A two‐part mixed effects model for cigarette purchase task data

The Cigarette Purchase Task is a behavioral economic assessment tool designed to measure the relative reinforcing efficacy of cigarette smoking across different prices. An exponential demand equation has become a standard model for analyzing purchase task data, but its utility is compromised by its inability to accommodate values of zero consumption. We propose a two‐part mixed effects model that keeps the same exponential demand equation for modeling nonzero consumption values, while providing a logistic regression for the binary outcome of zero versus nonzero consumption. Therefore, the proposed model can accommodate zero consumption values and retain the features of the exponential demand equation at the same time. As a byproduct, the logistic regression component of the proposed model provides a new demand index, the “derived breakpoint”, for the price above which a subject is more likely to be abstinent than to be smoking. We apply the proposed model to data collected at baseline from college students (N = 1,217) enrolled in a randomized clinical trial utilizing financial incentives to motivate tobacco cessation. Monte Carlo simulations showed that the proposed model provides better fits than an existing model. We note that the proposed methodology is applicable to other purchase task data, for example, drugs of abuse.     

The Role of Non-Numerical Stimulus Features in Approximate Number System Training in Preschoolers from Low-Income Homes

Recent findings have suggested that adults’ and children’s approximate number system (ANS) acuity may be malleable through training, but research on ANS acuity has largely been conducted with adults and children who are from middle- to high-income homes. We conducted 2 experiments to test the malleability of ANS acuity in preschool-aged children from low-income homes and to test how non-numerical stimulus features affected performance. In Experiment 1, mixed-effects models indicated that children significantly improved their ratio achieved across training. Children’s change in probability of responding correctly across sessions was qualified by an interaction with surface area features of the arrays such that children improved their probability of answering correctly across sessions on trials in which numerosity conflicted with the total surface area of object sets significantly more than on trials in which total surface area positively correlated with numerosity. In Experiment 2, we found that children who completed ANS acuity training performed better on an ANS acuity task compared with children in a control group, but they only did so on ANS acuity trials in which numerosity conflicted with the total surface area of object sets. These findings suggest that training affects ANS acuity in children from low-income homes by fostering an ability to focus on numerosity in the face of conflicting non-numerical stimulus features.     

An Attractor Model of Lexical Conceptual Processing: Simulating Semantic Priming

An attractor network was trained to compute from word form to semantic representations that were based on subject-generated features. The model was driven largely by higher-order semantic structure. The network simulated two recent experiments that employed items included in its training set (McRae and Boisvert, 1998). In Simulation 1, short stimulus onset asynchrony priming was demonstrated for semantically similar items. Simulation 2 reproduced subtle effects obtained by varying degree of similarity. Two predictions from the model were then tested on human subjects. In Simulation 3 and Experiment 1, the items from Simulation 1 were reversed, and both the network and subjects showed minimally different priming effects in the two directions. In Experiment 2, consistent with attractor networks but contrary to a key aspect of hierarchical spreading activation accounts priming was determined by featural similarity rather than shared superordinate category. It is concluded that semantic-similarity priming is due to featural overlap that is a natural consequence of distributed representations of word meaning.     

25 years of research on the use of geometry in spatial reorientation: a current theoretical perspective

The purpose of this article is to review and evaluate the range of theories proposed to explain findings on the use of geometry in reorientation. We consider five key approaches and models associated with them and, in the course of reviewing each approach, five key issues. First, we take up modularity theory itself, as recently revised by Lee and Spelke (Cognitive Psychology, 61, 152–176, 2010a; Experimental Brain Research, 206, 179–188, 2010b). In this context, we discuss issues concerning the basic distinction between geometry and features. Second, we review the view-matching approach (Stürzl, Cheung, Cheng, & Zeil, Journal of Experimental Psychology: Animal Behavior Processes, 34, 1–14, 2008). In this context, we highlight the possibility of cross-species differences, as well as commonalities. Third, we review an associative theory (Miller & Shettleworth, Journal of Experimental Psychology: Animal Behavior Processes, 33, 191–212, 2007; Journal of Experimental Psychology: Animal Behavior Processes, 34, 419–422, 2008). In this context, we focus on phenomena of cue competition. Fourth, we take up adaptive combination theory (Newcombe & Huttenlocher, 2006). In this context, we focus on discussing development and the effects of experience. Fifth, we examine various neurally based approaches, including frameworks proposed by Doeller and Burgess (Proceedings of the National Academy of Sciences of the United States of America, 105, 5909–5914, 2008; Doeller, King, & Burgess, Proceedings of the National Academy of Sciences of the United States of America, 105, 5915–5920, 2008) and by Sheynikhovich, Chavarriaga, Strösslin, Arleo, and Gerstner (Psychological Review, 116, 540–566, 2009). In this context, we examine the issue of the neural substrates of spatial navigation. We conclude that none of these approaches can account for all of the known phenomena concerning the use of geometry in reorientation and clarify what the challenges are for each approach.     

The effect of directed forgetting on the time to remember

A recognition memory task was used to determine whether the search set is reduced by cueing subject to forget a part of the input. Correct recognition reaction time was used to infer the size of the search set. The principal results were that RT on forget trials was faster than RT on remember trials and that RT was fastest when the forget cue was presented at the outset of the trial rather than after the material had been presented. These findings are generally consistent with the hypothesis that selective search is responsible for the enhancement of recall produced by forget instructions in earlier studies.     

In search of depth

Four experiments designed to investigate a visual search task are reported. In each experiment, subjects searched for either a two-dimensional shape rotated in depth among frontal-parallel distractors or a frontal-parallel shape among distractors that were rotated in depth. The principal independent variable was search-set size. In addition, over the four experiments, a variety of spatial arrangements and two axes of rotation in depth were sampled. The chief aim of the experiments was to adduce evidence bearing on the attentional demands of searching for depth. The slopes of the reaction-time (RT) functions were taken as diagnostic. Experiments 1–3 exhibited positive slopes for the RT-set-size function. These slopes appear to be due to a conscious adoption of a serial search strategy by the subjects. When this tendency was suppressed by the procedures of Experiment 4, the slope of the RT-set-size functions did not differ significantly from zero. We conclude that, in agreement with the findings of other studies, slant-in-depth can be detected preattentively.     

Using logistic regression to estimate delay-discounting functions

The monetary choice questionnaire (MCQ) and similar computer tasks ask preference questions in order to ascertain indifference, the perceived equivalence of immediate versus larger delayed rewards. Indifference data are then fitted with a hyperbolic function, summarizing the decline in perceived value with delay time. We present a fitting method that estimates the hyperbolic parameterk directly from survey responses. Binary preferences are modeled as a function of time (X₂) and a transformed reward ratio (X ₁), yielding logistic regression coefficients β₂ and β₁. The hyperbolic parameter emerges ask = β₂/β₁, where the logistic predictedp = .5 (the definition of indifference). The MCQ was administered to 1,073 adolescents and was scored using both standard and logistic methods. The means for ln(k) were similar (standard, −4.53; logistic, −4.51), and the results were highly correlated (ρ = .973). Simulated MCQ data showed thatk was unbiased, except where β₁ ≥ −1, indicating a vague survey response. Jackknife standard errors provided excellent coverage.