An integrated account of generalization across objects and features

Humans routinely make inductive generalizations about unobserved features of objects. Previous accounts of inductive reasoning often focus on inferences about a single object or feature: accounts of causal reasoning often focus on a single object with one or more unobserved features, and accounts of property induction often focus on a single feature that is unobserved for one or more objects. We explore problems where people must make inferences about multiple objects and features, and propose that people solve these problems by integrating knowledge about features with knowledge about objects. We evaluate three computational methods for integrating multiple systems of knowledge: the output combination approach combines the outputs produced by these systems, the distribution combination approach combines the probability distributions captured by these systems, and the structure combination approach combines a graph structure over features with a graph structure over objects. Three experiments explore problems where participants make inferences that draw on causal relationships between features and taxonomic relationships between animals, and we find that the structure combination approach provides the best account of our data.     

A five-factor measure of obsessive-compulsive personality traits

This study provides convergent, discriminant, and incremental validity data for the Five-Factor Obsessive-Compulsive Inventory (FFOCI), a newly developed measure of traits relevant to obsessive-compulsive personality disorder (OCPD) from the perspective of the Five-factor model (FFM). Twelve scales were constructed as maladaptive variants of specific FFM facets (e.g., Perfectionism as a maladaptive variant of FFM competence). On the basis of data from 407 undergraduates (oversampled for OCPD symptoms) these 12 scales demonstrated convergent correlations with established measures of OCPD and the FFM. Further, they obtained strong discriminant validity with respect to facets from other FFM domains. Most important, the individual scales and total score of the FFOCI obtained incremental validity beyond existing measures of the FFM and OCPD for predicting a composite measure of obsessive-compulsive symptomatology. The findings support the validity of the FFOCI as a measure of obsessive-compulsive personality traits, as well as of maladaptive variants of the FFM.     

Both trace and delay conditioned eyeblink responding can be dissociated from outcome expectancy

Squire and colleagues have proposed that trace and delay eyeblink conditioning are fundamentally different kinds of learning: trace conditioning requires acquisition of a conscious declarative memory for the stimulus contingencies whereas delay conditioning does not. Declarative memory in trace conditioning is thought to generate conditioned responding through the activation of a conscious expectancy for when the unconditioned stimulus (US) is going to occur. Perruchet (1985) has previously shown that in a 50% partial reinforcement design it is possible to dissociate single cue delay eyeblink conditioning from conscious expectancy for the US by examining performance over runs of reinforced and nonreinforced trials. Clark, Manns, and Squire (2001) claim that this dissociation does not occur in trace eyeblink conditioning. In the present experiment we examined the Perruchet effect for short, moderate, and long trace intervals (600, 1000, and 1400 ms) and for the equivalent interstimulus intervals (ISIs) in a delay conditioning procedure. We found evidence for a dissociation of eyeblink CRs and US expectancy over runs regardless of whether there was a delay or a trace arrangement of cues. The reasons for the Perruchet effect are still unclear, but the present data suggest that it does not depend on a separate nondeclarative system of the type proposed by Squire and colleagues.     

Collectivistic Self‐Construal and Forgiveness

This study tested a theoretical model of the relationship between collectivism and forgiveness. Participants (N= 298) completed measures of collectivistic self‐construal, forgiveness, and forgiveness‐related constructs. A collectivistic self‐construal was related to understanding forgiveness as an interpersonal process that involved reconciliation. Individuals with more collectivistic views reported higher trait forgivingness, which predicted the tendency to respond to specific offenses with decisional rather than emotional forgiveness. Individuals with a more collectivistic self‐construal may place more value on interpersonal harmony, reconciliation, and decisions to forgive rather than emotional peace. Implications suggest that counselors understand issues of conflict, hurts, and forgiveness within an assessment of clients’ self‐construal.     

I'll have what she's having: the impact of model characteristics on children's food choices

This research investigates children's use of social categories in their food selection. Across three studies, we presented preschoolers with sets of photographs that contrasted food-eating models with different characteristics, including model gender, race (Black, White), age (child or adult), and/or expression (acceptance or rejection of the food). Children were asked to pick between the photographs to choose which food they would like for snack. Results demonstrated that preschoolers prefer foods being eaten by models with positive over negative expressions, foods being eaten by child over adult models, and foods being eaten by child models of the same gender as themselves over models of the other gender. This work connects with previous research on children's understanding of social categories and also has important practical implications for how characteristics of a food-eating model can affect children's willingness to try new foods.     

Insights for treatment in Tourette syndrome from fMRI

In a recent American Journal of Psychiatry article, Wang and colleagues used functional MRI (fMRI) to examine cortico-striatal-thalamo-cortical circuitry in Tourette syndrome (TS), advancing the field's investigation of circuit level dysfunction in vivo in individuals with TS. Their results provide insight for interrogating neural mechanisms underlying different treatment methods.     

The Evolution of Stalking

We propose that stalking tactics have been shaped by evolutionary processes to help solve mating problems. These include: (1) acquiring new mates, (2) guarding existing mates to prevent defection, (3) fending off mate poachers, (4) poaching someone else’s mate, (5) interfering with intrasexual competitors, (6) reacquiring ex-mates, (7) sexual exploitation and predation, and (8) guarding kin from sexual exploitation. We hypothesize several, gender-differentiated design features of psychological adaptations, including sensitivity to adaptive problems for which stalking was an ancestral solution and cognitive biases that function to motivate and perpetuate stalking behaviors. Although often abhorrent, cost-inflicting, and illegal, stalking sometimes enables successful adaptive solutions to problems of mating and within-gender competition faced by both men and women.     

Forgiveness and Cohesion in Familial Perceptions of Alcohol Misuse

The authors examine the relationships between forgiveness, family cohesion, and alcohol. In Study 1 (N= 190), participants reported lower levels of trust and forgiveness for family members who misuse alcohol. In Study 2 (N= 141), the authors present a model demonstrating family cohesion and trait forgiveness related to state forgiveness of an alcohol‐misusing family member. State forgiveness was related to trust in that family member and, subsequently, higher levels of perceived misuser drinking refusal efficacy.     

Theory learning as stochastic search in the language of thought

We present an algorithmic model for the development of children's intuitive theories within a hierarchical Bayesian framework, where theories are described as sets of logical laws generated by a probabilistic context-free grammar. We contrast our approach with connectionist and other emergentist approaches to modeling cognitive development. While their subsymbolic representations provide a smooth error surface that supports efficient gradient-based learning, our symbolic representations are better suited to capturing children's intuitive theories but give rise to a harder learning problem, which can only be solved by exploratory search. Our algorithm attempts to discover the theory that best explains a set of observed data by performing stochastic search at two levels of abstraction: an outer loop in the space of theories and an inner loop in the space of explanations or models generated by each theory given a particular dataset. We show that this stochastic search is capable of learning appropriate theories in several everyday domains and discuss its dynamics in the context of empirical studies of children's learning.