Ensemble coding of facial identity is not refined by experience: Evidence from other-race and inverted faces

The ability to recognize identity despite within-person variability in appearance is likely a face-specific skill and shaped by experience. Ensemble coding – the automatic extraction of the average of a stimulus array – has been proposed as a mechanism underlying face learning (allowing one to recognize novel instances of a newly learned face). We investigated whether ensemble encoding, like face learning and recognition, is refined by experience by testing participants with upright own-race faces and two categories of faces with which they lacked experience: other-race faces (Experiment 1) and inverted faces (Experiment 2). Participants viewed four images of an unfamiliar identity and then were asked whether a test image of that same identity had been in the study array. Each test image was a matching exemplar (from the array), matching average (the average of the images in the array), non-matching exemplar (a novel image of the same identity), or non-matching average (an average of four different images of the same identity). Adults showed comparable ensemble coding for all three categories (i.e., reported that matching averages had been present more than non-matching averages), providing evidence that this early stage of face learning is not shaped by face-specific experience.     

Examining the Potential Mental Health Costs of Defending Victims of Bullying: a Longitudinal Analysis

Research on Child and Adolescent Psychopathology - It has been speculated that defending victims of bullying is stressful for youth, and may contribute to poor mental health among those who...     

Counterexample Search in Diagram-Based Geometric Reasoning

Topological relations such as inside, outside, or intersection are ubiquitous to our spatial thinking. Here, we examined how people reason deductively with topological relations between points, lines, and circles in geometric diagrams. We hypothesized in particular that a counterexample search generally underlies this type of reasoning. We first verified that educated adults without specific math training were able to produce correct diagrammatic representations contained in the premisses of an inference. Our first experiment then revealed that subjects who correctly judged an inference as invalid almost always produced a counterexample to support their answer. Noticeably, even if the counterexample always bore a certain level of similarity to the initial diagram, we observed that an object was more likely to be varied between the two drawings if it was present in the conclusion of the inference. Experiments 2 and 3 then directly probed counterexample search. While participants were asked to evaluate a conclusion on the basis of a given diagram and some premisses, we modulated the difficulty of reaching a counterexample from the diagram. Our results indicate that both decreasing the counterexample density and increasing the counterexample distance impaired reasoning performance. Taken together, our results suggest that a search procedure for counterexamples, which proceeds object-wise, could underlie diagram-based geometric reasoning. Transposing points, lines, and circles to our spatial environment, the present study may ultimately provide insights on how humans reason about topological relations between positions, paths, and regions.