It is well established that motion aftereffects (MAEs) can show interocular transfer (IOT); that is, motion adaptation in one eye can give a MAE in the other eye. Different quantification methods and different test stimuli have been shown to give different IOT magnitudes, varying from no to almost full IOT. In this study, we examine to what extent IOT of the dynamic MAE (dMAE), that is the MAE seen with a dynamic noise test pattern, varies with velocity of the adaptation stimulus. We measured strength of dMAE by a nulling method. The aftereffect induced by adaptation to a moving random-pixel array was compensated (nulled), during a brief dynamic test period, by the same kind of motion stimulus of variable luminance signal-to-noise ratio (LSNR). The LSNR nulling value was determined in a Quest-staircase procedure. We found that velocity has a strong effect on the magnitude of IOT for the dMAE. For increasing speeds from 1.5 deg s(-1) to 24 deg s(-1) average IOT values increased about linearly from 18% to 63% or from 32% to 83%, depending on IOT definition. The finding that dMAEs transfer to an increasing extent as speed increases, suggests that binocular cells play a more dominant role at higher speeds. 相似文献
We examine the differential signaling impact of two low pricing policies, Price Matching Guarantees and Everyday Low Prices, on consumers' trusting beliefs and purchase intentions. We demonstrate that both PMG and EDLP pricing policies signal stores' ability to offer lower prices. However, whether these sellers were perceived as benevolent, and—consequently—consumers' purchase intentions, varied critically depending upon price uncertainty. Perceived benevolence and purchase intentions were significantly higher [lower] for sellers offering PMG than EDLP when price dispersion was high [low]. Our findings offer insights into whether and under what conditions firms should adopt these low pricing policies. 相似文献
The social network perspective provides a valuable lens to understand the effectiveness of team leaders. In understanding leadership impact in team networks, an important question concerns the structural influence of leader centrality in advice-giving networks on team performance. Taking the inconsistent evidence for the positive relationship of network centrality and leadership effectiveness as a starting point, we suggest that the positive impact of leader centrality in advice-giving networks is contingent on team needs for leadership to meet communication and coordination challenges, which we argue are larger in larger teams. Developing our analysis, we examine the mediating role of member collaboration in the relationship of leader network centrality and team performance as moderated by team size. Based on a multi-source dataset of 542 employees and 71 team leaders, we found that leader centrality in advice-giving networks related positively to team performance in larger teams but negatively in smaller teams. Results supported the mediated moderation model via member collaboration in smaller teams, but not in larger teams.