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      Value-based attentional capture affects multi-alternative decision making

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          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Humans and other animals often violate economic principles when choosing between multiple alternatives, but the underlying neurocognitive mechanisms remain elusive. A robust finding is that adding a third option can alter the relative preference for the original alternatives, but studies disagree on whether the third option’s value decreases or increases accuracy. To shed light on this controversy, we used and extended the paradigm of one study reporting a positive effect. However, our four experiments with 147 human participants and a reanalysis of the original data revealed that the positive effect is neither replicable nor reproducible. In contrast, our behavioral and eye-tracking results are best explained by assuming that the third option’s value captures attention and thereby impedes accuracy. We propose a computational model that accounts for the complex interplay of value, attention, and choice. Our theory explains how choice sets and environments influence the neurocognitive processes of multi-alternative decision making.

          eLife digest

          A man in a restaurant is offered a choice between apple or blueberry pie, and chooses apple. The waiter then returns a few moments later and tells him they also have cherry pie available. “In that case”, replies the man, “I’ll have blueberry”.

          This well-known anecdote illustrates a principle in economics and psychology called the independence principle. This states that preferences between two options should not change when a third option becomes available. A person who prefers apple over blueberry pie should continue to do so regardless of whether cherry pie is also on the menu. But, as in the anecdote, people often violate the independence principle when making decisions. One example is voting. People may vote for a candidate who would not usually be their first choice only because there is also a similar but clearly less preferable candidate available.

          Such behavior provides clues to the mechanisms behind making decisions. Studies show, for example, that when people have to choose between two options, introducing a desirable third option that cannot be selected – a distractor – alters what decision they make. But the studies disagree on whether the distractor improves or impairs performance.

          Gluth et al. now resolve this controversy using tasks in which people had to choose between rectangles on a computer screen for the chance to win different amounts of money. Contrary to a previous study, their four experiments showed that a high-value distractor did not change how likely the volunteers were to select one of the two available options over the other. Instead, the distractor slowed down the entire decision-making process. Moreover, volunteers often selected the high-value distractor despite knowing that they could not have it. One explanation for such behavior is that high-value items capture our attention automatically even when they are irrelevant to our goals. If a person likes chocolate cake, their attention will immediately be drawn to a cake in a shop window, even if they had no plans to buy a cake. Eye-tracking data confirmed that volunteers in the above experiments spent more time looking at high-value items than low-value ones. Those volunteers whose gaze was distracted the most by high-value items also made the worst decisions.

          Based on the new data, Gluth et al. developed and tested a mathematical model. The model describes how we make decisions, and how attention influences this process. It provides insights into the interplay between attention, valuation and choice – particularly when we make decisions under time pressure. Such insights may enable us to improve decision-making environments where people must choose quickly between many options. These include emergency medicine, road traffic situations, and the stock market. To achieve this goal, findings from the current study need to be tested under more naturalistic conditions.

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          Most cited references58

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          Advances in prospect theory: Cumulative representation of uncertainty

          Journal of Risk and Uncertainty, 5(4), 297-323
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            • Record: found
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            The time course of perceptual choice: the leaky, competing accumulator model.

            The time course of perceptual choice is discussed in a model of gradual, leaky, stochastic, and competitive information accumulation in nonlinear decision units. Special cases of the model match a classical diffusion process, but leakage and competition work together to address several challenges to existing diffusion, random walk, and accumulator models. The model accounts for data from choice tasks using both time-controlled (e.g., response signal) and standard reaction time paradigms and its adequacy compares favorably with other approaches. A new paradigm that controls the time of arrival of information supporting different choice alternatives provides further support. The model captures choice behavior regardless of the number of alternatives, accounting for the log-linear relation between reaction time and number of alternatives (Hick's law) and explains a complex pattern of visual and contextual priming in visual word identification.
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              Normalization as a canonical neural computation.

              There is increasing evidence that the brain relies on a set of canonical neural computations, repeating them across brain regions and modalities to apply similar operations to different problems. A promising candidate for such a computation is normalization, in which the responses of neurons are divided by a common factor that typically includes the summed activity of a pool of neurons. Normalization was developed to explain responses in the primary visual cortex and is now thought to operate throughout the visual system, and in many other sensory modalities and brain regions. Normalization may underlie operations such as the representation of odours, the modulatory effects of visual attention, the encoding of value and the integration of multisensory information. Its presence in such a diversity of neural systems in multiple species, from invertebrates to mammals, suggests that it serves as a canonical neural computation.
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                Author and article information

                Contributors
                Role: Senior Editor
                Role: Reviewing Editor
                Journal
                eLife
                Elife
                eLife
                eLife
                eLife Sciences Publications, Ltd
                2050-084X
                05 November 2018
                2018
                : 7
                : e39659
                Affiliations
                [1 ]deptDepartment of Psychology University of Basel BaselSwitzerland
                [2 ]deptDepartment of Psychology University of Freiburg FreiburgGermany
                Brown University United States
                Brown University United States
                Brown University United States
                Author notes
                [†]

                These authors contributed equally to this work.

                Author information
                http://orcid.org/0000-0003-2241-5103
                https://orcid.org/0000-0003-0652-1993
                Article
                39659
                10.7554/eLife.39659
                6218187
                30394874
                6a8ae384-137b-4062-85bd-515199f4249a
                © 2018, Gluth et al

                This article is distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use and redistribution provided that the original author and source are credited.

                History
                : 28 June 2018
                : 01 October 2018
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/501100001711, Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung;
                Award ID: 100014_153616
                Award Recipient :
                The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
                Categories
                Research Article
                Neuroscience
                Custom metadata
                Speeded value-based decisions between two options can be affected by a third, high-value distractor that captures attention and slows down the choice process.

                Life sciences
                value-based decision making,eye tracking,sequential sampling models,context effects,cognitive modeling,replication,human

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