This thesis consists of five main chapters including three independent studies, focusing on reward-based distractor interference and reward-association. In particular, the thesis addresses at which attentional processing stages the reward-based distractor interference takes place, as well as whether and how the reward association is learned on different levels. In the first chapter, I introduced a general background of attention, associative learning, and relations between reward associative learning and attention. In the end, I highlighted the open issues that this thesis aimed (...) to address. Chapter II aimed to answer the question at which processing stage the reward-based distractor interferes with the ongoing task. The study adopted the visual additional singleton search task but extended it to visual-tactile search. A classical finding of the reward-based distractor interference is that a reward-associated color feature, which appears as a task-irrelevant distractor, albeit it is not salient, captures attention and impedes task-relevant response. However, it is unclear at which attentional processing stage the reward-driven capture effects occur. To identify the distractor interference at the pre-attentional searching stage or post/focal- attentional decision-making stage, three experiments were conducted. Instead of a circular search display used in a standard attentional capture paradigm, this study used a horizontal search display to maximize potential attentional capture and disengagement. The results revealed that the reward-based distractor interference was only observed when the target and reward-based distractor were on the same side, indicating the interference likely occurred at the post/focal- attentional decision-making stage. To confirm this, Experiments 2 and 3 adopted the crossmodal search paradigm, in which the search stage and post-selective identification stage took place in different modalities. Such design enabled us to distinguish whether the interference effect occurs at the searching stage or the post/focal-attentional decision-making stage. The results further corroborated that the reward-driven capture effects occur at the post/focal-attention stage. Chapter III focused on the question related to the level of reward associative learning. Most previous studies on reward-based attentional capture implicitly used feature-based reward association, particularly on the feature level, e.g., color-reward association. This leaves the question open regarding whether the associative reward could be established at the level of response mapping or task-set mapping. Two experiments were designed to address this question. In Experiment 1, high/low rewards were associated with both the two colors and the left/right response in the training phase, and the reward-associated color became one of the task-irrelevant distractors in the test phase. We failed to find any evidence on the reward-response association. However, the results showed the distractor with previously reward-associated features facilitated search, indicating a better distractor handling in the test phase. In Experiment 2, the reward was associated with task-sets in the training phase and the task-sets kept the same in the test phase, while the search task was changed. The results suggested that reward-associated learning facilitated distractor handling and task-set learning. Chapter IV tackled the open research question - whether reward associative learning could take place at the multi-conjunction level. The question is important, given that previous studies on reward-based attentional capture only investigated associative learning of a single feature. As reward association in daily life is usually complex, Study 3 aims to explore whether reward learning can be established through reward assignments with conjunction features and whether the interference of distractors with previously reward-associated features can be observed in a similar way as previous studies shown on single-feature-based reward-driven capture effects. Reward learning was found locally trial-by-trial throughout the whole learning process, however, it was hard to establish a reliable conjunction reward association. Furthermore, there was no reward-based distractor interference in the test phase. The findings suggest that conjunction reward-association is difficult, though a short-lived trial-to-trial conjunction reward learning can be established. The final Chapter V discussed the findings of these three studies and their inter-relations. And I summarized how these findings could contribute to the debate of reward-based distractor interference. In summary, this thesis helps to improve our knowledge about reward-based distractor interference, particularly on the identification of the processing stage of distractor interference and what can be associated with reward in reward associative learning. (shrink)

Observers can learn the locations where salient distractors appear frequently to reduce potential interference. The effect that observers appear to learn the spatial distribution of salient but task-irrelevant distractors in the visual environment to reduce the interference caused by such distractors was referred to as ‘statistical learning of distractor locations’. Emerging studies agreed that the observed reduction of distractor interference is largely attributable to better suppression of distractor in frequent locations, however, concerning how this spatial distractor suppression is implemented within (...) the functional architecture of search guidance, and how the learned suppression is processed in the brain to reduce the interference, remains debated and poorly understood. The line of studies of the current dissertation, therefore, explores the cognitive and neural mechanism underlying spatial distractor suppression based on statistical learning. Using psychophysical experiments, the first two studies examined a series of potentially ‘confounding’ factors that might lead to different theoretical conclusions concerning the locus of learned spatial distractor suppression in different studies. We found that irrespective of whether a salient singleton distractor is more likely to occur at multiple locations within a subregion of the display or at a specific location, observers are both likely to adopt the priority-map-based suppression strategy and dimension-based suppression strategy to reduce interference of distractor in the frequent region. Notably, a critical factor determining which strategy is adopted is whether the distractor and non-distractor items swap colors randomly across trials: without color swapping, observers are more likely to acquire a dimension-based suppression; with color swapping, they prefer to develop a priority-map-based suppression in the first beginning, and potentially shift to dimension-based suppression later with the course of learning. The third study employed functional magnetic resonance imaging techniques with the distractor-location learning paradigm with two types of distractors defined in either the same- or different- visual dimension relative to the target. We disclosed that statistical learning of distractor locations involves suppression down to the level of the early visual cortex to reduce distractor interference, potential different neural mechanisms of spatial distractor suppression between distractors defined in a different and the same dimension to the target. With different-dimension distractors, higher-level, dimension-specific filtering mechanisms plays a role to reduce the interference; with same-dimension distractors, interference reduction relies on cutting down lower-level sensory signals. (shrink)