REVIEW OF THE BOOK SNIFFY THE VIRTUAL RAT PRO VERSION 2.0

Sniffy the Virtual Rat Pro Version 2.0 is the most recent update to the Sniffy the Rat program modules. It has an extensive set of simulations related to Pavlovian and operant conditioning. Many of the standard conditioning paradigms and phenomena are contained within this program. Pavlovian effects such as blocking, overshadowing, and stimulus competition are demonstrated in the data output. Operant manipulations allow shaping the behavior of the virtual rat, observing cumulative records of interval and ratio schedules, as well as conducting operant discrimination procedures. In both Pavlovian and operant paradigms, one can generate histograms that predict the degree to which various stimuli control the virtual rat's behavior. On‐screen presentations may keep most users interested, but working with the generated data files sometimes can prove difficult. Overall, this program has a strong potential for facilitating the instruction in undergraduate conditioning courses, serving as an addendum to traditional undergraduate conditioning laboratories and as a supplement to the use of live animals.     

Melioration and self-experimentation

Operant researchers rarely use the arena of applied psychology to motivate or to judge their research. Absence of tests by application weakens the field of basic operant research. Early in their development, the physical and biological sciences emphasized meliorative aspects of research. Improvement of human life was a major goal of these young sciences. This paper argues that if basic operant researchers analogously invoked a melioration criterion, the operant field might avoid its tendency toward ingrowth and instead generate a broadly influential science. Operant researchers could incorporate melioration by (a) creating animal models to study applied problems; (b) confronting questions raised by applied analysts and testing hypotheses in applied settings; or (c) performing self-experiments—that is, using experimental methods and behavioral techniques to study and change the experimenter's behavior.     

Abstract Planning and Perceptual Chunks: Elements of Expertise in Geometry

We present a new model of skilled performance in geometry proof problem solving called the Diagram Configuration model (DC). While previous models plan proofs in a step-by-step fashion, we observed that experts plan at a more abstract level: They focus on the key steps and skip the less important ones. DC models this abstract planning behavior by parsing geometry problem diagrams into perceptual chunks, called diagram configurations, which cue relevant schematic knowledge. We provide verbal protocol evidence that DC's schemas correspond with the step-skipping inferences experts make in their initial planning. We compare DC with other models of geometry expertise and then, in the final section, we discuss more general implications of our research. DC's reasoning has important similarities with Larkin's (1988) display-based reasoning approach and Johnson-Laird's (1983) mental model approach. DC's perceptually based schemas are a step towards a unified explanation of (1) experts' superior problem-solving effectiveness, (2) experts' superior problem-state memory, and (3) experts' ability, in certain domains, to solve relatively simple problems by pure forward inferencing. We also argue that the particular and efficient knowledge organization of DC challenges current theories of skill acquisition as it presents an end-state of learning that is difficult to explain within such theories. Finally, we discuss the implications of DC for geometry instruction.     

The Proposition of a General Version of the Theory of Planned Behavior: Predicting Ecological Behavior1

The present paper explores whether the theory of planned behavior (TPB) must abandon the notion that perceived behavioral control (PBC) has a direct influence on behavior. In a cross‐sectional survey of 895 Swiss residents, our hypothesis was tested by means of structural equation models. Applied specifically, PBC turned out to be a significant direct predictor of one's performance. A general version of the TPB based on aggregated measures, however, revealed PBC's direct influence on behavior to be nonsignificant and, presumably, a non‐universally applicable and thus nongeneralizable part of the theory. Intention determined 51% to 52% of people's ecological behavior, which supports the claim of a strong attitude‐behavior relation. Attitude, subjective norms, and PBC, the 3 TPB components, account for 81% of intention's variance.     

An Interactive Approach for Multicriteria Decision Making Using a Tchebycheff Utility Function Approximation

Multicriteria decision making (MCDM) can provide an efficient mean for considering various and conflicting objectives to reveal the alternative that maximizes the decision maker's (DM) utility. In this paper, we propose a new interactive MCDM method for implicit alternatives to help a DM obtain a most preferred solution. We employ a Tchebycheff function to generate weights for objectives consistent with the DM's responses to pairwise comparisons between alternatives and present a mixed integer linear programming formulation to generate these weights. Thus, we approximate the DM's utility function by a Tchebycheff function and generate weights consistent with the DM's responses. We test our approach with different true utility functions on various sized multiple criteria linear programming problems. The computational results show that even with non‐Tchebycheff true utility functions, our method can generate alternatives very close to the optimal solution with few questions. The comparison of our results with other methods reveals its advantages. Copyright © 2013 John Wiley & Sons, Ltd.     

The personal life of the behavior analyst

The human species faces crises of critical proportions. Excessive population, global warming, and the anticipated descent from peak fossil-fuel extraction promise to change our future in far-reaching ways. Operant conditioning prepares the individual for a world similar to the selecting past, but our world is changing more rapidly than our adaptation. As individuals, we cannot make substantial changes in the world at large because we do not control enough reinforcers, but we can turn to the sources of our personal behavior and manipulate them. We will need help. Better organized social networks and the self-management techniques they support can promote immediate changes in consumption at home, work, and moving about in our personal worlds. Surprisingly, consuming less can lead to more satisfying and happier lives, but a better understanding of reinforcement contingencies is necessary. We can recover the strengthening effects of personal daily accomplishments that are eroded when conditioned generalized reinforcers intervene. When we get our own personal lives in order we can reduce our carbon footprints, restore the connections between our behavior and its strengthening effects, and become models worthy of imitation.     

Gricean Expectations in Online Sentence Comprehension: An ERP Study on the Processing of Scalar Inferences

There is substantial support for the general idea that a formalization of comprehenders' expectations about the likely next word in a sentence helps explaining data related to online sentence processing. While much research has focused on syntactic, semantic, and discourse expectations, the present event‐related potentials (ERPs) study investigates neurolinguistic correlates of pragmatic expectations, which arise when comprehenders expect a sentence to conform to Gricean Maxims of Conversation. For predicting brain responses associated with pragmatic processing, we introduce a formal model of such Gricean pragmatic expectations, using an idealized incremental interpreter. We examine whether pragmatic expectancies derived from this model modulate the amplitude of the N400, a component that has been associated with predictive processing. As part of its parameterization, the model distinguishes genuine pragmatic interpreters, who expect maximally informative true utterances, from literal interpreters, who only expect truthfulness. We explore the model's non‐trivial predictions for an experimental setup which uses picture‐sentence verification with ERPs recorded at several critical positions in sentences containing the scalar implicature trigger some. We find that Gricean expectations indeed affect the N400, largely in line with the predictions of our model, but also discuss discrepancies between model predictions and observations critically.     

Towards end-to-end likelihood-free inference with convolutional neural networks

Complex simulator-based models with non-standard sampling distributions require sophisticated design choices for reliable approximate parameter inference. We introduce a fast, end-to-end approach for approximate Bayesian computation (ABC) based on fully convolutional neural networks. The method enables users of ABC to derive simultaneously the posterior mean and variance of multidimensional posterior distributions directly from raw simulated data. Once trained on simulated data, the convolutional neural network is able to map real data samples of variable size to the first two posterior moments of the relevant parameter's distributions. Thus, in contrast to other machine learning approaches to ABC, our approach allows us to generate reusable models that can be applied by different researchers employing the same model. We verify the utility of our method on two common statistical models (i.e., a multivariate normal distribution and a multiple regression scenario), for which the posterior parameter distributions can be derived analytically. We then apply our method to recover the parameters of the leaky competing accumulator (LCA) model and we reference our results to the current state-of-the-art technique, which is the probability density estimation (PDA). Results show that our method exhibits a lower approximation error compared with other machine learning approaches to ABC. It also performs similarly to PDA in recovering the parameters of the LCA model.     

Coping With Unemployment: The Impact of Unemployment Duration and Personality on Trajectories of Life Satisfaction

Unemployment is a major life event that causes an enormous drop in people's life satisfaction. However, there is substantial variability in people's ability (or inability) to cope with the experience of unemployment. In the present study, we examined the causes of individual differences in trajectories of life satisfaction when people were faced with unemployment by taking into account the persistence of unemployment, pre‐event personality and age. Analyses were based on data from the German Socio‐Economic Panel. Using latent growth curve modelling, life satisfaction was investigated from 3 years before to 3 years after a person became unemployed in a total sample of 908 individuals. As expected, unemployment caused a substantial drop in life satisfaction that persisted for at least 3 years after the event. On average, individuals did not completely return to their previous satisfaction level. This pattern existed even for participants who re‐entered the labour market. Moreover, our results showed that variability in coping with unemployment can be explained in part by personality traits. For people with short periods of unemployment, Conscientiousness reinforced the negative effect of unemployment, whereas Extraversion softened the effect. In sum, our analyses showed that (a) the negative effect of unemployment on life satisfaction differs according to the length of the unemployment period and (b) personality partially moderates responses to unemployment over time. Copyright © 2015 European Association of Personality Psychology     

Symbolically speaking: a connectionist model of sentence production

The ability to combine words into novel sentences has been used to argue that humans have symbolic language production abilities. Critiques of connectionist models of language often center on the inability of these models to generalize symbolically (Fodor & Pylyshyn, 1988; Marcus, 1998). To address these issues, a connectionist model of sentence production was developed. The model had variables (role‐concept bindings) that were inspired by spatial representations (Landau & Jackendoff, 1993). In order to take advantage of these variables, a novel dual‐pathway architecture with event semantics is proposed and shown to be better at symbolic generalization than several variants. This architecture has one pathway for mapping message content to words and a separate pathway that enforces sequencing constraints. Analysis of the model's hidden units demonstrated that the model learned different types of information in each pathway, and that the model's compositional behavior arose from the combination of these two pathways. The model's ability to balance symbolic and statistical behavior in syntax acquisition and to model aphasic double dissociations provided independent support for the dual‐pathway architecture.     

Judging the accuracy of a likelihood judgment: the case of smoking risk

A standard method for assessing whether people have appropriate internal representations of an event's likelihood is to check whether their subjective probability or frequency estimates for the event correspond with the assumed objective value for that event. When a person's estimate for the event exceeds its assumed objective probability or frequency, the person's expectancy for the event is concluded to be greater than warranted. This paper describes three lines of reasoning as to why conclusions of this sort can be problematic. Recently published findings as well as data from two new experiments are described to support this main thesis. The case of smoking risk is used to illustrate the more general problem, and issues that must be considered to avoid or contend with the problem are discussed. Copyright © 2002 John Wiley & Sons, Ltd.     

The relationship between marital interaction behaviors and affective reactions to one's own and one's spouse's self-evaluation needs

A recent extension (Beach, & Tesser, 1993) of Tesser's self-evaluation maintenance model (SEM: Tesser, 1988) proposed that a person's motivation to feel good about the self, and his or her concern for the partner's need to feel good about the self, can affect the couple's interaction behavior. In the present study, individual differences in the motivation to maintain one's own and one's partner's SEM needs are used to predict the couple's problem-solving discussion behaviors. Fifty-three married couples were videotaped for 20 minutes while discussing an important relationship issue on which there was disagreement. From these video records, husbands' and wives' favorable and unfavorable discussion behaviors were coded. During a subsequent session, couples reported their affective reactions to a number of SEM scenarios recalled from memory, which were used to create an individual difference measure representing the strength in motivation to maintain one's own and one's partner's self-evaluation needs. In general, husbands' and wives' responsiveness to their partners' SEM needs was associated with favorable interaction behavior, whereas responsiveness to one's own SEM needs was associated with unfavorable interaction behavior. The results of this study suggest that the extended SEM model provides an experimental framework that incorporates research directed at both the elucidation of individual differences and the examination of the couple as a unit.     

Process variables in the treatment of sexual offenders: A review of the relevant literature

The present review considers the relevance of process issues for the treatment of sexual offenders. The general literature on psychotherapy indicates that the therapist's style, the client's perceptions of the therapist, and the alliance between client and therapist, all influence treatment effectiveness. From our review of this literature, and the far less voluminous research on these issues by cognitive behavior therapists, we draw implications for enhancing the effectiveness of treatment of sexual offenders. We also make suggestions for research on process variables in the treatment of these offenders.     

Pivotal behavior as the mediator of the relationship between parental responsiveness and children's symbolic behavior

Previous research with parents and children with developmental disabilities indicated that the relationship between mothers’ responsive style of interaction and children's rate of development was mediated by the simultaneous relationship between mothers’ responsiveness and children's social engagement, or pivotal behavior. In this study, we attempted to determine whether children's pivotal behavior might also mediate the relationship between responsiveness and child development in a sample of 165 typically developing toddlers and their Taiwanese parents. Child development was assessed with a parent report measure of children's symbolic behavior. Parental responsiveness and children's pivotal behavior were assessed from observations of parent–child play. Results indicated that parental responsiveness was correlated with children's pivotal behavior, and that both of these variables were correlated with children's symbolic behavior. Structural equation models indicated that the relationship between responsiveness and children's symbolic behavior was fully mediated by children's pivotal behavior.     

The meta‐analysis of partial effect sizes

This paper discusses the synthesis of partial effect sizes derived from multivariate settings. The general statistical properties of the d‐effect size are derived, extending Hedges's statement of zero‐order properties. These general properties have direct relevance in the synthesis of a set of independent effect sizes arising from empirical studies predicated on a common theoretical model. We discuss possible solutions to the problem of comparing effect sizes arising from models employing differing sets of covariates. We apply the general statistical properties in the synthesis of gender performance differences in first‐level economics courses at three New Zealand universities. The model of academic performance is based on Spearman's conception of general academic ability and specific ability in economics.     

The effect of consequential thinking on trust game behavior

Contrary to rational Expected Monetary Value (EMV) predictions that no money will be transferred in Trust Games, in experiments players make positive transfers. Theorists have proposed modifying the Sender's utility function while retaining utility‐maximization assumptions to account for this behavior. Such accounts assume that Senders can grasp the possible outcomes of their choices, their probabilities, and utilities. In reality, however, Senders' choices are unexpectedly complex, and the assumption that they approximate expected utility maximization is highly implausible. Instead, we suggest that Senders are guided by general propensities to trust others. Two experiments examine the effect of inducing consequential thought on Sender behavior. One induced consequential thought directly; the other did so indirectly. The amount sent was significantly reduced following either manipulation. This suggests that models of Sender behavior in Complex Trust Games should not assume that participants routinely engage in consequential thinking (CT) of the depth that would be required for utility maximization. Copyright © 2008 John Wiley & Sons, Ltd.     

How do Motor Systems Deal with the Problems of Controlling Three-Dimensional Rotations?

Rotations are fundamental to motor control, not only for orienting to stimuli but also in the joint articulations that underlie translational movements. Studying three-dimensional (3-D) rotations of the simplest joint system, the eye, has provided general insights into the neural control of movement. First, in selecting one 3-D eye orientation for each two-dimensional (2-D) gaze direction, the oculomotor system generates a behavior called Listing's law that constrains eye position to a 2-D plane, Listing's plane. This selection is made internally by an inverse kinematic transformation called the Listing's law operator. Second, the oculomotor system incorporates the inherent multiplicative relationship between rotational velocity and position to generate the 3-D movement and position commands required by Listing's law. Finally, the coordinate systems for these commands appear to align with Listing's plane rather than with anatomic structures. Recent investigations have revealed similar behavioral constraints in the orientations of the head and arm, suggesting that the neural mechanisms for Listing's law may have analogues in many motor systems.