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.     

Stability control of grasping objects with different locations of center of mass and rotational inertia

The objective of this study was to observe how the digits of the hand adjust to varying location of the center of mass (CoM) above or below the grasp and rotational inertia (RI) of a handheld object. Such manipulations do not immediately affect the equilibrium equations while stability control is affected. Participants were instructed to hold a handle, instrumented with 5 force-torque transducers and a 3-D rotational tilt sensor, while either the location of the CoM or the RI values were adjusted. On the whole, people use 2 mechanisms to adjust to the changed stability requirements; they increase the grip force and redistribute the total moment between the normal and tangential forces offsetting internal torques. The increase in grip force, an internal force, and offsetting internal torques allows for increases in joint and hand rotational apparent stiffness while not creating external forces-torques that would unbalance the equations of equilibrium.     

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.