sample stimulus were independently varied. When the retention interval was short and when the delay-reduction value of the sample stimulus was high, the sample exerted greater control over choice; the control by the overall proportion of reinforcements for selecting each choice stimulus was correspondingly low. Conversely, when the retention interval was long and the delay-reduction value of the sample stimulus was low, the sample exerted relatively less control over choice; control by the overall proportion of reinforcements obtained for selecting each choice stimulus was correspondingly high. A signal detection analysis found that sensitivity to reinforcement varied directly with retention interval. Data were also consistent with misallocation models. No evidence was found to suggest that pigeons ignore the rate at which selecting individual choice stimuli is reinforced, as has been reported in studies with human subjects.     

Retrospective questions and correlations

In survey research it is not uncommon to ask questions of the following type: “How many times did you undertake actiona in reference periodT of length τ?.” The relationship is established between τ and the correlation of the number of reported actions with some background variable. To this end it is assumed that the process of actions satisfies a renewal model with individual heterogeneity. Also a model has to be formulated for possible recall effects. Applications are given in the field of medical consumption.     

On the use of bisection procedures in animal psychophysical scaling

The ability of bisection procedures to specify the form of the psychophysical scale depends upon the precision of the technique. It is demonstrated that the precision of bisection techniques is a function of the stimulus interval bisected. Consequently, the choice of stimuli in a bisection experiment may predispose the ability of the experiment to distinguish between alternative psychophysical scales. The testing of interval scale properties of derived scales and the assessment of context effects in bisection experiments was also discussed.This material has been reviewed by the Walter Reed Army Institute of Research, and there is no objection to its presentation and/or publication. The opinions or assertions contained herein are the private views of the author and are not to be construed as official or as reflecting the view of the Department of the Army or the Department of Defense.     

Statistical inference for false positive and false negative error rates in mastery testing

This paper describes an asymptotic inferential procedure for the estimates of the false positive and false negative error rates. Formulas and tables are described for the computations of the standard errors. A simulation study indicates that the asymptotic standard errors may be used even with samples of 25 cases as long as the Kuder-Richardson Formula 21 reliability is reasonably large. Otherwise, a large sample would be required.This work was performed pursuant to Grant No NIE-G-78-0087 with the National Institute of Education, Department of Health, Education and Welfare, Huynh Huynh, Principal Investigator. Points of view or opinions stated do not necessarily reflect NIE position or policy and no official endorsement should be inferred. The editorial assistance of Joseph C. Saunders is gratefully acknowledged.     

Using automation to combat the replication crisis: A case study from controlled-rearing studies of newborn chicks

The accuracy of science depends on the precision of its methods. When fields produce precise measurements, the scientific method can generate remarkable gains in knowledge. When fields produce noisy measurements, however, the scientific method is not guaranteed to work – in fact, noisy measurements are now regarded as a leading cause of the replication crisis in psychology. Scientists should therefore strive to improve the precision of their methods, especially in fields with noisy measurements. Here, we show that automation can reduce measurement error by ∼60% in one domain of developmental psychology: controlled-rearing studies of newborn chicks. Automated studies produce measurements that are 3–4 times more precise than non-automated studies and produce effect sizes that are 3–4 times larger than non-automated studies. Automation also eliminates experimenter bias and allows replications to be performed quickly and easily. We suggest that automation can be a powerful tool for improving measurement precision, producing high powered experiments, and combating the replication crisis.     

The use of mixed modeling to evaluate the impact of treatment integrity on learning

Treatment integrity, or the degree to which an intervention is implemented as intended, is a critical feature of skill acquisition tasks. Single‐case design consistently demonstrates that low treatment integrity slows or inhibits learning, but the relative impact of different types of instructional errors, or the presence of multiple errors, is less clear. The present study utilized a multilevel modeling approach to evaluate the impact of type of error (omission versus omission and commission) and error component (reinforcer delivery versus feedback) on learning. Findings revealed that learning outcomes worsened based on the type of error and as the complexity of errors increased; more specifically, participants performed better when only a single type of error occurred and when only a single error component was manipulated. Additionally, individual characteristics contributed to learning outcomes, highlighting the use of multilevel modeling as a helpful tool to supplement single‐case design. The differential impact of integrity errors on learning may be due to timing of errors (i.e., commission errors more likely to occur early in learning) or how errors affect reinforcement schedule versus discriminative control.