Getting the Right Idea: Semantic Activation in the Right HemisphereMay Help Solve Insight Problems

Two experiments examined hemispheric differences in information processing that may contribute to solving insight problems. We propose that right-hemisphere (RH) coarse semantic coding is more likely than left-hemisphere (LH) fine semantic coding to activate distantly related information or unusual interpretations of words, and thus more likely to activate solution-relevant information for insight problems. In Experiment 1, after trying to solve insight problems, participants read aloud solution or unrelated target words presented to the left visual field (lvf) or right visual field (rvf). Participants showed greater lvf-RH than rvf-LH priming for solutions for solved problems and priming only in the lvf-RH for unsolved problems. In Experiment 2, participants showed an lvf-RH advantage for recognizing solutions to unsolved problems. These results demonstrate that in a problem-solving context, there was greater activation of solution-relevant information in the RH than in the LH. This activation is useful for recognizing, and perhaps producing, solutions to insight problems.     

Observer Perceptions of Would-Be Provider and Would-Be Recipient Reactions to Rejected Social Support1

Role-playing observers predicted the reactions of hypothetical would-be recipients whose requests for social support were unmet as well as those of hypothetical would-be providers for their rejection of such requests. The extent to which the would-be recipient was depicted at fault for the problem was predicted to affect perceived reactions since support may be less likely when potential recipients are blameworthy than when they are innocent of responsibility for their predicament. Observers perceived would-be recipients of support as believing that would-be providers blamed them. Observers saw would-be providers as blaming the would-be recipients rather than themselves, especially if the victim was blameworthy. When the victim was not blameworthy, would-be providers were more likely than would-be recipients to be judged to use a mixture of rationalizations and excuses rather than blame.     

Search efficiency is not sufficient: The nature of search modulates stimulus-driven attention

It has long been debated whether or not a salient stimulus automatically attracts people’s attention in visual search. Recent findings showed that a salient stimulus is likely to capture attention especially when the search process was inefficient due to high levels of competition between the target and distractors. Expanding these studies, the present study proposes that a specific nature of visual search, as well as search efficiency, determines whether or not a salient, task-irrelevant singleton stimulus captures attention. To test this proposition, we conducted three experiments, in which participants performed two visual search tasks whose underlying mechanisms are known to be different: orientation-feature search and Landolt-C search tasks. We found that color singleton distractors captured attention when participants performed the orientation-feature search task. The magnitude of this capture effect increased as search efficiency decreased. On the contrary, the capture by singleton distractors was not observed under the Landolt-C search task. This differential pattern of capture effect was not due to differences in search efficiency across the search tasks; even when search efficiency was controlled for, stimulus-driven capture of attention by a salient distractor was found only under the feature search. Based on these results, the present study suggests that in addition to search efficiency, the nature of search strategy and the extent to which attentional control is strained play crucial roles in observing stimulus-driven attentional capture in visual search.     

Functional Multiple-Set Canonical Correlation Analysis

We propose functional multiple-set canonical correlation analysis for exploring associations among multiple sets of functions. The proposed method includes functional canonical correlation analysis as a special case when only two sets of functions are considered. As in classical multiple-set canonical correlation analysis, computationally, the method solves a matrix eigen-analysis problem through the adoption of a basis expansion approach to approximating data and weight functions. We apply the proposed method to functional magnetic resonance imaging (fMRI) data to identify networks of neural activity that are commonly activated across subjects while carrying out a working memory task.     

Dynamic GSCA (Generalized Structured Component Analysis) with Applications to the Analysis of Effective Connectivity in Functional Neuroimaging Data

We propose a new method of structural equation modeling (SEM) for longitudinal and time series data, named Dynamic GSCA (Generalized Structured Component Analysis). The proposed method extends the original GSCA by incorporating a multivariate autoregressive model to account for the dynamic nature of data taken over time. Dynamic GSCA also incorporates direct and modulating effects of input variables on specific latent variables and on connections between latent variables, respectively. An alternating least square (ALS) algorithm is developed for parameter estimation. An improved bootstrap method called a modified moving block bootstrap method is used to assess reliability of parameter estimates, which deals with time dependence between consecutive observations effectively. We analyze synthetic and real data to illustrate the feasibility of the proposed method.     

Testing mediator variables in a resistance training intervention for obese adults with type 2 diabetes

A poor understanding of behaviour change mechanisms has hindered the development of effective physical activity interventions. The aim of this study was to identify potential mediators of change in a home-based resistance training (RT) program for obese individuals with type 2 diabetes. Obese individuals with type 2 diabetes (N?=?48) were randomly allocated to either an RT intervention (n?=?27) or a control group (n?=?21) for the 16-week study period. The study sample included 16 men and 32 women and the mean age of participants was 54.4 (±11.7) years. Participants in the RT group received a multi-gym and dumbbells and home supervision from a certified personal trainer. RT behaviour was measured using a modified Godin Leisure Time Questionnaire. Social-cognitive constructs were measured and tested in a mediating variable framework using a product-of-coefficients test. The intervention had a significant effect on RT behaviour (p?相似文献