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Impact of relative and absolute values on selective attention
Abstract
Valuable stimuli receive attentional priority. However, it is unknown whether the mechanism of the attentional priority is based on relative (e.g., higher) or absolute (e.g., 45 points) values. Therefore, we manipulated the relative and absolute values independently in a modified value-driven attentional capture paradigm. In the training phase, where associative learning occurs between color and reward value, two test target colors were each presented with another different target color (reference target colors) in separate context blocks. Therefore, each test target color had different reference points. In the test phase, the two test target colors were used as singleton distractor colors. In the training phase of Experiment 1, the absolute reward value of the test target colors was the same, but one had a higher value than its reference target color and the other had a lower value. In the test phase, the high relative value color distractor captured attention more, suggesting that the relative value of stimuli influenced selective attention. In Experiment 2 the relative value of the test target colors was the same, but the absolute value was higher for one. The high and low absolute value color distractors captured attention equally in the test phase, indicating little impact of the absolute value on selective attention. These findings suggest that the relative value, rather than absolute value, plays a critical role in the allocation of attention. Accordingly, the present study suggests that prospect theory (Kahneman & Tversky, Econometrica, 47 (2), 363-391, 1979) can be extended to earlier cognitive stages such as selective attention.
... In line with this, previous studies demonstrated that attentional control reflects the reference dependence and diminishing sensitivity principles of prospect theory. Kim and Beck (2020) found evidence of reference dependence in attention. A 50-point item that was compared with a 1-point item attracted more attention than a 50-point item that was compared with a 100-point item, suggesting that relative value (higher or lower), not absolute value (50 points), influences attentional allocation to items. ...
... Method Participants Forty participants with normal or corrected-tonormal visual acuity and color vision participated in Experiment 1 for payment of KRW 7,000 (about US$6). To determine the effect size, we looked to the Kim and Beck (2020) study, which had an effect size of 0.30. The present study was assumed to have a higher effect size than Kim and Beck (2020), given more direct measures in attentional selection in the present study. ...
... To determine the effect size, we looked to the Kim and Beck (2020) study, which had an effect size of 0.30. The present study was assumed to have a higher effect size than Kim and Beck (2020), given more direct measures in attentional selection in the present study. Therefore, we ran the G-power test with a power of 0.85, an alpha of 0.05, and an effect size of 0.5, and found a minimum sample size of 38. ...
Loss aversion is a psychological bias where an increase in loss is perceived as being larger than an equivalent increase in gain. In the present study, two experiments were conducted to explore whether attentional control reflects loss aversion. Participants performed a visual search task. On each trial, a red target and a green target were presented simultaneously, and participants were free to search for either one. Participants always gained points when they searched for a gain color target (e.g., red). However, they gained or lost points when they searched for a gain-loss color target (e.g., green). In Experiment 1, the expected values of the gain color and the gain-loss color were equal. Therefore, for maximizing the reward, participants did not need to preferably search for a particular color. However, results showed that participants searched for the gain color target more than the gain-loss color target, suggesting stronger attentional control for the gain color than the gain-loss color. In Experiment 2, even though the expected value of the gain-loss color was greater than that of the gain color, attention was allocated to the gain color more than to the gain-loss color. The results imply that attentional control can operate in accordance with the loss aversion principle when the boundary conditions for loss aversion in a repeated binary decision-making task were met.
... Commonly, attention processes can be either stimulus-driven or goal-driven (20)(21)(22). As a more stimulus-driven process, patients' visiting is expected to increase with an increase of physician information sharing since patients' attention could be captured by topics of interest in health articles (12,23). However, patients' reading is a more goal-driven process where information overload dampens patients' attention to physicians' articles (24). ...
... It thus offers a visualized framework to enhance the understanding of how physician online information sharing provokes potential patient education by patients' visiting and realized patient education by patients' reading. According to attention theory, patients' visiting is similar to a stimulus-driven attention process, and the information sharing by physicians may initiate potential patient education as patients' attention could be captured by contents of interest in shared health articles (12,23). However, patients' reading is a goal-driven process where the patients' information decision is the trade-off between the benefits and the costs of attention, and information overload dampens patients' attention to physicians' articles (24). ...
... Physicians with higher clinic titles are regarded as experts in their medical field, and their articles are perceived as more rewarding to patients (55,56). Valuable information receives attentional priority, and once the shared information enters patients' browsing range, it draws the patients' attention (23). Further, physicians with higher professional titles are more likely to obtain active goal-driven attention from patients because patients tend to choose medical services from highertitled physicians, and are thus inclined to seek health knowledge shared by them as well (1,29). ...
Aims
With the development of information technology, online health platforms and physician online information sharing play an important role in public health management and patient education. Is physician online information sharing always beneficial to patient education? From the attention perspective, this study aims to explore how physician online information sharing influences patient education, considering the contingent roles of physician online reputation and offline expertise.
Methods
A 6-month panel data of 61,566 physician-month observations from an online health platform in China was used to tested the proposed hypotheses. Considering the inefficiency and estimated bias of the ordinary least squares regression model, this study conducted the fixed models to test the direct and moderating effects.
Results
The results indicate that physician online information sharing is positively related to potential patient education, while the relationship between physician online information sharing and realized patient education is an inverted U-shape. Physician online reputation enhances the positive relationship between physician online information sharing and potential patient education, but physician offline expertise weakens the abovementioned relationship. In addition, physician offline expertise flattens the curvilinear effect of physician online information sharing on realized patient education.
Conclusion
This study contributes to the literature about attention theory and information sharing for patient education, and provides implications for practice.
... shows that attention is attracted based on relative value rather than absolute value (Kim & Beck 2020b). The present study expands on this previous work by investigating whether when a valuable item attracts attention, the value of the item is distorted on the basis of the diminishing sensitivity principle of prospect theory (Kahneman & Tversky, 1979). ...
... These allude to the extendibility of reference dependence and diminishing sensitivity to selective attention. In line with this, Kim and Beck (2020b) demonstrated that the reference dependence principle of prospect theory is present in selective attention. In the current study, we expand on this previous research to show that diminishing sensitivity is also present in selective attention. ...
... That is, prospect theory suggests that relative value (high or low compared with a reference point), not absolute value ($10), is critical to perceived value. Kim and Beck (2020b) demonstrated that reference dependence operates in selective attention by applying the reference dependence principle to value-driven attention. Value-driven attention (Anderson et al., 2011;Bucker & Theeuwes, 2017;Chelazzi, Perlato, Santandrea, & Della Libera, 2013;Della Libera & Chelazzi, 2009;Hickey, Chelazzi, & Theeuwes, 2010;Le Pelley, Pearson, Porter, Yee, & Luque, 2019;Mine & Saiki, 2015;Roper, Vecera, & Vaidya, 2014) suggests that more valuable stimuli are attended more. ...
Kim and Beck (2020b) demonstrated that value-driven attention is based on relative value rather than absolute value, suggesting that prospect theory is relevant to our understanding of value-driven attention. To further this understanding, the present study investigated the impacts of diminishing sensitivity on value-driven attention. According to diminishing sensitivity, changes in outcomes have greater impacts nearer the reference point of 0 than farther from the point. Thus, the difference between 100 looms larger than that between 1000, due to their different ratios (100/1 > 1000/901). However, according to the absolute difference hypothesis, the differences should have similar impacts due to the absolute differences being the same (100 - 1 = 1000 - 901). Experiment 1 investigated whether diminishing sensitivity operates in the modified value-driven attention paradigm while controlling the impact of absolute differences. In the training phase, 100-point and 1000-point color targets had references of 1-point and 901-point color targets, respectively. In the test phase, 100-point color distractors attracted attention more than 1000-point color distractors, supporting the diminishing sensitivity hypothesis. Experiment 2 examined the absolute difference hypothesis while controlling the impact of diminishing sensitivity. Contrary to the absolute difference hypothesis, the test phase showed that 1000-point color distractors (compared with 10-point colors for a 990 absolute difference in the training phase) failed to attract attention more than 100-point color distractors (compared with 1-point colors, for a 99 absolute difference). These results suggest that diminishing sensitivity rather than absolute difference influences value-driven attention, further supporting the relevance of prospect theory to value-driven attention.
... Prospect theory (Kahneman & Tversky, 1979) suggests that relative rather than absolute values influence behaviors in later cognitive stages such as judgement and decision making. Kim and Beck (2020) extended the Prospect theory to earlier cognitive stages (i.e., selective attention). Specifically, the distractor with high relative value captured attention more than that with low relative value even when their absolute value was the same. ...
... Namely, although we strengthened the intensity of the competitive reward structure by using 100 points in Experiment 3, there was no significant difference in the magnitude of temporal cue validity effect between receiving 10 points (Experiment 1) and 100 points (Experiment 3) compared to receiving the same reference point (i.e., 1 point). These findings extend the Prospect Theory in the spatial domain (Kim & Beck, 2020) to the temporal domain, whereby the relative (e.g., higher or lower) rather than the absolute (e.g., 10 or 100 points) value determines the allocation of attention in time. ...
Reward has been known to render the reward-associated stimulus more salient to block effective attentional orienting in space. However, whether and how reward influences goal-directed attention in time remains unclear. Here, we used a modified attentional cueing paradigm to explore the effect of reward on temporal attention, in which the valid targets were given a low monetary reward and invalid targets were given a high monetary reward. The results showed that the temporal cue validity effect was significantly smaller when the competitive reward structure was employed (Experiment 1), and we ruled out the possibility that the results were due to the practice effect (Experiment 2a) or a reward-promoting effect (Experiment 2b). When further strengthening the intensity of the reward from 1:10 to 1:100 (Experiment 3), we found a similar pattern of results to those in Experiment 1. These results suggest that reward information which was based on relative instead of absolute values can weaken, but not reverse, the orienting attention in time.
... Our extinction procedure may resemble the idea of 'successive negative contrasts' (Phelps et al., 2015). We believe this approach may be better suited to test the extinction of VMAC, given that what participants learn is that the distractor is relatively more valuable than others (Kim & Beck, 2020). This procedure more closely mirrors that of Pavlovian extinction, where only the relationship between the cue and reward for the to-be-extinguished stimulus is usually modified, leaving the rest of the stimuli unaffected. ...
Particular features of the stimuli that predict significant outcomes tend to capture our attention in a rather automatic and inflexible way. This form of attention has been described as a Pavlovian bias that mimics the phenomenon of sign-tracking described in animals, where reward-predictive cues become motivational magnets. In humans, Value-Modulated Attentional Capture (VMAC) refers to a phenomenon where distractors that signal high-value outcomes receive higher attentional priority. VMAC is particularly difficult to extinguish, showing a similar persistence often described in animal sign-tracking. In the present study, we evaluated to what extent VMAC would persist using a more specific extinction procedure than previous research, where instead of removing the possibility of obtaining rewards, the different discriminant stimuli that signal reward equate its value. Furthermore, we manipulated between experiments whether the high-value distractor predicted high-reward and high-punishment contingent to response accuracy (mimicking previous research; Experiment 1) or only high-reward (Experiment 2), and also explored the association of VMAC and its persistence with measures of emotional impulsivity employed in past research. Our results show that when both rewards and punishments are possible, VMAC does not extinguish after an extensive extinction stage, nor is it associated with measures of emotional impulsivity. When punishments were removed, we showed that VMAC gradually extinguished both in response times and accuracy and that the persistence of VMAC was significantly associated with positive urgency. We discussed these results on the potential of punishments to qualitatively alter learning and response strategies employed by participants.
... All practice trials were excluded from analyses. We calculated anticipations (RTs < 150 ms) and timeouts (RTs > 1500 ms), and as per typical processing conventions (Hayward et al., 2018;Kim & Beck, 2020;Landry et al., 2022), any participants who committed more than 10% timing errors or had poor accuracy performance (less than 50% accuracy to report the presence or absence of the target) were removed from all analyses. The cooperation mode consisted of 108 participants (Social Presence: visually absent, n = 29; schematic face, n = 26; real face, n = 27; confederate, n = 26), the competition mode consisted of 107 participants (Social Presence: visually absent, n = 27; schematic face, n = 26; real face, n = 29; confederate, n = 25), and the control conditions consisted of 51 participants (points: n = 26; baseline: n = 25; anonymized summary data can be found here: https:// osf.io/283bt/). ...
... riven band activity, on the other hand, is subject to control by top-down attention (Gray et al., 2015;20 Haegens & Zion Golumbic, 2018;Y. J. Kim et al., 2007) and, as shown in our study, modulated by VDAC. Habitual biases of VDAC appear more driven by the updating involved in the computation of relative value and its consolidation (Anderson, 2019;S. Kim & Beck, 2020;Liao & Anderson, 2020) rather than amplifying sensory features that signal value . In addition, the redress by VDAC may involve object-selective cortical 25 processing areas Hickey & Peelen, 2015), with the encoding of relative value in object-based representations (Stănişor et al., 2013). In this way, endogenous band activity correspond ...
By linking with rewards, sensory signals gain salience and the ability to influence selective attention even when they have become irrelevant. The dynamics of reward-driven distraction in the brain remains unclear, particularly at the time of shaping multisensory associations. It is unknown whether reward-driven distraction by visual signals interferes with the robust ability of the brain to phase-lock to auditory modulations. In a dynamic audiovisual (AV) coherence task, we investigated how visual reward associations affect performance and modulate auditory encoding precision. Participants were presented with dual visual object streams flickering at different rates, accompanied by an amplitude-modulated sound matching one of the flicker periods, for subjects to identify the matching visual object. At the periphery, an irrelevant color feature flickers in sync with the target and may capture observers' attention, due to a prior color-reward association training regime. Electroencephalography (EEG) recordings assessed participants' sensitivity to the audiovisual task. The findings indicate that target discrimination was impoverished in the presence of colors that had previously been associated with reward. The phase locking of auditory responses also decreased, evidencing an attentional shift away from auditory modulation representations. Moreover, down-modulations of auditory phase locking predicted the effect size of participants' reward-driven distraction. These findings highlight how value-driven attentional capture fundamentally alters multimodal processing in the temporal domain. They suggest that less precise neural representations of unisensory streams not connected to reward-associated cues undermine the processing of temporal coherence relationships between multisensory streams. Momentary inter-modal competition, induced by reward-driven distraction, appears consistent with the systematic exploit of gaps in active attentional sampling strategies that unfold over time.
... and are the attention distribution coefficients, which represent the attention weights assigned to the non-zero thermal reference point and the target thermal environment, respectively. These coefficients are derived from well-established principles in cognitive psychology: valuable stimuli receive attentional priority [58][59][60], and attention amplifies subjective value [56,61]. ...
... The range of absolute values for fribbles also differed between conditions. However, the relative value of fribbles within choices, the most important factor in binary choice behavior, Kim and Beck (2020) was similar across conditions. While participants were instructed to 'add up' the learned values of individual attributes in the elemental trials, they could have adopted other attribute-based strategies including shortcuts such as a 'take Estimates rates from the model for between-object transitions across conditions (model output). ...
Introduction
While many everyday choices are between multi-attribute options, how attribute values are integrated to allow such choices remains unclear. Recent findings suggest a distinction between elemental (attribute-by-attribute) and configural (holistic) evaluation of multi-attribute options, with different neural substrates. Here, we asked if there are behavioral or gaze pattern differences between these putatively distinct modes of multi-attribute decision-making.
Methods
Thirty-nine healthy men and women learned the monetary values of novel multi-attribute pseudo-objects (fribbles) and then made choices between pairs of these objects while eye movements were tracked. Value was associated with individual attributes in the elemental condition, and with unique combinations of attributes in the configural condition. Choice, reaction time, gaze fixation time on options and individual attributes, and within- and between-option gaze transitions were recorded.
Results
There were systematic behavioral differences between elemental and configural conditions. Elemental trials had longer reaction times and more between-option transitions, while configural trials had more within-option transitions. The effect of last fixation on choice was more pronounced in the configural condition.
Discussion
We observed differences in gaze patterns and the influence of last fixation location on choice in multi-attribute value-based choices depending on how value is associated with those attributes. This adds support for the claim that multi-attribute option values may emerge either elementally or holistically, reminiscent of similar distinctions in multi-attribute object recognition. This may be important to consider in neuroeconomics research that involve visually-presented complex objects.
... Most previous studies using the classical VDAC paradigm failed to observe a statistical difference in behavioral performances between the target types in the training phase (Anderson & Halpern, 2017;Kim & Beck, 2020;Miranda & Palmer, 2014;Roper & Vecera, 2016). These results are possibly due to a ceiling/floor effect: while reward feedback allowed participants to adequately form stimulus-reward associations, top-down attentional control may have modulated the visual search for the two target colors by assigning equal priority , as the reward itself was irrelevant to identifying the line orientation within the target circles. ...
Value-driven attentional capture (VDAC) refers to a phenomenon by which stimulus features associated with greater reward value attract more attention than those associated with smaller reward value. To date, the majority of VDAC research has revealed that the relationship between reward history and attentional allocation follows associative learning rules. Accordingly, a mathematical implementation of associative learning models and multiple comparison between them can elucidate the underlying process and properties of VDAC. In this study, we implemented the Rescorla-Wagner, Mackintosh (Mac), Schumajuk-Pearce-Hall (SPH), and Esber-Haselgrove (EH) models to determine whether different models predict different outcomes when critical parameters in VDAC were adjusted. Simulation results were compared with experimental data from a series of VDAC studies by fitting two key model parameters, associative strength (V) and associability (α), using the Bayesian information criterion as a loss function. The results showed that SPH-V and EH- α outperformed other implementations of phenomena related to VDAC, such as expected value, training session, switching (or inertia), and uncertainty. Although V of models were sufficient to simulate VDAC when the expected value was the main manipulation of the experiment, α of models could predict additional aspects of VDAC, including uncertainty and resistance to extinction. In summary, associative learning models concur with the crucial aspects of behavioral data from VDAC experiments and elucidate underlying dynamics including novel predictions that need to be verified.
... Considering that stimulus features associated with reward uncertainty acquire priority signals (Anselme, 2010;Gottlieb, 2012) similar to those associated with high reward value, enhanced attentional orienting for the uncertainty targets is expected to facilitate behavioral responses. In contrast, other studies showed a lack of difference in behavioral performances by target reward contingency (Anderson & Halpern, 2017;Kim & Beck, 2020;Miranda & Palmer, 2014;Roper & Vecera, 2016). These mixed results suggest that, while reward feedback allowed participants to adequately form the stimulusreward associations top-down attentional control modulated the visual search for the two target colors by assigning equal priority (Anderson, Laurent, & Yantis, 2013), as the reward itself is irrelevant for the task goal of identifying the line orientation within the target circles. ...
Previous studies on value-driven attentional capture (VDAC) have demonstrated that the uncertainty of reward value modulates attentional allocation via associative learning. However, it is unclear whether such attentional exploration is executed based on the amount of potential reward information available for refining value prediction or the absolute size of reward prediction error. The present study investigated the effects of reward information (information entropy) and prediction error (variance) on attentional bias while controlling for the influence of the strength of reward association. Participants were instructed to search for either a red or green target circle and respond to the line orientation within the target. Each target color was associated with reward contingencies with different levels of uncertainty. In Experiment 1, one color was paired with a single reward value (zero entropy and variance) and the other with multiple reward values (high entropy and variance). In Experiment 2, one color had a high-entropy, low-variance reward contingency and the other had the inverse. Attentional interference for distractors with high entropy was consistently greater than low or zero entropy distractors. In addition, in Experiment 3, when distractors with an identical level of variance were given, information entropy was observed to modulate the attentional bias toward distractors. Lastly, Experiment 4 revealed that distractors associated with contrasting levels of variance, while information entropy was kept identical, failed to modulate VDAC. These results indicate that value-based attention is primarily allocated to cues that provide maximal information about the reward outcomes and that information entropy is one of the key predictors mediating attentional exploration and associative learning. (PsycInfo Database Record (c) 2022 APA, all rights reserved).
... Previous studies have suggested that the effects of value are relativethat is that a high-value stimulus is deemed to be high in value because it is more valuable than another stimulus. For example, S. Kim and Beck (2020) compared the effect of a reward to a higher and a lower reference value and found that the relative value, rather than the absolute value, determined the priority in attentional allocation. Importantly, in most previous studies of value-driven capture, both the high-and low-value colors from the training phase were presented in the test phase. ...
Attention tends to be attracted to visual features previously associated with reward. To date, nearly all existing studies examined value-associated stimuli at or near potential target locations, making such locations meaningful to inspect. The present experiments examined whether the attentional priority of a value-associated stimulus depends on its location-wise task relevance. In three experiments we used an RSVP task to compare the attentional demands of a value-associated peripheral distractor to that of a distractor associated with the top-down search goal. At a peripheral location that could never contain the target, a value-associated color did not capture attention. In contrast, at the same location, a distractor in a goal-matching color did capture attention. The results show that value-associated stimuli lose their attentional priority at task-irrelevant locations, in contrast to other types of stimuli that capture attention.
... It is also worth noting that conditioned stimuli associated with relatively higher reward values are prioritized attentionally (Anderson et al., 2011;Chelazzi et al., 2013;Kim & Beck, 2020;Lee & Shomstein, 2014), which may have disproportionately facilitated value updating for fruit snack-associated objects after fruit snack satiation in contrast to peanut-associated objects after peanut satiation. This explanation, however, depends on the assumption that monkeys primarily made selections by rejecting objects associated with the This document is copyrighted by the American Psychological Association or one of its allied publishers. ...
Goal-directed behavior and habit are parallel and, at times, competing processes. The relative balance of flexible, goal-directed responding as compared to inflexible habitual responding is highly dependent on experience (e.g., training history in a task) and conditions under which the behavior was formed. Reinforcer devaluation tasks have been used widely across species to study the neurobiology of goal-directed behavior. In rodents, under some conditions, extended training in reinforcer devaluation tasks transforms goal-directed responses into habits, rendering the animals insensitive to devaluation. In nonhuman primates, no studies have previously evaluated the impact of extended training. Here we trained four macaques in a variant of the standard reinforcer devaluation task (Málková et al., 1997), in which we presented objects with either a standard number of exposures (i.e., up to 55) or with a high number of exposures (i.e., up to 454). We tested for goal-directed behavior at three time points during the course of this extended training with different combinations of high- and low-repetition objects and stratified results based on whether the preferred or nonpreferred reinforcer was devalued. We found robust devaluation effects across all three cycles of training; however, the magnitude of the effect was modulated by reinforcer preference and by the relative training history of the objects. These data argue against habit formation after overtraining in the reinforcer devaluation task in macaques, a finding that is consistent with reports in humans and with tasks in rodents that employ multiple stimuli, reinforcers, and instrumental actions. (PsycInfo Database Record (c) 2022 APA, all rights reserved).
... Attentional biases toward learned reward cues continue to be updated by corresponding reward prediction-errors even when they have been made entirely irrelevant to the task (appear as task-irrelevant distractors) and no longer have any systematic relationship with reward outcome (Anderson et al., 2013b). A recent study shows that the relative, rather than absolute, amount of reward predicted by a stimulus determines the magnitude of subsequent attentional bias (Kim and Beck, 2020), as would be predicted from prediction-error accounts. Correspondingly, activity within regions of the brain coding reward prediction-errors have been related to the value-based control of attention (Arsenault et al., 2013;Barbaro et al., 2017;Peelen, 2015, 2017;Meffert et al., 2018; see Anderson, 2019, for a review). ...
The last ten years of attention research have witnessed a revolution, replacing a theoretical dichotomy (top-down vs. bottom-up control) with a trichotomy (biased by current goals, physical salience, and selection history). This third new mechanism of attentional control, selection history, is multifaceted. Some aspects of selection history must be learned over time whereas others reflect much more transient influences. A variety of different learning experiences can shape the attention system, including reward, aversive outcomes, past experience searching for a target, target‒non-target relations, and more. In this review, we provide an overview of the historical forces that led to the proposal of selection history as a distinct mechanism of attentional control. We then propose a formal definition of selection history, with concrete criteria, and identify different components of experience-driven attention that fit within this definition. The bulk of the review is devoted to exploring how these different components relate to one another. We conclude by proposing an integrative account of selection history centered on underlying themes that emerge from our review.
... The reward effects in the test phase indicate that the colorreward associations have successfully been established during the training phase. Surprisingly, though, in the majority of experiments, no reward effects have been observed during this phase (e.g., Anderson et al., 2011bAnderson et al., , 2013Anderson, 2015a,b;Gong et al., 2016, Experiment 2;Anderson and Halpern, 2017;Roper et al., 2014;Kim and Beck, 2020). Only in a few studies, some effects of the reward-association learning on performance have been reported (e.g., Anderson et al., 2016;Sha and Jiang, 2016). ...
One puzzling result in training-test paradigms is that effects of reward-associated stimuli on attention are often seen in test but not in training. We focus on one study, where reward-related performance benefits occur in the training and which was discussed contentiously. By using a similar design, we conceptually replicated the results. Moreover, we investigated the underlying mechanisms and processes resulting in these reward-related performance benefits. In two experiments, using search tasks and having participants perform the tasks either with or without individually adjusted time pressure, we disentangled the mechanisms and processes contributing to the reward-related benefits. We found evidence that not only search efficiency is increased with increasing reward, but also that non-search factors contribute to the results. By also investigating response time distributions, we were able to show that reward-related performance effects increased as search time increased in demanding tasks but not in less demanding tasks. Theoretical implications of the results regarding how reward influences attentional processing are discussed.
Stimuli associated with rewards can acquire the ability to capture our attention independently of our goals and intentions. Here, we examined whether attentional prioritisation of reward-related cues is sensitive to changes in the value of the reward itself. To this end, we incorporated an instructed outcome devaluation (Experiment 1a), “super-valuation” (Experiment 1b), or value switch (Experiment 2) into a visual search task, using eye-tracking to examine attentional prioritisation of stimuli signalling high- and low-value rewards. In Experiments 1a and 1b, we found that prioritisation of high- and low-value stimuli was insensitive to devaluation of a previously high-value outcome, and super-valuation of a previously low-value outcome, even when participants were provided with further experience of receiving that outcome. In Experiment 2, following a value-switch manipulation, we found that prioritisation of a high-value stimulus could not be overcome with knowledge of the new values of outcomes alone. Only when provided with further experience of receiving the outcomes did patterns of attentional prioritisation of high- and low-value stimuli switch, in line with the updated values of the outcomes they signalled. To reconcile these findings, we suggest that participants were motivated to engage in effortful updating of attentional control settings when there was a relative difference between reward values at test (Experiment 2) but that previous settings were allowed to persist when both outcomes had the same value at test (Experiments 1a and 1b). These findings provide a novel framework to further understand the role of cognitive control in driving reward-modulated attention and behaviour.
This literature review considers a range of factors regarding the concepts of ‘value’ and ‘values’ (including financial, tangible and intangible, measurable and non-measurable). The review is the first output from a project that examines ways of thinking about possible complementarities and tradeoffs between values (and systems of values) held by stakeholders. In doing so, the project provides a foundation for other projects concerned with diverse aspects of transformations in mining economies (e.g. relating to tools to manage closure and strategic planning processes). The literature review provides a synthesis of key insights into the rationale for considering values in the transition to post-mining land uses in section 2. The different dimensions of value differences are summarised in section 3, including the degree to which values change over time and space. Following on from this, a synthesis of the different ways of negotiating differences in values is provided in section 4. Together these sections help to understand values from different perspectives as well as possible ways to achieve ‘win-wins’ for different systems of values.
This literature review takes a broad approach to what we mean by ‘values’, rather than a narrow emphasis on ‘financial value’ or ‘financial worth’. One of the underlying rationales for this review was the need to shift post-mining land use evaluation from a focus on singular ‘value’ to plural ‘values’. While both are crucially important to the resources sector, the latter takes a wider and more inclusive approach. The singular ‘value’ focuses on those aspects of mining that can be reduced to a single measure, often conceptualised as financial worth expressed as net present value (NPV), return on investment (ROI), or as a measure of size in weight or volume. These measures of value have the benefit of being expressed in a single unit which makes them more tractable and easier to communicate. While a singular value (e.g. expressed as NPV) is important, to focus exclusively on a ‘value as financial worth’ runs the risk of ignoring a wider range of considerations which speak to things that matter to people (i.e. ‘values’) and potentially missing opportunities for post-mining land uses. This wider range of values incorporates a suite of issues which are often less tractable and more difficult to represent in balance sheets or quarterly reports. The implication of this tendency is that these broader ‘values’ may receive relatively less attention, despite their importance in transitions to post-mining economies. These issues are broad but may include externalities related to quality and quantity of resources such as water, opportunity costs and a range of intangibles such as sense of identity, connection to country, appreciation of natural wonder and human endeavour. Despite being less tractable, these broader values can be reflected in concepts such as ‘social licence’ which, from an industry perspective, can lead to disruption to mining activities (Owen, 2016). In extreme situations, failure to come to terms with a wider set of values can lead to conflict. The cost of this conflict has been estimated to be US$20 million per week of delayed production in NPV terms (Franks et al., 2014). It is important to emphasise that a broader recognition of values is not only about avoiding costs. It is also about realising opportunities and this is why moving from ‘value’ to ‘values’ is a key consideration in the context of post-mining transitions.
Stimuli formerly associated with monetary reward capture our attention, even if this attraction is contrary to current goals (so-called value-driven attentional capture [VDAC], see Anderson (Ann N Y Acad Sci 1369:24–39, 2016), for a review). Despite the growing literature to this topic, little is known about the boundary conditions for the occurrence of VDAC. In three experiments, we investigated the role of response conflicts and spatial uncertainty regarding the target location during the training and test phase for the emergence of value-driven effects. Thus, we varied the occurrence of a response conflict, search components, and the type of task in both phases. In the training, value-driven effects were rather observed if the location of the value-associated target was not predictable and a response conflict was present. Value-driven effects also only occurred, if participants have not learned to deal with a response conflict, yet. However, the introduction of a response conflict during learning of the color-value association seemed to prevent attention to be distracted by this feature in a subsequent test. The study provides new insights not only into the boundary conditions of the learning of value associations, but also into the learning of cognitive control.
Selective attention is a cognitive skill that allows an individual to focus on a particular input for further processing while simultaneously suppressing irrelevant or distracting information. In this study, we have developed a new test to assess selective attention-the Cognitive Skills Assessment of Minerva (CSM) Selective Attention Test-and have established selective attention norm values for Turkish individuals aged 6-14 years. This new online selective attention assessment test includes the flanker task. We employed split-half reliability to prove the reliability of the test. Based on the analysis, there was no significant difference between the groups, indicating that the test is reliable. We used criterion-related validity (congruent validity) analysis to evaluate the CSM Selective Attention Test. The correlation between the results of the new test and the Eriksen Flanker Test showed that the new test is valid. Finally, we conducted a comprehensive norm study with 2,297 participants aged 6-14 years from 12 different regions and schools in Turkey. According to the analysis of variance, age but not gender is a distinguishing factor for selective attention. We subsequently established norm values for each age group. The findings also show that the CSM Selective Attention Test provides reliable results across all samples and populations aged 6-14.
Values are what stakeholders regard to be important to decisions (Kruglanski & Higgins 2007). How stakeholder prioritize, rank, balance, and trade-off values can have significant influence on their reasoning and evaluation of decommissioning outcomes and decisions. Stakeholder values can vary depending on various factors including religious beliefs, personal interests, and past experiences (Lechner et al., 2017). Value-focused thinking is a decision science theory developed by Keeney (1992) which builds upon the concept of varying stakeholder values. Keeney (1992) argues that the best decision is one that best reflects the actual values of stakeholders. which suggests that the acceptability of decommissioning decisions (full removal, partial removal, leave in-situ, rigs-to-reefs, etc.) by stakeholders will vary depending on the values of stakeholder in that particular context.
This paper explores the idea of value-focused thinking and derive implications for decommissioning decision-making. Overall, the research finding suggests that rather than basing a decommissioning decision solely on scientific evidence, there is also a need for the decommissioning decisions to be able to reflect the actual values of stakeholders in that particular context. The criteria and weightage of the adopted multi-criteria decision analysis tool, for example, should accurately represent the actual values of stakeholders, so as to enable the tool to produce outcomes and decisions that has a higher probability of stakeholder acceptance.
Despite the increasing popularity of Bayesian inference in empirical research, few practical guidelines provide detailed recommendations for how to apply Bayesian procedures and interpret the results. Here we offer specific guidelines for four different stages of Bayesian statistical reasoning in a research setting: planning the analysis, executing the analysis, interpreting the results, and reporting the results. The guidelines for each stage are illustrated with a running example. Although the guidelines are geared toward analyses performed with the open-source statistical software JASP, most guidelines extend to Bayesian inference in general.
Recent evidence shows that distractors that signal high compared to low reward availability elicit stronger attentional capture, even when this is detrimental for task-performance. This suggests that simply correlating stimuli with reward administration, rather than their instrumental relationship with obtaining reward, produces value-driven attentional capture. However, in previous studies, reward delivery was never response independent, as only correct responses were rewarded, nor was it completely task-irrelevant, as the distractor signaled the magnitude of reward that could be earned on that trial. In two experiments, we ensured that associative reward learning was completely response independent by letting participants perform a task at fixation, while high and low rewards were automatically administered following the presentation of task-irrelevant colored stimuli in the periphery (Experiment 1) or at fixation (Experiment 2). In a following non-reward test phase, using the additional singleton paradigm, the previously reward signaling stimuli were presented as distractors to assess truly task-irrelevant value driven attentional capture. The results showed that high compared to low reward-value associated distractors impaired performance, and thus captured attention more strongly. This suggests that genuine Pavlovian conditioning of stimulus-reward contingencies is sufficient to obtain value-driven attentional capture. Furthermore, value-driven attentional capture can occur following associative reward learning of temporally and spatially task-irrelevant distractors that signal the magnitude of available reward (Experiment 1), and is independent of training spatial shifts of attention towards the reward signaling stimuli (Experiment 2). This confirms and strengthens the idea that Pavlovian reward learning underlies value driven attentional capture.
Adolescence has been characterized as a period of both opportunity and vulnerability. Numerous clinical conditions, including substance-use disorders, often emerge during adolescence. These maladaptive behaviors have been linked to problems with cognitive control, yet few studies have investigated how rewards differentially modulate attentional processes in adolescents versus adults. Here, we trained adults and adolescents on a visual task to establish stimulus-reward associations. Later, we assessed learning in an extinction task in which previously rewarded stimuli periodically appeared as distractors. Both age groups initially demonstrated value-driven attentional capture; however, the effect persisted longer in adolescents than in adults. The results could not be explained by developmental differences in visual working memory. Given the importance of attentional control to daily behaviors and clinical conditions such as attention-deficit/hyperactivity disorder, these results reveal that cognitive control failures in adolescence may be linked to a value-based attentional-capture effect.
Attention is automatically drawn to stimulus features previously associated with reward, a phenomenon referred to as value-driven attentional capture. To date, value-driven attentional capture has been studied exclusively by manipulating stimulus-reward contingencies in an experimental setting. Although practical and intuitively appealing, this approach poses theoretical challenges to understanding the broader impact of reward on attention in everyday life. These challenges arise from the fact that associative learning between a given visual feature and reward is not limited to the context of an experiment, yet such extra-experimental learning is completely ignored in studies of value-driven attention. How is it, then, that experimentally established reward associations even influence attention, seemingly overshadowing any prior learning about particular features and rewards? And how do the effects of this experimental learning persist over long periods of time, in spite of all the intervening experiences outside of the lab that might interfere with the learning? One potential answer to these questions is that value-driven attention is context specific, such that different contexts evoke different value priors that the attention system uses to assign priority. In the present study, I directly tested this hypothesis. The results show that the same stimulus feature either does or does not capture attention, depending on whether it has been rewarded specifically in the context within which it appears. The findings provide insight into how multiple reward structures can efficiently guide attention with minimal interference.
Previously rewarded stimuli involuntarily capture attention. The learning mechanisms underlying this value-driven attentional capture remain less understood. We tested whether theories of prediction-based associative reward learning explain the conditions under which reward feedback leads to value-based modulations of attentional priority. Across 4 experiments, we manipulated whether stimulus features served as unique predictors of reward outcomes. Participants received monetary rewards for correctly identifying a color-defined target in an initial search task (training phase) and then immediately completed a second, unrewarded visual search task in which color was irrelevant (test phase). In Experiments 1-3, monetary reward followed correct target selection during training, but critically, no target-defining features carried uniquely predictive information about reward outcomes. Under these conditions, we found no evidence of attentional capture by the previous target colors in the subsequent test phase. Conversely, when target colors in the training phase of Experiment 4 carried uniquely predictive information about reward magnitude, we observed significant attentional capture by the previously rewarded color. Our findings show that value-based attentional priority only develops for stimulus features that carry uniquely predictive information about reward, ruling out a purely motivational account and suggesting that mechanisms of reward prediction play an important role in shaping attentional priorities. (PsycINFO Database Record (c) 2014 APA, all rights reserved).
Recent evidence has suggested that reward modulates bottom-up and top-down attentional selection and that this effect persists within the same task even when reward is no longer offered. It remains unclear whether reward effects transfer across tasks, especially those engaging different modes of attention. We directly investigated whether reward-based contingency learned in a bottom-up search task was transferred to a subsequent top-down search task, and probed the nature of the transfer mechanism. Results showed that a reward-related benefit established in a pop-out-search task was transferred to a conjunction-search task, increasing participants' efficiency at searching for targets previously associated with a higher level of reward. Reward history influenced search efficiency by enhancing both target salience and distractor filtering, depending on whether the target and distractors shared a critical feature. These results provide evidence for reward-based transfer between different modes of attention and strongly suggest that an integrated priority map based on reward information guides both top-down and bottom-up attention.
Visual selective attention is the brain function that modulates ongoing processing of retinal input in order for selected representations to gain privileged access to perceptual awareness and guide behavior. Enhanced analysis of currently relevant or otherwise salient information is often accompanied by suppressed processing of the less relevant or salient input. Recent findings indicate that rewards exert a powerful influence on the deployment of visual selective attention. Such influence takes different forms depending on the specific protocol adopted in the given study. In some cases, the prospect of earning a larger reward in relation to a specific stimulus or location biases attention accordingly in order to maximize overall gain. This is mediated by an effect of reward acting as a type of incentive motivation for the strategic control of attention. In contrast, reward delivery can directly alter the processing of specific stimuli by increasing their attentional priority, and this can be measured even when rewards are no longer involved, reflecting a form of reward-mediated attentional learning. As a further development, recent work demonstrates that rewards can affect attentional learning in dissociable ways depending on whether rewards are perceived as feedback on performance or instead are registered as random-like events occurring during task performance. Specifically, it appears that visual selective attention is shaped by two distinct reward-related learning mechanisms: one requiring active monitoring of performance and outcome, and a second one detecting the sheer association between objects in the environment (whether attended or ignored) and the more-or-less rewarding events that accompany them. Overall this emerging literature demonstrates unequivocally that rewards "teach" visual selective attention so that processing resources will be allocated to objects, features and locations which are likely to optimize the organism's interaction with the surrounding environment and maximize positive outcome.
Visual attention is captured by physically salient stimuli (termed salience-based attentional capture), and by otherwise task-irrelevant stimuli that contain goal-related features (termed contingent attentional capture). Recently, we reported that physically nonsalient stimuli associated with value through reward learning also capture attention involuntarily (Anderson, Laurent, & Yantis, PNAS, 2011). Although it is known that physical salience and goal-relatedness both influence attentional priority, it is unknown whether or how attentional capture by a salient stimulus is modulated by its associated value. Here we show that a physically salient, task-irrelevant distractor previously associated with a large reward slows visual search more than an equally salient distractor previously associated with a smaller reward. This magnification of salience-based attentional capture by learned value extinguishes over several hundred trials. These findings reveal a broad influence of learned value on involuntary attentional capture.
On the contingent capture account, top-down attentional control settings restrict involuntary attentional capture to items that match the features of the search target. Attention capture is involuntary, but contingent on goals and intentions. The observation that only target-similar items can capture attention has usually been taken to show that the content of the attentional control settings consists of specific feature values. In contrast, the present study demonstrates that the top-down target template can include information about the relationship between the target and nontarget features (e.g., redder, darker, larger). Several spatial cuing experiments show that a singleton cue that is less similar to the target but that shares the same relational property that distinguishes targets from nontargets can capture attention to the same extent as cues that are similar to the target. Moreover, less similar cues can even capture attention more than cues that are identical to the target when they are relationally better than identical cues. The implications for current theories of attentional capture and attentional guidance are discussed.
What we pay attention to is influenced by reward learning. Converging evidence points to the idea that associative reward learning changes how visual stimuli are processed in the brain, rendering learned reward cues difficult to ignore. Behavioral evidence distinguishes value-driven attention from other established control mechanisms, suggesting a distinct underlying neurobiological process. Recently, studies have begun to explore the neural substrates of this value-driven attention mechanism. Here, I review the progress that has been made in this area, and synthesize the findings to provide an integrative account of the neurobiology of value-driven attention. The proposed account can explain both attentional capture by previously rewarded targets and the modulatory effect of reward on priming, as well as the decoupling of reward history and prior task relevance in value-driven attention.
A large body of research has shown that learning about relationships between neutral stimuli and events of significance-rewards or punishments-influences the extent to which people attend to those stimuli in future. However, different accounts of this influence differ in terms of the critical variable that is proposed to determine learned changes in attention. We describe two experiments using eye-tracking with a rewarded visual search procedure to investigate whether attentional capture is influenced by the predictiveness of stimuli (i.e., the extent to which they provide information about upcoming events) or by their absolute associative value (that is, the expected incentive value of the outcome that a stimulus predicts). Results demonstrated a clear influence of associative value on the likelihood that stimuli will capture eye-movements, but the evidence for a distinct influence of predictiveness was less compelling. The results of these experiments can be reconciled within a simple account under which attentional prioritization is a monotonic function of the expected, subjective value of the reward that is signalled by a stimulus.
Typically, if attending a target stimulus is consistently paired with obtaining high reward, then that stimulus becomes more likely to capture attention compared with an equally salient stimulus associated with low reward. Recent evidence extends this finding by showing that task-irrelevant distractors that signal high compared with low reward availability also elicit stronger capture, even when this is detrimental for task-performance and monetary payout. This suggests that the simple correlation between stimuli and reward delivery, rather than their instrumental relationship with obtaining reward, underlies value driven attentional capture. However, in previous studies, reward delivery was never response independent, as only fast and correct responses were rewarded, nor completely task-irrelevant, as the only way to discover how much reward could be earned on a trial was to attend the reward signaling distractor. In the present study we specifically addressed whether the mere correlation between stimuli and obtaining reward, completely independent of the current task and/or response, was able to elicit value driven attentional capture. During a classical (Pavlovian) conditioning phase, twenty-four participants performed a fixation task while stimuli following high and low reward feedback were presented in the periphery. In a subsequent testing phase in which no rewards were distributed, participants performed the additional singleton task while one of the distractors was sometimes presented in the previously high or low reward-value associated color. The results revealed that high compared with low reward-value associated distractors significantly slowed response times. Furthermore we showed that value driven attentional capture was strongest directly after the reward conditioning phase and decreased over time. These results provide clear evidence that value driven attentional capture occurs following a classical conditioning procedure. This confirms and strengthens the idea that Pavlovian rather than instrumental learning of stimulus-reward contingencies underlies value driven attentional capture.
Meeting abstract presented at VSS 2016
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Two experiments were conducted to directly test the feature set hypothesis and the relational set hypothesis in an inattentional blindness task. The feature set hypothesis predicts that unexpected objects that match the to-be-attended stimuli will be reported most. The relational set hypothesis predicts that unexpected objects that match the relationship between the to-be-attended and the to-be-ignored stimuli will be reported the most. Experiment 1 manipulated the luminance of the stimuli. Participants were instructed to monitor the gray letter shapes and to ignore either black or white letter shapes. The unexpected objects that exhibited the luminance relation of the to-be-attended to the to-be-ignored stimuli were reported by participants the most. Experiment 2 manipulated the color of the stimuli. Participants were instructed to monitor the yellower orange or the redder orange letter shapes and to ignore the redder orange or yellower letter shapes. The unexpected objects that exhibited the color relation of the to-be-attended to the to-be-ignored stimuli were reported the most. The results do not support the use of a feature set to accomplish the task and instead support the use of a relational set. In addition, the results point to the concurrent use of multiple attentional sets that are both excitatory and inhibitory.
There is growing consensus that reward plays an important role in the control of attention. Until recently, reward was thought to influence attention indirectly by modulating task-specific motivation and its effects on voluntary control over selection. Such an account was consistent with the goal-directed (endogenous) versus stimulus-driven (exogenous) framework that had long dominated the field of attention research. Now, a different perspective is emerging. Demonstrations that previously reward-associated stimuli can automatically capture attention even when physically inconspicuous and task-irrelevant challenge previously held assumptions about attentional control. The idea that attentional selection can be value driven, reflecting a distinct and previously unrecognized control mechanism, has gained traction. Since these early demonstrations, the influence of reward learning on attention has rapidly become an area of intense investigation, sparking many new insights. The result is an emerging picture of how the reward system of the brain automatically biases information processing. Here, I review the progress that has been made in this area, synthesizing a wealth of recent evidence to provide an integrated, up-to-date account of value-driven attention and some of its broader implications.
Prospect theory, first described in a 1979 paper by Daniel Kahneman and Amos Tversky, is widely viewed as the best available description of how people evaluate risk in experimental settings. While the theory contains many remarkable insights, economists have found it challenging to apply these insights, and it is only recently that there has been real progress in doing so. In this paper, after first reviewing prospect theory and the difficulties inherent in applying it, I discuss some of this recent work. While it is too early to declare this research effort an unqualified success, the rapid progress of the last decade makes me optimistic that at least some of the insights of prospect theory will eventually find a permanent and significant place in mainstream economic analysis.
Rewards affect the deployment of visual attention in various situations. Evidence suggests that the stimulus associated with reward involuntary captures attention (value-driven attentional capture; VDAC). Recent studies report VDAC even when the reward-associated feature does not define the target (i.e., task-irrelevant). However, these studies did not conduct the test phase without reward, thus the effect may be qualitatively different from those in the previous studies. In the current study, we tested if task-irrelevant features induce VDAC even in the test phase with no reward. We used a flanker task during reward learning to create color-reward associations (training phase), and then tested the effect of color during visual search (test phase). Reward learning with no spatial uncertainty in the flanker task induced VDAC, even when reward signaling color was associated with both target and distractor (Experiments 1 and 2). In Experiment 3, a significant VDAC with a color for all letters indicated that target-distractor discrimination is not necessary for VDAC. Finally, a significant VDAC (Experiment 4) with color rectangular frames around the letters indicated binding reward-associated features to task-relevant letters is not necessary for VDAC. All these effects were obtained in the test phase without reward, thus VDAC in the current study is comparable to previous studies using target-defining features. These findings indicate that task-relevance is not a necessary condition for VDAC from reward-associated features, suggesting that reward-associated learning in VDAC is more indirect.
Task-relevant and physically salient features influence visual selective attention. In the present study, we investigated the influence of task-irrelevant and physically nonsalient reward-associated features on visual selective attention. Two hypotheses were tested: One predicts that the effects of target-defining task-relevant and task-irrelevant features interact to modulate visual selection; the other predicts that visual selection is determined by the independent combination of relevant and irrelevant feature effects. These alternatives were tested using a visual search task that contained multiple targets, placing a high demand on the need for selectivity, and that was data-limited and required unspeeded responses, emphasizing early perceptual selection processes. One week prior to the visual search task, participants completed a training task in which they learned to associate particular colors with a specific reward value. In the search task, the reward-associated colors were presented surrounding targets and distractors, but were neither physically salient nor task-relevant. In two experiments, the irrelevant reward-associated features influenced performance, but only when they were presented in a task-relevant location. The costs induced by the irrelevant reward-associated features were greater when they oriented attention to a target than to a distractor. In a third experiment, we examined the effects of selection history in the absence of reward history and found that the interaction between task relevance and selection history differed, relative to when the features had previously been associated with reward. The results indicate that under conditions that demand highly efficient perceptual selection, physically nonsalient task-irrelevant and task-relevant factors interact to influence visual selective attention.
Relative reward value is important for the choice between a set of available rewards, and absolute reward value for stable and consistent economic choice. It is unclear whether in the human brain subjective absolute value representations can be dissociated from relative reward value representations. Using fMRI, we investigated how the subjective pleasantness of an odor is influenced by whether the odor is presented in the context of a relatively more pleasant or less pleasant odor. We delivered two of a set of four odors separated by a delay of 6 s, with the instruction to rate the pleasantness of the second odor, and searched for brain regions where the activations were correlated with the absolute pleasantness rating of the second odor, and for brain regions where the activations were correlated with the difference in pleasantness of the second from the first odor, that is, with relative pleasantness. Activations in the anterolateral orbitofrontal cortex tracked the relative subjective pleasantness, whereas activations in the anterior insula tracked the relative subjective unpleasantness. In contrast, in the medial and midorbitofrontal cortex activations tracked the absolute pleasantness of the stimuli. Thus, both relative and absolute subjective value signals which provide important inputs to decision-making processes about which stimulus to choose are separately and simultaneously represented in the human brain.
Has evolution optimized visual selective attention to make the best possible use of all information available? If so, then Bayesian optimal performance in a localization task is achieved by optimally weighting the visual evidence with one's prior spatial expectations. In 2 psychophysical experiments, participants conducted covert target localization where both visual cues and prior expectations were available. The amount of information conveyed by the visual evidence was held constant, while the degree of belief was manipulated via peripheral cuing (Experiment 1) and spatial probabilities (Experiment 2). A number of findings result: (1) People appear to optimally combine slightly biased prior beliefs with sensory evidence. (2) These biases are directly comparable to those descriptively accounted for by the Prospect Theory. (3) Probabilistic information about a target's upcoming location is integrated identically, irrespective of whether endogenous or exogenous cuing is used. (4) In localization tasks, spatial attention can be understood and quantitatively modeled as a set of prior expectations over space that modulate incoming noisy sensory evidence.
First published in 1958, this book has become recognized as a classic in its field. It marked a transition between behaviourist learning theory and the modern 'information processing' or 'cognitive' approach to perception and communication skills. It continues to provide a principal starting point for theoretical and experimental work on selective attention. As Professor Posner writes in his Foreword to the reissue: 'it remains of great interest to view the work in its original form and to ponder those creative moments when the mind first grasps a new insight and then struggles to work out its consequences.
The psychological principles that govern the perception of decision problems and the evaluation of probabilities and outcomes
produce predictable shifts of preference when the same problem is framed in different ways. Reversals of preference are demonstrated
in choices regarding monetary outcomes, both hypothetical and real, and in questions pertaining to the loss of human lives.
The effects of frames on preferences are compared to the effects of perspectives on perceptual appearance. The dependence
of preferences on the formulation of decision problems is a significant concern for the theory of rational choice.
Analysis of decision making under risk has been dominated by expected utility theory, which generally accounts for people's actions. Presents a critique of expected utility theory as a descriptive model of decision making under risk, and argues that common forms of utility theory are not adequate, and proposes an alternative theory of choice under risk called prospect theory. In expected utility theory, utilities of outcomes are weighted by their probabilities. Considers results of responses to various hypothetical decision situations under risk and shows results that violate the tenets of expected utility theory. People overweight outcomes considered certain, relative to outcomes that are merely probable, a situation called the "certainty effect." This effect contributes to risk aversion in choices involving sure gains, and to risk seeking in choices involving sure losses. In choices where gains are replaced by losses, the pattern is called the "reflection effect." People discard components shared by all prospects under consideration, a tendency called the "isolation effect." Also shows that in choice situations, preferences may be altered by different representations of probabilities. Develops an alternative theory of individual decision making under risk, called prospect theory, developed for simple prospects with monetary outcomes and stated probabilities, in which value is given to gains and losses (i.e., changes in wealth or welfare) rather than to final assets, and probabilities are replaced by decision weights. The theory has two phases. The editing phase organizes and reformulates the options to simplify later evaluation and choice. The edited prospects are evaluated and the highest value prospect chosen. Discusses and models this theory, and offers directions for extending prospect theory are offered. (TNM)
Perception and communication
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