Affect regulation and synchrony in mother—infant play as precursors to the development of symbolic competence

This study examines relationships between organizing processes of affective communication in infancy and the development of symbolic competence. Thirty six mother—infant dyads were observed at 3 and 9 months, and 32 dyads were reassessed at 24 months. Mother's and infant affective states during face-to-face play at 3 and 9 months were coded in .25-second frames. The underlying structure of infant affect and the time-lag synchrony between mother and infant affective states were assessed with time-series analyses. In addition, interactions at 3 and 9 months were assessed for the global level of infant positive affect and maternal affect attunement. At 2 years, three dimensions of symbolic competence were evaluated: symbolic play, verbal IQ, and the child's use of internal states words. Infant affect regulation at 3 months, defined by the existence of a non-random, stochastic-cyclic organization of affective states, predicted all three domains of symbolic competence at 2 years. Maternal synchrony and attunement each had an independent contribution to the prediction of symbolic play and internal state talk. The microanalytic and global indices of affect each added meaningfully to the prediction of symbolic functioning. The organization of behavioral sequences into coherent affective configurations is discussed as a possible precursor to the general capacity to develop symbols. © 1997 Michigan Association for Infant Mental Health     

Making sense of agency: Belief in free will as a unique and important construct

Belief in free will is the general belief that human behavior is free from internal and external constraints across situations for both self and others. In the last decade, scholars in social‐cognitive psychology and experimental philosophy have made progress in defining free will terms, exploring how laypersons think of free will, discovering related cognitive processes and biases, and examining the behavioral outcomes of believing in free will. The growing interest in this construct raises the need for a discussion of what is new about free will beliefs, and how this construct differs from and relates to other well‐known agency constructs in the literature. In this review, we integrate conceptual discussions and empirical findings in the existing literature to highlight the belief in free will as a separate and important construct, different from existing constructs in the literature, and capturing unique aspects of agency. We conclude by calling researchers to recognize these differences and to leverage the potential in the construct of the belief in free will as a predictor of cognition and behavior.     

Effects of Group Functional Behavior-Based Cognitive-Behavioral Therapy for Obsessive-Compulsive Behavior in a Youth With Autism Spectrum Disorder

Individuals with Autism Spectrum Disorder (ASD) often present with comorbid Obsessive Compulsive Behaviors (OCBs), but little research exists on effective intervention for OCBs. Using a single-case experimental design, this study highlights the efficacy of a Group Functional Behavior-based Cognitive-Behavior Therapy (Fb-CBT) to reduce OCBs in an 11-year-old youth with ASD. Tailored to the individual needs of this youth, Fb-CBT included traditional CBT components (e.g., psychoeducation, cognitive-behavioral skills training, and exposure and response prevention) coupled with functional behavior assessment and intervention. Time-series parent report data and standardized measures showed clinically significant decreases in OCBs, an increase in psychosocial functioning, and high consumer satisfaction.     

When Accurate Beliefs Lead to Better Lie Detection1

This study tested the hypothesis that people with accurate beliefs about the cues that predict deception are better at detecting deception only when those beliefs are cognitively available and activated. To test the hypothesis, participants viewed video fragments of people who were being either honest or dishonest. A questionnaire assessed participants' beliefs about the cues involved in deception, and activation of participants' belief cues was accomplished by manipulating suspicion. The results provided support for the hypothesis, where participants whose beliefs were activated and had accurate beliefs were better at detecting deception compared to other participants. Gender differences were also found, where lies communicated by women were more accurately detected than were lies communicated by men.     

Locus of control and organizational embeddedness

Using conservation of resources theory as a guide, this study examines why individuals with an internal locus of control (LOC) are more likely to feel embedded in their organizations. Two mediating processes are posited. First, people with high internal LOC are more likely to acquire greater work resources because they are more effective in negotiating and receiving employment deals which are not widely available or replicable elsewhere. Second, people with high internal LOC are more likely to acquire additional work resources because they network more proactively with colleagues and supervisors. Consequently, high LOC individuals are likely to become more embedded because they have more links with their colleagues and the sacrifices associated with leaving their jobs would be greater. The proposed model was tested and supported with three waves of data collected from a sample of 375 managerial respondents over an 8‐month period. Implications for future research, especially the role of personality traits in understanding organizational embeddedness, are also discussed.     

Americans respond politically to 9/11: understanding the impact of the terrorist attacks and their aftermath

The 9/11 terrorist attacks have had profound effect on U.S. domestic and foreign security policy, leading to several expensive wars and the erosion of civil liberties (under the USA PATRIOT Act). We review evidence on political reactions to the 9/11 attacks and conclude that subjective reactions to terrorism played an important role in shaping support for national security policy in the wake of 9/11. Support for a strong national security policy was most pronounced among Americans who perceived the nation as at threat from terrorism and felt angry at terrorists. In contrast, Americans who were personally affected by the attacks were more likely to feel anxious about terrorism, and this anxiety translated into less support for overseas military action. In addition, Americans who felt insecure after the 9/11 attacks and perceived a high future threat of terrorism were more likely than others to support strong foreign and domestic national security policies. Overall, research on American political reactions to 9/11 suggests that support for a strong government response to terrorism is most likely when members of a population perceive a high risk of future terrorism and feel angry at terrorists.     

Exemplar models as a mechanism for performing Bayesian inference

Probabilistic models have recently received much attention as accounts of human cognition. However, most research in which probabilistic models have been used has been focused on formulating the abstract problems behind cognitive tasks and their optimal solutions, rather than on mechanisms that could implement these solutions. Exemplar models are a successful class of psychological process models in which an inventory of stored examples is used to solve problems such as identification, categorization, and function learning. We show that exemplar models can be used to perform a sophisticated form of Monte Carlo approximation known as importance sampling and thus provide a way to perform approximate Bayesian inference. Simulations of Bayesian inference in speech perception, generalization along a single dimension, making predictions about everyday events, concept learning, and reconstruction from memory show that exemplar models can often account for human performance with only a few exemplars, for both simple and relatively complex prior distributions. These results suggest that exemplar models provide a possible mechanism for implementing at least some forms of Bayesian inference.     

The price of deceptive behavior: Disliking and lying to people who lie to us

We hypothesized that frequency and quality of deception influences how people perceive those who lie to them and that people subsequently increase deceptive behavior as a consequence of being lied to. In Study 1, participants were covertly videotaped conversing with a partner. Following the conversation, participants evaluated partners, and partners reviewed the videotape, identifying deceptions that they told. Findings indicated that partner’s frequency of deception was inversely related to likeability. In Study 2, participants watched a videotape of a confederate who appeared to produce one or four exaggerated or minimized lies, and then evaluated the confederate. Participants and confederates subsequently engaged in a conversation. When participants witnessed either one exaggerated lie, one or four minimal lies, or no lies they trusted and liked the confederate more than when witnessing four exaggerated lies. Moreover, participants increased their own use of deception as a function of the severity and quantity of confederate’s lies.     

An algebra of human concept learning

An important element of learning from examples is the extraction of patterns and regularities from data. This paper investigates the structure of patterns in data defined over discrete features, i.e. features with two or more qualitatively distinct values. Any such pattern can be algebraically decomposed into a spectrum of component patterns, each of which is a simpler or more atomic “regularity.” Each component regularity involves a certain number of features, referred to as its degree. Regularities of lower degree represent simpler or more coarse patterns in the original pattern, while regularities of higher degree represent finer or more idiosyncratic patterns. The full spectral breakdown of a pattern into component regularities of minimal degree, referred to as its power series, expresses the original pattern in terms of the regular rules or patterns it obeys, amounting to a kind of “theory” of the pattern. The number of regularities at various degrees necessary to represent the pattern is tabulated in its power spectrum, which expresses how much of a pattern's structure can be explained by regularities of various levels of complexity. A weighted mean of the pattern's spectral power gives a useful numeric summary of its overall complexity, called its algebraic complexity. The basic theory of algebraic decomposition is extended in several ways, including algebraic accounts of the typicality of individual objects within concepts, and estimation of the power series from noisy data. Finally some relations between these algebraic quantities and empirical data are discussed.