The role of priming in conjunctive visual search

To assess the role of priming in conjunctive visual search tasks, we systematically varied the consistency of the target and distractor identity between different conditions. Search was fastest in the standard conjunctive search paradigm where identities remained constant. Search was slowest when potential target identity varied predictably for each successive trial (the 'switch' condition). The role of priming was also demonstrated on a trial-by-trial basis in a 'streak' condition where target and distractor identity was unpredictable yet was consistent within streaks. When the target to be found was the same for a few trials in a row, search performance became similar to that when the potential target was the same on all trials. A similar pattern was found for the target absent trials, suggesting that priming is based on the whole search array rather than just the target in each case. Further analysis indicated that the effects of priming are sufficiently strong to account for the advantage seen for the conjunctive search task. We conclude that the role of priming in visual search is underestimated in current theories of visual search and that differences in search times often attributed to top-down guidance may instead reflect the benefits of priming.     

Analog number representations in mongoose lemurs (Eulemur mongoz): evidence from a search task

A wealth of data demonstrating that monkeys and apes represent number have been interpreted as suggesting that sensitivity to number emerged early in primate evolution, if not before. Here we examine the numerical capacities of the mongoose lemur (Eulemur mongoz), a member of the prosimian suborder of primates that split from the common ancestor of monkeys, apes and humans approximately 47–54 million years ago. Subjects observed as an experimenter sequentially placed grapes into an opaque bucket. On half of the trials the experimenter placed a subset of the grapes into a false bottom such that they were inaccessible to the lemur. The critical question was whether lemurs would spend more time searching the bucket when food should have remained in the bucket, compared to when they had retrieved all of the food. We found that the amount of time lemurs spent searching was indicative of whether grapes should have remained in the bucket, and furthermore that lemur search time reliably differentiated numerosities that differed by a 1:2 ratio, but not those that differed by a 2:3 or 3:4 ratio. Finally, two control conditions determined that lemurs represented the number of food items, and neither the odor of the grapes, nor the amount of grape (e.g., area) in the bucket. These results suggest that mongoose lemurs have numerical representations that are modulated by Webers Law.     

7~12岁儿童视觉搜索能力的发展

该研究主要考察7~12岁儿童视觉搜索能力的发展。实验结果表明：儿童视觉搜索能力随年龄的增长而提高,性别差异不显著;儿童对三种不同视觉刺激材料（阿拉伯数字、英文字母、汉字）的视觉搜索的反应时没有表现出明显的差异,这个结果与通常的一些实验结果不同。同时,儿童在视觉搜索过程中,判断刺激出现的反应时均明显短于判断刺激没有出现的反应时;两种判断与左右手之间存在着交互作用。     

Model specification search using a genetic algorithm with factor reordering for a simple structure factor analysis model

Abstract:  Many techniques for automated model specification search based on numerical indices have been proposed, but no single decisive method has yet been determined. In the present article, the performance and features of the model specification search method using a genetic algorithm (GA) were verified. A GA is a robust and simple metaheuristic algorithm with great searching power. While there has already been some research applying metaheuristics to the model fitting task, we focus here on the search for a simple structure factor analysis model and propose a customized algorithm for dealing with certain problems specific to that situation. First, implementation of model specification search using a GA with factor reordering for a simple structure factor analysis is proposed. Then, through a simulation study using generated data with a known true structure and through example analysis using real data, the effectiveness and applicability of the proposed method were demonstrated.     

Mapping the color space of saccadic selectivity in visual search

Color coding is used to guide attention in computer displays for such critical tasks as baggage screening or air traffic control. It has been shown that a display object attracts more attention if its color is more similar to the color for which one is searching. However, what does similar precisely mean? Can we predict the amount of attention that a display color will receive during a search for a given target color? To tackle this question, two color‐search experiments measuring the selectivity of saccadic eye movements and mapping out its underlying color space were conducted. A variety of mathematical models, predicting saccadic selectivity for given target and display colors, were devised and evaluated. The results suggest that applying a Gaussian function to a weighted Euclidean distance in a slightly modified HSI color space is the best predictor of saccadic selectivity in the chosen paradigm. Hue and intensity information by itself provides a basis for useful predictors, spanning a possibly spherical color space of saccadic selectivity. Although the current models cannot predict saccadic selectivity values for a wide variety of visual search tasks, they reveal some characteristics of color search that are of both theoretical and applied interest, such as for the design of human–computer interfaces.     

视觉搜索过程中的眼跳及其机制

该文对视觉搜索过程中的眼跳及其时间进程、神经机制及相关的理论与模型等方面研究进行了回顾。发现内外源性眼跳得到了研究者的普遍关注,对眼运动记忆、返回抑制及眼跳时间进程的研究尚存在分歧。关于眼跳的神经机制,额叶眼动区与上丘分别被认为是眼跳的关键区与指令发出者。尽管不同的眼跳理论与模型对眼跳现象给出了各自的解释,但都不尽完善,尚需对这些理论进行整合或者提出新的解释模型。文章还对未来的研究进行了展望     

What is adaptive about adaptive decision making? A parallel constraint satisfaction account

There is broad consensus that human cognition is adaptive. However, the vital question of how exactly this adaptivity is achieved has remained largely open. Herein, we contrast two frameworks which account for adaptive decision making, namely broad and general single-mechanism accounts vs. multi-strategy accounts. We propose and fully specify a single-mechanism model for decision making based on parallel constraint satisfaction processes (PCS-DM) and contrast it theoretically and empirically against a multi-strategy account. To achieve sufficiently sensitive tests, we rely on a multiple-measure methodology including choice, reaction time, and confidence data as well as eye-tracking. Results show that manipulating the environmental structure produces clear adaptive shifts in choice patterns – as both frameworks would predict. However, results on the process level (reaction time, confidence), in information acquisition (eye-tracking), and from cross-predicting choice consistently corroborate single-mechanisms accounts in general, and the proposed parallel constraint satisfaction model for decision making in particular.     

Are summary statistics enough? Evidence for the importance of shape in guiding visual search

Peripheral vision outside the focus of attention may rely on summary statistics. We used a gaze-contingent paradigm to directly test this assumption by asking whether search performance differed between targets and statistically-matched visualizations of the same targets. Four-object search displays included one statistically-matched object that was replaced by an unaltered version of the object during the first eye movement. Targets were designated by previews, which were never altered. Two types of statistically-matched objects were tested: One that maintained global shape and one that did not. Differences in guidance were found between targets and statistically-matched objects when shape was not preserved, suggesting that they were not informationally equivalent. Responses were also slower after target fixation when shape was not preserved, suggesting an extrafoveal processing of the target that again used shape information. We conclude that summary statistics must include some global shape information to approximate the peripheral information used during search.     

Predictors of re‐employment: A question of attitude,behavior, or gender?

This longitudinal study examined the predictive value of attitudes, personal‐related variables, job search behaviour, and demographic variables on re‐employment among 142 assembly workers who had been made redundant. Participants completed a questionnaire within a week after leaving their jobs, and another 15 months later. Results of hierarchical logistic regression revealed that gender (being male), was the strongest predictor of re‐employment. Willingness to relocate and desire to change occupation also increased the odds of re‐employment 15 months after dismissal. On the other hand ‐ having children at home and anonymous‐passive job‐search behaviour, which is more prevalent among women, decreased the odds for re‐employment. The study is contributing to research by revealing gender differences in job search behaviour and the importance of focusing qualitative differences instead of merely quantitative measures in job‐search behaviour. And even more important, despite attitude and job‐search behaviour, there is still differences that seems to be related to gender and family responsibility.     

Why are unemployed aged fifty and over less likely to find a job? A decomposition analysis

Reemployment chances for unemployed aged fifty and over are low compared to those of younger persons. To explain the different chances, the job search literature has largely focused on the job search behavior of unemployed individuals. Based on job search models, we propose that not only job search behavior, but also wage setting behavior, attitudinal variables and personal variables impact the difference in reemployment opportunities. Besides gaining insight into which variables explain the difference in reemployment opportunities, we also test how much of the difference each of these variables explains. We do this by drawing on a decomposition analysis. Using data from 647 recently unemployed, we find that about one third of the reemployment gap can be explained by the variables suggested by job search models, mostly in terms of age differences in search behavior, educational levels and reservation wage. Hence, about 70 % can be ascribed to other factors, such as employer preferences for those aged between 18 and 49. Implications of these results for theory, policy and practice are discussed.