Imitation,Impersonation, and Transformation: Using Male Role Models in Films to Promote Maturity

Becoming a man is developmental. Boys model after men in their lives as well as figures they see in the media. When role models are positive, appropriate, and present, boys grow into constructive adults who contribute to society. This article examines how counselors can intentionally help young men mature into well‐grounded and prosocial individuals through the use of models in films. It provides a list of some movies that counselors can use in the process.     

SAwSu: An Integrated Model of Associative and Reinforcement Learning

Successfully explaining and replicating the complexity and generality of human and animal learning will require the integration of a variety of learning mechanisms. Here, we introduce a computational model which integrates associative learning (AL) and reinforcement learning (RL). We contrast the integrated model with standalone AL and RL models in three simulation studies. First, a synthetic grid‐navigation task is employed to highlight performance advantages for the integrated model in an environment where the reward structure is both diverse and dynamic. The second and third simulations contrast the performances of the three models in behavioral experiments, demonstrating advantages for the integrated model in accounting for behavioral data.     

计算模型视角下信任形成的心理和神经机制——基于信任博弈中投资者的角度

人际信任渗透在社会交互的各个方面, 是促进和维持合作的重要基石。以往研究者借助信任博弈范式, 主要探讨了人际信任的理论模型、生物基础和影响因素等方面。近年来, 研究者开始将计算模型应用于信任博弈的数据分析中, 深入挖掘人际信任行为背后的心理机制, 将计算模型与神经影像技术结合, 加深对信任行为背后脑机制的理解。目前将计算模型应用于信任博弈范式中的研究主要针对“信任是如何形成的”这一科学问题, 未来要进一步发展计算模型方法, 结合非侵入性脑刺激技术, 应用于精神疾病人群中, 以深入理解正常和异常信任形成的心理和神经机制。     

Organizational social context and psychopathology of youth in residential care: The intervening role of youth–caregiver relationship quality

Drawing on an ecological approach with multiple informants, this study investigated the mediating role of youth–caregiver relationship quality in associations between different features of residential care settings' organizational social context and youth's psychopathology. Participants were 378 youth aged between 12 and 25 years old, and 54 caregivers aged between 24 and 57 years old, from 29 generalist residential youth care settings in Portugal. Given the hierarchical structure of data, analyses were performed using multilevel modeling. Results revealed that organizational social contexts characterized by higher levels of engagement, stress, and centralization, as perceived by the caregivers, were associated with lower levels of youth's externalizing problems (e.g., aggressive behavior and delinquency), reported by the caregivers, via better youth–caregiver relationship quality, perceived by the youth in care. These findings highlight the relevance of creating an organizational social context in residential care settings that supports caregivers in establishing high-quality relationships with the youth in care, thereby promoting their mental health. This study contributes to the clarification of conflicting findings in previous studies of this field, by offering further empirical investigation of these issues.     

A zero-bounded model of operant demand

Contemporary approaches for evaluating the demand for reinforcers use either the Exponential or the Exponentiated model of operant demand, both derived from the framework of Hursh and Silberberg (2008). This report summarizes the strengths and complications of this framework and proposes a novel implementation. This novel implementation incorporates earlier strengths and resolves existing shortcomings that are due to the use of a logarithmic scale for consumption. The Inverse Hyperbolic Sine (IHS) transformation is reviewed and evaluated as a replacement for the logarithmic scale in models of operant demand. Modeling consumption in the “log₁₀-like” IHS scale reflects relative changes in consumption (as with a log scale) and accommodates a true zero bound (i.e., zero consumption values). The presence of a zero bound obviates the need for a separate span parameter (i.e., k) and the span of the model may be more simply defined by maximum demand at zero price (i.e., Q₀). Further, this reformulated model serves to decouple the exponential rate constant (i.e., α) from variations in span, thus normalizing the rate constant to the span of consumption in IHS units and permitting comparisons when spans vary. This model, called the Zero-bounded Exponential (ZBE), is evaluated using simulated and real-world data. The direct reinstatement ZBE model showed strong correspondence with empirical indicators of demand and with a normalization of α (ZBEn) across empirical data that varied in reinforcing efficacy (dose, time to onset of peak effects). Future directions in demand curve analysis are discussed with recommendations for additional replication and exploration of scales beyond the logarithm when accommodating zero consumption data.     

Quantifying the psychopathic stare: Automated assessment of head motion is related to antisocial traits in forensic interviews

Clinicians have long noted that individuals with high psychopathic traits exhibit unique interpersonal style often observable during forensic interviews. Here we develop an automated approach for quantifying head dynamics during video-recorded naturalistic clinical interviews. We expected head dynamics would be related to psychopathic traits. As predicted, dwell times indicate that those with higher levels of psychopathic traits are characterized by more stationary head positions, focused directly towards the camera/interviewer, than were individuals low in psychopathic traits. These associations were primarily driven by developmental/antisocial features of psychopathy, indicating that those with severe and life-course persistent antisocial behavior exhibit more rigid and focused orienting of their head during interpersonal communication. These results encourage more research into the automated quantification of behavioral manifestations of personality to support clinical observations that psychopaths exhibit unique qualities in non-verbal interpersonal communication.     

A Computational Evaluation of Two Models of Retrieval Processes in Sentence Processing in Aphasia

Can sentence comprehension impairments in aphasia be explained by difficulties arising from dependency completion processes in parsing? Two distinct models of dependency completion difficulty are investigated, the Lewis and Vasishth (2005) activation-based model and the direct-access model (DA; McElree, 2000). These models' predictive performance is compared using data from individuals with aphasia (IWAs) and control participants. The data are from a self-paced listening task involving subject and object relative clauses. The relative predictive performance of the models is evaluated using k-fold cross-validation. For both IWAs and controls, the activation-based model furnishes a somewhat better quantitative fit to the data than the DA. Model comparisons using Bayes factors show that, assuming an activation-based model, intermittent deficiencies may be the best explanation for the cause of impairments in IWAs, although slowed syntax and lexical delayed access may also play a role. This is the first computational evaluation of different models of dependency completion using data from impaired and unimpaired individuals. This evaluation develops a systematic approach that can be used to quantitatively compare the predictions of competing models of language processing.     

Friends in Low-Entropy Places: Orthographic Neighbor Effects on Visual Word Identification Differ Across Letter Positions

Visual word recognition is facilitated by the presence of orthographic neighbors that mismatch the target word by a single letter substitution. However, researchers typically do not consider where neighbors mismatch the target. In light of evidence that some letter positions are more informative than others, we investigate whether the influence of orthographic neighbors differs across letter positions. To do so, we quantify the number of enemies at each letter position (how many neighbors mismatch the target word at that position). Analyses of reaction time data from a visual word naming task indicate that the influence of enemies differs across letter positions, with the negative impacts of enemies being most pronounced at letter positions where readers have low prior uncertainty about which letters they will encounter (i.e., positions with low entropy). To understand the computational mechanisms that give rise to such positional entropy effects, we introduce a new computational model, VOISeR (Visual Orthographic Input Serial Reader), which receives orthographic inputs in parallel and produces an over-time sequence of phonemes as output. VOISeR produces a similar pattern of results as in the human data, suggesting that positional entropy effects may emerge even when letters are not sampled serially. Finally, we demonstrate that these effects also emerge in human subjects' data from a lexical decision task, illustrating the generalizability of positional entropy effects across visual word recognition paradigms. Taken together, such work suggests that research into orthographic neighbor effects in visual word recognition should also consider differences between letter positions.