23 research outputs found

    Context modulation of learned attention deployment

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    In three experiments, we investigated the contextual control of attention in human discrimination learning. In each experiment, participants initially received discrimination training in which the cues from Dimension A were relevant in Context 1 but irrelevant in Context 2, whereas the cues from Dimension B were irrelevant in Context 1 but relevant in Context 2. In Experiment 1, the same cues from each dimension were used in Contexts 1 and 2, whereas in Experiments 2 and 3, the cues from each dimension were changed across contexts. In each experiment, participants were subsequently shifted to a transfer discrimination involving novel cues from either dimension, to assess the contextual control of attention. In Experiment 1, measures of eye gaze during the transfer discrimination revealed that Dimension A received more attention than Dimension B in Context 1, whereas the reverse occurred in Context 2. Corresponding results indicating the contextual control of attention were found in Experiments 2 and 3, in which we used the speed of learning (associability) as an indirect marker of learned attentional changes. Implications of our results for current theories of learning and attention are discussed

    A test for a difference in the associability of blocked and uninformative cues in human predictive learning

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    In human predictive learning, blocking, A+ AB+, and a simple discrimination, UX+ VX–, result in a stronger response to the blocked, B, than the uninformative cue, X (where letters represent cues and + and – represent different outcomes). To assess whether these different treatments result in more attention being paid to blocked than uninformative cues, Stage 1 in each of three experiments generated two blocked cues, B and E, and two uninformative cues, X and Y. In Stage 2, participants received two simple discriminations: either BX+ EX– and BY+ EY–, or BX+ BY– and EX+ EY–. If more attention is paid to blocked than uninformative cues, then the first pair of discriminations will be solved more readily than the second pair. In contrast to this prediction, both discriminations were acquired at the same rate. These results are explained by the theory of Mackintosh, by virtue of the assumption that learning is governed by an individual rather than a common error term

    Attentional Bias for Uncertain Cues of Shock in Human Fear Conditioning: Evidence for Attentional Learning Theory

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    Eye tracking data and statistical analysis of: Koenig, S., Uengoer, M., & Lachnit, H. (2017). Attentional bias for uncertain cues of shock in human fear conditioning: Evidence for attentional learning theory. Frontiers in Human Neuroscience. doi: 10.3389/fnhum.2017.00266. Abstract: We conducted a human fear conditioning experiment in which three different color cues were followed by an aversive electric shock on 0, 50, and 100% of the trials, and thus induced low (L), partial (P), and high (H) shock expectancy respectively. The cues differed with respect to the strength of their shock association (L < P < H) and the uncertainty of their prediction (L < P > H). During conditioning we measured pupil dilation and ocular fixations to index differences in the attentional processing of the cues. After conditioning, the shock-associated colors were introduced as irrelevant distracters during visual search for a shape target while shocks were no longer administered and we analyzed the cues’ potential to capture and hold overt attention automatically. Our findings suggest that fear conditioning creates an automatic attention bias for the conditioned cues that depends on their correlation with the aversive outcome. This bias was exclusively linked to the strength of the cues’ shock association for the early attentional processing of cues in the visual periphery, but additionally was influenced by the uncertainty of the shock prediction after participants fixated on the cues. These findings are in accord with attentional learning theories that formalize how associative learning shapes automatic attention

    Reminder cues modulate the renewal effect in human predictive learning

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    Associative learning refers to our ability to learn about regularities in our environment. When a stimulus is repeatedly followed by a specific outcome, we learn to expect the outcome in the presence of the stimulus. We are also able to modify established expectations in the face of disconfirming information (the stimulus is no longer followed by the outcome). Both the change of environmental regularities and the related processes of adaptation are referred to as extinction. However, extinction does not erase the initially acquired expectations. For instance, following successful extinction, the initially learned expectations can recover when there is a context change – a phenomenon called the renewal effect, which is considered as a model for relapse after exposure therapy. Renewal was found to be modulated by reminder cues of acquisition and extinction. However, the mechanisms underlying the effectiveness of reminder cues are not well understood. The aim of the present study was to investigate the impact of reminder cues on renewal in the field of human predictive learning. Experiment I demonstrated that renewal in human predictive learning is modulated by cues related to acquisition or extinction. Initially, participants received pairings of a stimulus and an outcome in one context. These stimulus-outcome pairings were preceded by presentations of a reminder cue (acquisition cue). Then, participants received extinction in a different context in which presentations of the stimulus were no longer followed by the outcome. These extinction trials were preceded by a second reminder cue (extinction cue). During a final phase conducted in a third context, participants showed stronger expectations of the outcome in the presence of the stimulus when testing was accompanied by the acquisition cue compared to the extinction cue. Experiment II tested an explanation of the reminder cue effect in terms of simple cue-outcome associations. Therefore, acquisition and extinction cues were equated for their associative histories in Experiment II, which should abolish their impact on renewal if based on simple cue-outcome associations. In contrast to this prediction, Experiment II replicated the findings from Experiment I indicating that the effectivenes of reminder cues did not require direct reminder cue-outcome associations

    You see what you have learned. Evidence for an inter-relation of associative learning and visual selective attention

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    Besides visual salience and observers' current intention, prior learning experience may influence deployment of visual attention. Associative learning models postulate that observers pay more attention to stimuli previously experienced as reliable predictors of specific outcomes. To investigate the impact of learning experience on deployment of attention, we combined an associative learning task with a visual search task and measured event-related potentials of the EEG as neural markers of attention deployment. In the learning task, participants categorized stimuli varying in color/shape with only one dimension being predictive of category membership. In the search task, participants searched a shape target while disregarding irrelevant color distractors. Behavioral results showed that color distractors impaired performance to a greater degree when color rather than shape was predictive in the learning task. Neurophysiological results show that the amplified distraction was due to differential attention deployment (N2pc). Experiment 2 showed that when color was predictive for learning, color distractors captured more attention in the search task (ND component) and more suppression of color distractor was required (PD component). The present results thus demonstrate that priority in visual attention is biased toward predictive stimuli, which allows learning experience to shape selection. We also show that learning experience can overrule strong top-down control (blocked tasks, Experiment 3) and that learning experience has a longer-term effect on attention deployment (tasks on two successive days, Experiment 4).<br/

    The fate of redundant cues in human predictive learning

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    In each of three experiments, a single group of participants received a sequence of trials involving pictures of a variety of foods presented individually or in pairs. Participants were required to predict in which trials the food would lead to a hypothetical allergic reaction. The different trials involved blocking, A+ AX+, and a simple discrimination, BY– CY+, in which each letter stands for a different food. Training trials were followed by a test in which participants were asked to predict how likely each kind of food would be followed by the allergic reaction. The principal purpose of the experiments was to determine how the redundant cue from blocking, X, would be judged relative to the redundant cue from the simple discrimination, Y. In contrast to predictions from currently influential theories of associative learning, X was regarded as a better predictor for the allergic reaction than Y

    Reward Draws the Eye, Uncertainty Holds the Eye: Associative Learning Modulates Distractor Interference in Visual Search

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    Stimuli in our sensory environment differ with respect to their physical salience but moreover may acquire motivational salience by association with reward. If we repeatedly observed that reward is available in the context of a particular cue but absent in the context of another cue the former typically attracts more attention than the latter. However, we also may encounter cues uncorrelated with reward. A cue with 50% reward contingency may induce an average reward expectancy but at the same time induces high reward uncertainty. In the current experiment we examined how both values, reward expectancy and uncertainty, affected overt attention. Two different colors were established as predictive cues for low reward and high reward respectively. A third color was followed by high reward on 50% of the trials and thus induced uncertainty. Colors then were introduced as distractors during search for a shape target, and we examined the relative potential of the color distractors to capture and hold the first fixation. We observed that capture frequency corresponded to reward expectancy while capture duration corresponded to uncertainty. The results may suggest that within trial reward expectancy is represented at an earlier time window than uncertainty

    Contextual control of attentional allocation in human discrimination learning

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    In 3 human predictive learning experiments, we investigated whether the allocation of attention can come under the control of contextual stimuli. In each experiment, participants initially received a conditional discrimination for which one set of cues was trained as relevant in Context 1 and irrelevant in Context 2, and another set was relevant in Context 2 and irrelevant in Context 1. For Experiments 1 and 2, we observed that a second discrimination based on cues that had previously been trained as relevant in Context 1 during the conditional discrimination was acquired more rapidly in Context 1 than in Context 2. Experiment 3 revealed a similar outcome when new stimuli from the original dimensions were used in the test stage. Our results support the view that the associability of a stimulus can be controlled by the stimuli that accompany it

    An exploration of the feature-positive effect in adult humans

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    Experiment 1 compared the acquisition of a feature-positive and a feature-negative discrimination in humans. In the former, an outcome was signaled by two stimuli together, but not by one of these stimuli alone. In the latter, the outcome was signaled by one stimulus alone, but not by two stimuli together. Using a within-group design, the experiment revealed that the feature-positive discrimination was acquired more readily than the feature-negative discrimination. Experiment 2 tested an explanation for these results, based on the Rescorla–Wagner theory, by examining how novel discriminations, based on a combination of a feature-positive and a feature-negative discrimination, were solved. The results did not accord with predictions from the theory. Alternative explanations for the results are considered
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