A Dyadic IRT Model

Psychometrika - We propose a dyadic Item Response Theory (dIRT) model for measuring interactions of pairs of individuals when the responses to items represent the actions (or behaviors,...     

EARSHOT: A Minimal Neural Network Model of Incremental Human Speech Recognition

Despite the lack of invariance problem (the many-to-many mapping between acoustics and percepts), human listeners experience phonetic constancy and typically perceive what a speaker intends. Most models of human speech recognition (HSR) have side-stepped this problem, working with abstract, idealized inputs and deferring the challenge of working with real speech. In contrast, carefully engineered deep learning networks allow robust, real-world automatic speech recognition (ASR). However, the complexities of deep learning architectures and training regimens make it difficult to use them to provide direct insights into mechanisms that may support HSR. In this brief article, we report preliminary results from a two-layer network that borrows one element from ASR, long short-term memory nodes, which provide dynamic memory for a range of temporal spans. This allows the model to learn to map real speech from multiple talkers to semantic targets with high accuracy, with human-like timecourse of lexical access and phonological competition. Internal representations emerge that resemble phonetically organized responses in human superior temporal gyrus, suggesting that the model develops a distributed phonological code despite no explicit training on phonetic or phonemic targets. The ability to work with real speech is a major advance for cognitive models of HSR.     

Effects of Gender and Appearance Comparisons on Associations Between Media-Based Appearance Pressure and Disordered Eating: Testing a Moderated Mediation Model

Sex Roles - Appearance pressure from mass media and appearance social comparisons have been implicated in theory and research on disordered eating. However, mediating effects of upward and downward...     

Why People Join Terrorist Groups in Kuwait: A Qualitative Examination

Qualitative interviews were conducted with nine members of the Islamic State of Iraq and Syria (ISIS) and Al-Qaeda currently incarcerated in Kuwait's Central Prison. The semistructured interviews attempted to understand psychosocial factors in Kuwait that contributed to their decision to join extremist organizations. Interviews were analyzed using Interpretive Phenomenological Analysis (IPA) and the emergent themes identified the following core themes explaining their involvement: (1) religious identity development; (2) personal connections; (3) propaganda; (4) defense of Islam; and (5) social marginalization. Participants described a process whereby their religion became a central part of their personal identity. As their religious identity developed, they became involved in Islamic organizations where they met people involved with ISIS or Al-Qaeda. These social connections exposed them to jihadi propaganda which, in addition to increased military conflict in the Middle East, crystallized their beliefs that Islam is under attack, and they were religiously obligated to defend it. The results also identified societal factors that increased the probability of engaging in terrorism including relatively low levels of education, coming from low socioeconomic groups in Kuwait, and feeling socially marginalized by broader Kuwaiti society.     

Changing counterproductive beliefs about attention,memory, and multitasking: Impacts of a brief,fully online module

Ubiquitous mobile technology is part of contemporary life, bringing with it the potential for distraction and reduction in performance associated with multitasking. The predisposition toward dysfunctional multitasking may be shaped in part by beliefs that individuals hold about memory and attention. The issue is particularly pressing for college students, given established links between distraction, multitasking, and learning. This project assessed the impact of an online learning module on beliefs about attention, memory, and learning in college students. It also contrasted these beliefs in a college and non-college community sample. Significant reductions in counterproductive beliefs were associated with completing the module; counterproductive beliefs were also no more prevalent in the college vs. the non-college sample. Our findings suggest that brief online modules are a practical way to address counterproductive beliefs related to multitasking with technology, and add to the literature on metacognition, attention, and multitasking in college and non-college populations.     

Thought-shape fusion in anorexia nervosa: an experimental investigation

Cognitive biases and cognitive distortions have been implicated as important factors in the development and maintenance of many disorders. The concept of thought-shape fusion (TSF) in eating disorders was developed by Shafran, Teachman, Kerry, and Rachman (British Journal of Clinical Psychology 38 (1999) 167) as a variant of thought-action fusion, described by Shafran, Thordarson and Rachman (Journal of Anxiety Disorders 10 (1996) 379). TSF occurs when thinking about eating certain types of food increases a person's estimate of their shape and/or weight, elicits a perception of moral wrongdoing, and/or makes the person feel fat. Shafran et al. (1999) examined both the psychometric and experimental properties of TSF in an undergraduate sample. This paper reports an extension of this work to a clinical group (N=20) of patients with anorexia nervosa. After completing a set of relevant questionnaires, participants were asked to think about a food which they considered extremely fattening. They were then asked to write out the sentence, "I am eating--.", inserting the name of the fattening food in the blank. After being asked to rate their anxiety, guilt, feelings about their weight, morality, etc., participants were given the opportunity to neutralize their statement in any way they chose. The majority of the participants neutralized in ways consistent with the findings of Shafran et al. (1999). The results are discussed in terms of cognitive-behavioural formulations of eating disorders, and of the influence of cognitive biases and cognitive distortions on the processing of information relevant to food, weight and shape in anorexia nervosa.     

Conceiving of entities as objects and as stuff

What is the difference between conceiving of an entity as an object of some kind and conceiving of it as an amount of solid stuff? We propose that the difference lies in how one thinks about the entity's structure. Object construals require thinking of the structure as being nonarbitrary, whereas substance construals require thinking of the structure as being arbitrary. We report six experiments that provide empirical support for this proposal. Regularity of structure, repetition of structure, and the existence of structure-dependent functions, all of which provide reasons to consider the structure of an entity to be nonarbitrary, were shown to bias participants towards object construals. We also discuss how the proposed account of what it means to construe an entity as an object or as some stuff can account for a range of findings in the literature on lexical development. These include the relation between cohesiveness and ontological category, shape and ontological category, and complexity of shape and ontological category. Finally, we discuss the nature of construals and the relation of object and substance construals to the physical, design, and intentional stances.     

Generalizing a neuropsychological model of visual categorization to auditory categorization of vowels

Twelve male listeners categorized 54 synthetic vowel stimuli that varied in second and third formant frequency on a Bark scale into the American English vowel categories [see text]. A neuropsychologically plausible model of categorization in the visual domain, the Striatal Pattern Classifier (SPC; Ashby & Waldron, 1999), is generalized to the auditory domain and applied separately to the data from each observer. Performance of the SPC is compared with that of the successful Normal A Posteriori Probability model (NAPP; Nearey, 1990; Nearey & Hogan, 1986) of auditory categorization. A version of the SPC that assumed piece-wise linear response region partitions provided a better account of the data than the SPC that assumed linear partitions, and was indistinguishable from a version that assumed quadratic response region partitions. A version of the NAPP model that assumed nonlinear response regions was superior to the NAPP model with linear partitions. The best fitting SPC provided a good account of each observer's data but was outperformed by the best fitting NAPP model. Implications for bridging the gap between the domains of visual and auditory categorization are discussed.