7-11-year-old children show an advantage for matching and recognizing the internal features of familiar faces: Evidence against a developmental shift

Adults are better at recognizing familiar faces from the internal facial features (eyes, nose, mouth) than from the external facial features (hair, face outline). However, previous research suggests that this “internal advantage” does not appear until relatively late in childhood, and some studies suggest that children rely on external features to recognize all faces, whether familiar or not. We use a matching task to examine face processing in 7-8- and 10-11-year-old children. We use a design in which all face stimuli can be used as familiar items (for participants who are classmates) and unfamiliar items (for participants from a different school). Using this design, we find an internal feature advantage for matching familiar faces, for both groups of children. The same children were then shown the external and internal features of their classmates and were asked to name or otherwise identify them. Again, both age groups identified more of their classmates correctly from the internal than the external features. This is the first time an internal advantage has been reported in this age group. Results suggest that children as young as 7 process faces in the same way as do adults, and that once procedural difficulties are overcome, the standard effects of familiarity are observed.     

Toward a predictive model of suicidal ideation and behavior: some preliminary data in college students

Within a multivariate statistical design, the relationship of various interpersonal, emotional, and cognitive variables to suicidal ideation and behavior in college students was examined. A total of 158 subjects (58 males, 100 females) completed self-report measures of life stress, faulty cognitions, loneliness, depression, hopelessness, family cohesiveness, adaptive reasons for living, and suicidal ideation and behavior. The results of a multiple-regression analysis, forward-inclusion algorithm, indicated that a predictive equation consisting of loneliness, irrational beliefs, and low adaptive reasons for living best accounted for suicidal behavior scores. To determine the basic structures and power of the predictor variables under study, a factor analysis and composite regression were employed, resulting in a predictive equation consisting of three factors: Social/Emotional Alienation, Cognitive Distortions, and Deficient Adaptive Resources. Results are discussed in terms of an interactional model of suicidal behavior.     

Familiarity influences judgments of sex: the case of voice recognition

Two experiments are reported in which subjects made judgments about the sex or the familiarity of a voice. In experiment 1, subjects were fans of the BBC-radio soap opera, The Archers, and familiar voice clips were taken from this programme. Subjects showed a large reduction in response times when making sex judgments to familiar voices, despite the fact that sex judgments are generally much faster than familiarity judgments. In experiment 2, the same familiar clips were played to subjects unfamiliar with the soap opera, and no difference was observed in times to make sex judgments to Archers or non-Archers voices. We conclude that, unlike the case of face recognition, sex and identity processing of voices are not independent. The findings constrain models of person recognition across multiple modalities.     

Finding MAPs using strongly equivalent high order recurrent symmetric connectionist networks

Belief revision is the problem of finding the most plausible explanation for an observed set of evidences. It has many applications in various scientific domains like natural language understanding, medical diagnosis and computational biology. Bayesian Networks (BN) is an important probabilistic graphical formalism widely used for belief revision tasks. In BN, belief revision can be achieved by finding the maximum a posteriori (MAP) assignment. Finding MAP is an NP-Hard problem. In previous work, we showed how to find the MAP assignment in BN using High Order Recurrent Neural Networks (HORN) through an intermediate representation of Cost-Based Abduction. This method eliminates the need to explicitly construct the energy function in two steps, objective and constraints. This paper builds on that previous work by providing the theoretical foundation and proving that the resultant HORN used to find MAP is strongly equivalent to the original BN it tries to solve.     

In conflict with ourselves? An investigation of heuristic and analytic processes in decision making

Many theorists propose two types of processing: heuristic and analytic. In conflict tasks, in which these processing types lead to opposing responses, giving the analytic response may require bothdetection andresolution of the conflict. The ratio bias task, in which people tend to treat larger numbered ratios (e.g., 20/100) as indicating a higher likelihood of winning than do equivalent smaller numbered ratios (e.g., 2/10), is considered to induce such a conflict. Experiment 1 showed response time differences associated with conflict detection, resolution, and the amount of conflict induced. The conflict detection and resolution effects were replicated in Experiment 2 and were not affected by decreasing the influence of the heuristic response or decreasing the capacity to make the analytic response. The results are consistent with dual-process accounts, but a single-process account in which quantitative, rather than qualitative, differences in processing are assumed fares equally well in explaining the data.     

Separating the confident from the correct: Leveraging member knowledge in groups to improve decision making and performance

Groups often struggle to distinguish expert members from others who stand out for various reasons but may not be particularly knowledgeable (Littlepage & Mueller, 1997). We examined an intervention designed to improve group decision making and performance through instructing group members to search for information they already possessed that was relevant to a problem. Participants estimated values and expressed their confidence in their estimates individually and then a second time either individually or in a group. This was done with or without the intervention. Results indicated that: (1) groups were more confident than, and out-performed, individuals, (2) group decision making was best captured by models predicting more influence for more accurate members when the intervention was used and more influence for more confident members in its absence, and (3) groups that received the intervention out-performed groups that did not.     

Effectiveness of Positive Hypothesis Testing in Inductive and Deductive Rule Learning

In a positive hypothesis test a person generates or examines evidence that is expected to have the property of interest if the hypothesis is correct, whereas in a negative hypothesis test a person generates or examines evidence that is not expected to have the property of interest if the hypothesis is correct. Two experiments assessed the effectiveness of positive versus negative hypothesis tests on inductive and deductive rule learning problems. In Experiment 1 problem solvers induced a rule by proposing hypotheses and selecting evidence in the eight conditions of a factorial design defined by instructions to use a positive or negative hypothesis test on each of trials 1-5, 6-10, and 11-15. Instructions to use positive tests resulted in more examples, fewer strategic hypotheses, and a higher weighted score for five types of hypotheses than instructions to use negative tests. In Experiment 2 problem solvers identified 1 of a possible 1296 correct rules in the deductive rule learning game Mastermind. When problems were classified in the 16 possible combinations of positive or negative hypothesis tests on trials 2, 3, 4, and 5 there were fewer trials to solution for positive tests on each of the four trials and fewer trials to solution with increasing positive tests. We conclude that positive hypothesis tests are generally more effective than negative hypothesis tests in both inductive and deductive rule learning. Copyright 1999 Academic Press.     

Further analysis of subtypes of automatically reinforced SIB: A replication and quantitative analysis of published datasets

Hagopian, Rooker, and Zarcone (2015) evaluated a model for subtyping automatically reinforced self‐injurious behavior (SIB) based on its sensitivity to changes in functional analysis conditions and the presence of self‐restraint. The current study tested the generality of the model by applying it to all datasets of automatically reinforced SIB published from 1982 to 2015. We identified 49 datasets that included sufficient data to permit subtyping. Similar to the original study, Subtype‐1 SIB was generally amenable to treatment using reinforcement alone, whereas Subtype‐2 SIB was not. Conclusions could not be drawn about Subtype‐3 SIB due to the small number of datasets. Nevertheless, the findings support the generality of the model and suggest that sensitivity of SIB to disruption by alternative reinforcement is an important dimension of automatically reinforced SIB. Findings also suggest that automatically reinforced SIB should no longer be considered a single category and that additional research is needed to better understand and treat Subtype‐2 SIB.