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)

Food uncertainty has the effect of invigorating food-related responses. Psychologists have noted that mammals and birds respond more to a conditioned stimulus that unreliably predicts food delivery, and ecologists have shown that animals consume and/or hoard more food and can get fatter when access to that resource is unpredictable. Are these phenomena related? We think they are. Psychologists have proposed several mechanistic interpretations, while ecologists have suggested a functional interpretation: The effect of unpredictability on fat reserves and hoarding behavior is (...) an evolutionary strategy acting against the risk of starvation when food is in short supply. Both perspectives are complementary, and we argue that the psychology of incentive motivational processes can shed some light on the causal mechanisms leading animals to seek and consume more food under uncertainty in the wild. Our theoretical approach is in agreement with neuroscientific data relating to the role of dopamine, a neurotransmitter strongly involved in incentive motivation, and its plausibility has received some explanatory and predictive value with respect to Pavlovian phenomena. Overall, we argue that the occasional and unavoidable absence of food rewards has motivational effects that facilitate foraging effort. We show that this hypothesis is computationally tenable, leading foragers in an unpredictable environment to consume more food items and to have higher long-term energy storage than foragers in a predictable environment. (shrink)

A motivational system approach to avoidance behavior is presented. According to this approach, a motivational state increases the probability of relevant response patterns and establishes the appropriate or “ideal” consummatory stimuli as positive reinforcers. In the case of feeding motivation, for example, hungry rats are likely to explore and gnaw, and to learn to persist in activities correlated with the reception of consummatory stimuli produced by ingestion of palatable substances. In the case of defense motivation, fearful rats are likely to (...) flee or freeze, and to learn to persist in activities correlated with consummatory stimuli produced by flight from a dangerous place. Defense system activation is distinct from alarm reactions. The latter prepare the animal for probable noxious events, involve relatively intense negative affect and extinguish rapidly in situations where the noxious event no longer occurs. In contrast, defense system activation potentiates innate and modified defense reactions, thus preparing the animal for possible, but not necessarily probable, noxious events; it involves little or no negative affect and extinguishes very slowly when the noxious event no longer occurs. With these assumptions and the resulting model we attempt to resolve several long-standing problems in avoidance learning, including the low correlation between negative affect and avoidance performance, differential rates of extinction for avoidance performance and conditioned emotional responses, and evidence that some avoidance responses are much more easily learned than others. In addition, the model has implications for the study of parallels between appetitive and aversive motivation, sign tracking in aversive conditioning, and orientation of flight responses. Historical antecedents and alternative approaches are discussed. (shrink)

Converging data from different disciplines are showing the role of classical conditioning processes in the elaboration of human and animal behavior to be larger than previously supposed. Restricted views of classically conditioned responses as merely secretory, reflexive, or emotional are giving way to a broader conception that includes problem-solving, and other rule-governed behavior thought to be the exclusive province of either operant conditiońing or cognitive psychology. These new views have been accompanied by changes in the way conditioning is conducted and (...) evaluated. Data from a number of seemingly unrelated phenomena such as relapse to drug abuse by postaddicts, the placebo effect, and the immune response appear to involve classical conditioning processes. Classical conditioning, moreover, has been found to occur in simpler and simpler organisms and recently even demonstrated in brain slices and in utero. This target article will integrate the several research areas that have used the classical conditioning process as an explanatory model; it will challenge teleological interpretations of the classically conditioned CR and offer some basic principles for testing conditioning in diverse areas. (shrink)

Despite the fact that the role of learning is recognised in empirical and theoretical work on sense of agency , the nature of this learning has, rather surprisingly, received little attention. In the present study we consider the contribution of associative mechanisms to SoA. SoA can be measured quantitatively as a temporal linkage between voluntary actions and their external effects. Using an outcome blocking procedure, it was shown that training action–outcome associations under conditions of increased surprise augmented this temporal linkage. (...) Moreover, these effects of surprise were correlated with schizotypy scores, suggesting that individual differences in higher level experiences are related to associative learning and to its impact on SoA. These results are discussed in terms of models of SoA, and our understanding of disrupted SoA in certain disorders. (shrink)

Symbols enable people to organize and communicate about the world. However, the ways in which symbolic knowledge is learned and then represented in the mind are poorly understood. We present a formal analysis of symbolic learning—in particular, word learning—in terms of prediction and cue competition, and we consider two possible ways in which symbols might be learned: by learning to predict a label from the features of objects and events in the world, and by learning to predict features from a (...) label. This analysis predicts significant differences in symbolic learning depending on the sequencing of objects and labels. We report a computational simulation and two human experiments that confirm these differences, revealing the existence of Feature-Label-Ordering effects in learning. Discrimination learning is facilitated when objects predict labels, but not when labels predict objects. Our results and analysis suggest that the semantic categories people use to understand and communicate about the world can only be learned if labels are predicted from objects. We discuss the implications of this for our understanding of the nature of language and symbolic thought, and in particular, for theories of reference. (shrink)

The past 50 years have seen an accumulation of evidence suggesting that associative learning depends on high-level cognitive processes that give rise to propositional knowledge. Yet, many learning theorists maintain a belief in a learning mechanism in which links between mental representations are formed automatically. We characterize and highlight the differences between the propositional and link approaches, and review the relevant empirical evidence. We conclude that learning is the consequence of propositional reasoning processes that cooperate with the unconscious processes involved (...) in memory retrieval and perception. We argue that this new conceptual framework allows many of the important recent advances in associative learning research to be retained, but recast in a model that provides a firmer foundation for both immediate application and future research. (shrink)

An attentional-associative model (Schmajuk et al. 1996), previously evaluated against multiple sets of classical conditioning data, is applied to causal learning. In agreement with Mitchell et al.'s suggestion, according to the model associative learning can be a conscious, controlled process. However, whereas our model correctly predicts blocking following or preceding subadditive training, the propositional approach cannot account for those results.

To make behavioral choices that are in line with our goals and our moral beliefs, we need to gather and consider information about our current situation. Most information present in our environment is not relevant to the choices we need or would want to make and thus could interfere with our ability to behave in ways that reflect our underlying values. Certain sources of information could even lead us to make choices we later regret, and thus it would be beneficial (...) to be able to ignore that information. Our ability to exert successful self-governance depends on our ability to attend to sources of information that we deem important to our decision-making processes. We generally assume that, at any moment, we have the ability to choose what we pay attention to. However, recent research indicates that what we pay attention to is influenced by our prior experiences, including reward history and past successes and failures, even when we are not aware of this history. Even momentary distractions can cause us to miss or discount information that should have a greater influence on our decisions given our values. Such biases in attention thus raise questions about the degree to which the choices that we make may be poorly informed and not truly reflect our ability to otherwise exert self-governance. (shrink)

Pavlovian cues predict the occurrence of motivationally salient outcomes, thus serving as an important trigger of approach and avoidance behavior. The amygdala is a key substrate of Pavlovian conditioning, and the nature of its contribution varies by the motivational valence of unconditioned stimuli. The literature on aversive Pavlovian learning supports a serial-processing model of amygdalar function, while appetitive studies suggest that Pavlovian associations are processed through parallel circuits in the amygdala. It is proposed that serial and parallel forms of information (...) processing can be attributed to differential recruitment of amygdalar nuclei, with emphasis placed on the lateral amygdala. (shrink)

It is nearly 10 years since Patrick Haggard and colleagues first reported the ‘intentional binding’ effect . The intentional binding effect refers to the subjective compression of the temporal interval between a voluntary action and its external sensory consequence. Since the first report, considerable interest has been generated and a fascinating array of studies has accumulated. Much of the interest in intentional binding comes from the promise to shed light on human agency. In this review we survey studies on intentional (...) binding, focusing, in particular, on the link between intentional binding and the sense of agency . We suggest that, whilst it is yet to be fully explicated, the link between intentional binding and the sense of agency is compelling. We conclude by considering outstanding questions and future directions for research on intentional binding. (shrink)