A Multi-informant Multi-Measure Approach to the Two Factor Model of Emotion with Youth

The two-factor model of emotion clarifies the complexities of the relationship between anxiety and depression through their varying associations with positive and negative affect. Although this model’s structure has been studied in children, the lack of parent report measures on model-specific constructs has thus far prevented a multi-informant perspective on the model. Capitalizing on recent advancements in parent report assessment instruments, the present investigation aimed to confirm the two-factor model of emotion per child self-report; expand the model’s applicability to include parent report; and create a combined-informant model with a large number of parent-child dyad pairs (N?=?610). Structural equation modeling demonstrated good fit within parent and child informant models, but diminished fit for the multi-informant model. These results suggest a high degree of robustness with respect to informant type. Implications for the integration of multi-informant assessment information are discussed.     

A simple computational algorithm of model-based choice preference

A broadly used computational framework posits that two learning systems operate in parallel during the learning of choice preferences—namely, the model-free and model-based reinforcement-learning systems. In this study, we examined another possibility, through which model-free learning is the basic system and model-based information is its modulator. Accordingly, we proposed several modified versions of a temporal-difference learning model to explain the choice-learning process. Using the two-stage decision task developed by Daw, Gershman, Seymour, Dayan, and Dolan (2011), we compared their original computational model, which assumes a parallel learning process, and our proposed models, which assume a sequential learning process. Choice data from 23 participants showed a better fit with the proposed models. More specifically, the proposed eligibility adjustment model, which assumes that the environmental model can weight the degree of the eligibility trace, can explain choices better under both model-free and model-based controls and has a simpler computational algorithm than the original model. In addition, the forgetting learning model and its variation, which assume changes in the values of unchosen actions, substantially improved the fits to the data. Overall, we show that a hybrid computational model best fits the data. The parameters used in this model succeed in capturing individual tendencies with respect to both model use in learning and exploration behavior. This computational model provides novel insights into learning with interacting model-free and model-based components.     

Proper Semantics for Substructural Logics,from a Stalker Theoretic Point of View

We study filters in residuated structures that are associated with congruence relations (which we call -filters), and develop a semantical theory for general substructural logics based on the notion of primeness for those filters. We first generalize Stone’s sheaf representation theorem to general substructural logics and then define the primeness of -filters as being “points” (or stalkers) of the space, the spectrum, on which the representing sheaf is defined. Prime FL-filters will turn out to coincide with truth sets under various well known semantics for certain substructural logics. We also investigate which structural rules are needed to interpret each connective in terms of prime -filters in the same way as in Kripke or Routley-Meyer semantics. We may consider that the set of the structural rules that each connective needs in this sense reflects the difficulty of giving the meaning of the connective. A surprising discovery is that connectives , ⅋ of linear logic are linearly ordered in terms of the difficulty in this sense. Presented by Wojciech Buszkowski     

Common and Unique Factors Associated with DSM-IV-TR Internalizing Disorders in Children

With the fifth edition of the Diagnostic and Statistical Manual of Mental Disorders (American Psychiatric Association. Diagnostic and statistical manual of mental disorders DSM-IV Fourth Edition-Text Revision. Author, Washington, DC. 2000) ahead, decisions will be made about the future of taxonomic conceptualizations. This study examined the factor structure of items from three internalizing disorders (Social Phobia, Generalized Anxiety Disorder, and Depression) on the Anxiety Disorders Interview Schedule for DSM-IV-Child Version (Silverman, W. K., & Albano, A. M. Anxiety disorders interview schedule for children for DSM-IV, child and parent versions. Psychological Corporation, San Antonio, 1996). Two-, three-, and four-factor models emerged in an exploratory factor analysis. Confirmatory factor analysis provided additional empirical support for the four-factor model over the two- or three-factor models. Implications for the structure of the DSM-V taxonomy in children and adolescents are discussed.     

Seeing the Forest Beyond the Trees: A Construal‐Level Approach to Self‐Control

Self‐control failure is a ubiquitous and troubling problem people face. This article reviews psychological models of self‐control and describes a new integrative approach based on construal level theory (e.g., Trope & Liberman, 2003 ). This construal‐level perspective proposes that people's subjective mental construals or representations of events impacts self‐control. Specifically, more abstract, global (high‐level) construals promote self‐control success, whereas more concrete, local (low‐level) construals tend to lead to self‐control failure. That is, self‐control is promoted when people see the proverbial forest beyond the trees. This article surveys research findings that demonstrate that construing events at high‐level versus low‐level construals promotes self‐control. This article also discusses how a construal‐level perspective promotes understanding of self‐control failures.     

Inhibition in Goal Systems: A Retrieval-Induced Forgetting Account

In social psychological models of goals, particular means or goals that receive more activation are pursued while their counterparts are “inhibited.” To account for inhibition, these theories emphasize structural distribution of resources and the consequences of goal or means choices. Absent are alternate accounts of inhibition based on memory processes that rely on retrieval or recall of items. We propose that the act of recalling means or goals from memory entails inhibition of competing alternatives. Two experiments using repeated retrieval paradigms present evidence that recalling one means associated with a particular goal inhibits competing means. Moreover, this inhibitory mechanism is sensitive to the structural relationship of goals and means. Implications for models of inhibition in goal pursuit are discussed.     

Differences in adrenocortical secretory and gene expression responses to stimulation in vitro by ACTH or prolactin between high- and low-avoidance Hatano rats

Rats of the Hatano high-avoidance (HAA) and low-avoidance (LAA) strains have been genetically selected on the basis of their two-way active avoidance behavior, and have different endocrine responses to stress. The present study focused on the adrenal steroid hormone responses of the Hatano strains and identifies differences in regulation of the adrenal cortex in vitro of HAA and LAA rats. Although incubation with prolactin (PRL) and/or adrenocorticotrophic hormone (ACTH) resulted in a dose-dependent increase of corticosterone and progesterone release by adrenal cells from both HAA and LAA male rats, the responses were markedly increased for adrenal cells from LAA rats as compared with HAA rats. This finding suggested that adrenal glands of HAA rats are less sensitive to PRL and/or ACTH than adrenals from LAA rats. Several possible intra-adrenal regulators were investigated. The basal level of expression of steroidogenic acute regulatory protein (StAR) and the long form of the PRL receptor (PRLR-L) mRNAs was higher in adrenals of LAA rats. ACTH treatment of adrenal cells from HAA rats resulted in statistically significant increases in melanocortin receptor 2 (MC2R) mRNA expression, while neither ACTH nor PRL altered MC2R mRNA expression in adrenal cells of LAA rats. Conversely, the increase in PRLR-L mRNA expression induced by PRL was observed only in adrenal cells from LAA rats. Treatment of adrenal cells with PRL and/or ACTH increased the expression of StAR and CYP11A1 mRNAs for both Hatano strains. However, the induction of StAR mRNA expression was higher in LAA rats, but the CYP11A1 response was lower. These findings indicate that adrenal cells of the LAA strain have higher sensitivity to secretagogues than those of the HAA strain. These results suggest that PRL may also be important in stimulating secretion of adrenal steroid hormones.     

Categorical and dimensional perceptions in decoding emotional facial expressions

We investigated whether categorical perception and dimensional perception can co-occur while decoding emotional facial expressions. In Experiment 1, facial continua with endpoints consisting of four basic emotions (i.e., happiness–fear and anger–disgust) were created by a morphing technique. Participants rated each facial stimulus using a categorical strategy and a dimensional strategy. The results show that the happiness–fear continuum was divided into two clusters based on valence, even when using the dimensional strategy. Moreover, the faces were arrayed in order of the physical changes within each cluster. In Experiment 2, we found a category boundary within other continua (i.e., surprise–sadness and excitement–disgust) with regard to the arousal and valence dimensions. These findings indicate that categorical perception and dimensional perception co-occurred when emotional facial expressions were rated using a dimensional strategy, suggesting a hybrid theory of categorical and dimensional accounts.     

Standard errors for the class of orthomax-rotated factor loadings: Some matrix results

The partial derivative matrices of the class of orthomax-rotated factor loadings with respect to the unrotated maximum likelihood factor loadings are derived. The reported results are useful for obtaining standard errors of the orthomax-rotated factor loadings, with or without row normalization (standardization) of the initial factor loading matrix for rotation. Using a numerical example, we verify our analytic formulas by comparing the obtained standard error estimates with that from some existing methods. Some advantages of the current approach are discussed.Authorship is determined by alphabetical order. The authors contributed equally to the research. Kentaro Hayashi is now at the Department of Mathematics, Bucknell University, Lewisburg, PA 17837 (email: khayashi@Bucknell.edu). Yiu-Fai Yung is now at the SAS Institute, Inc., SAS Campus Drive, Cary, NC 27513 (email: yiyung@wnt.sas.com).Part of the research was completed while Yiu-Fai Yung was a visiting scholar at the Department of Psychology, the Ohio State University. The visit was supported in part by grant N4856118101 from the NIMH and the Mason and Linda Stephenson Travel Award from the Department of Psychology, University of North Carolina at Chapel Hill. The authors are grateful to Michael Browne who suggested some relevant references and provided valuable comments on the research, and to Robert Cudeck who provided the FAS program for the numerical comparison. The expert comments by the reviewers are deeply appreciated.