Change one can believe in: Adding learning to computational models of self-regulation

Theories of self-regulation describe motivation as a dynamic process of goal choice and goal striving. To facilitate those processes, individuals learn about themselves and their environment, which is an internal dynamic process. However, the precise nature of the relationship between these learning and motivational processes is not well specified. This article integrates formal models of learning, goal choice, and goal striving using a single information processing structure found in self-regulatory models of motivation. Results from two published studies ( and ) validate the model. In both cases, the integrated model accounts for findings that previous theories of self-regulation could not explain. Discussion focuses on additional tests to validate the model and on the value of incorporating formal models from the cognitive, learning, and motivational literatures to account for behavior in complex settings and over time.     

Kinematic Measures of Imitation Fidelity in Primary School Children

We sought to develop a method for measuring imitation accuracy objectively in primary school children. Children imitated a model drawing shapes on the same computer-tablet interface they saw used in video clips, allowing kinematics of model and observers' actions to be directly compared. Imitation accuracy was reported as a correlation reflecting the statistical dependency between values of the model's and participant's sets of actions, or as a mean absolute difference between them. Children showed consistent improvement in imitation accuracy across middle childhood. They appeared to rationalize the demands of the task by remembering duration and size of action, which enabled them to reenact speed through motor-planning mechanisms. Kinematic measures may provide a window into the cognitive mechanisms involved in imitation.     

Emotional scenes elicit more pronounced self-reported emotional experience and greater EPN and LPP modulation when compared to emotional faces

Emotional faces and scenes carry a wealth of overlapping and distinct perceptual information. Despite widespread use in the investigation of emotional perception, expressive face and evocative scene stimuli are rarely assessed in the same experiment. Here, we evaluated self-reports of arousal and pleasantness, as well as early and late event-related potentials (e.g., N170, early posterior negativity [EPN], late positive potential [LPP]) as subjects viewed neutral and emotional faces and scenes, including contents representing anger, fear, and joy. Results demonstrate that emotional scenes were rated as more evocative than emotional faces, as only scenes produced elevated self-reports of arousal. In addition, viewing scenes resulted in more extreme ratings of pleasantness (and unpleasantness) than did faces. EEG results indicate that both expressive faces and emotional scenes evoke enhanced negativity in the N170 component, while the EPN and LPP components show significantly enhanced modulation only by scene, relative to face stimuli. These data suggest that viewing emotional scenes results in a more pronounced emotional experience that is associated with reliable modulation of visual event-related potentials that are implicated in emotional circuits in the brain.     

Salience Not Status: How Category Labels Influence Feature Inference

Two main uses of categories are classification and feature inference, and category labels have been widely shown to play a dominant role in feature inference. However, the nature of this influence remains unclear, and we evaluate two contrasting hypotheses formalized as mathematical models: the label special‐mechanism hypothesis and the label super‐salience hypothesis. The special‐mechanism hypothesis is that category labels, unlike other features, trigger inference decision making in reference to the category prototypes. This results in a tendency for prototype‐compatible inferences because the labels trigger a special mechanism rather than because of any influences they have on similarity evaluation. The super‐salience hypothesis assumes that the large label influence is due to their high salience and corresponding impact on similarity without any need for a special mechanism. Application of the two models to a feature inference task based on a family resemblance category structure yields strong support for the label super‐salience hypothesis and in particular does not support the need for a special mechanism based on prototypes.     

Revoking a leader's “license to fail”: downgrading evaluations of prototypical in‐group leaders following an intergroup failure

Drawing on the social identity theory of leadership, we examined how leadership as an identity function alters perceptions and evaluations of in‐ and out‐group political leaders over time. Participants responded to two online questionnaires, before and after the 2012 U.S. Presidential election between Democrat Barack Obama and Republican Mitt Romney. We assessed respondents' strength of party identification, perceptions of each candidate's prototypicality, and evaluations of each candidate. Results supported the hypothesis: after his loss, Romney was presumably perceived as less prototypical of the Republican Party among strong identifiers, who symbolically revoked Romney's “license to fail.” Weakly identified Republicans were unaffected by his defeat, granting him a “license to fail.” Unexpectedly, Democrats and Republicans following his electoral success evaluated Obama more harshly.