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Hu M, Chang R, Sui X, Gao M. Attention biases the process of risky decision-making: Evidence from eye-tracking. Psych J 2024; 13:157-165. [PMID: 38155408 PMCID: PMC10990817 DOI: 10.1002/pchj.724] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2023] [Accepted: 11/29/2023] [Indexed: 12/30/2023]
Abstract
Attention determines what kind of option information is processed during risky choices owing to the limitation of visual attention. This paper reviews research on the relationship between higher-complexity risky decision-making and attention as illustrated by eye-tracking to explain the process of risky decision-making by the effect of attention. We demonstrate this process from three stages: the pre-phase guidance of options on attention, the process of attention being biased, and the impact of attention on final risk preference. We conclude that exogenous information can capture attention directly to salient options, thereby altering evidence accumulation. In particular, for multi-attribute risky decision-making, attentional advantages increase the weight of specific attributes, thus biasing risk preference in different directions. We highlight the significance of understanding how people use available information to weigh risks from an information-processing perspective via process data.
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Affiliation(s)
- Mengchen Hu
- School of Psychology, Liaoning Collaborative Innovation Center of Children and Adolescents Healthy Personality Assessment and CultivationLiaoning Normal UniversityDalianChina
| | - Ruosong Chang
- School of Psychology, Liaoning Collaborative Innovation Center of Children and Adolescents Healthy Personality Assessment and CultivationLiaoning Normal UniversityDalianChina
| | - Xue Sui
- School of Psychology, Liaoning Collaborative Innovation Center of Children and Adolescents Healthy Personality Assessment and CultivationLiaoning Normal UniversityDalianChina
| | - Min Gao
- School of Psychology, Liaoning Collaborative Innovation Center of Children and Adolescents Healthy Personality Assessment and CultivationLiaoning Normal UniversityDalianChina
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2
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Nunez MD, Fernandez K, Srinivasan R, Vandekerckhove J. A tutorial on fitting joint models of M/EEG and behavior to understand cognition. Behav Res Methods 2024:10.3758/s13428-023-02331-x. [PMID: 38409458 DOI: 10.3758/s13428-023-02331-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 12/21/2023] [Indexed: 02/28/2024]
Abstract
We present motivation and practical steps necessary to find parameter estimates of joint models of behavior and neural electrophysiological data. This tutorial is written for researchers wishing to build joint models of human behavior and scalp and intracranial electroencephalographic (EEG) or magnetoencephalographic (MEG) data, and more specifically those researchers who seek to understand human cognition. Although these techniques could easily be applied to animal models, the focus of this tutorial is on human participants. Joint modeling of M/EEG and behavior requires some knowledge of existing computational and cognitive theories, M/EEG artifact correction, M/EEG analysis techniques, cognitive modeling, and programming for statistical modeling implementation. This paper seeks to give an introduction to these techniques as they apply to estimating parameters from neurocognitive models of M/EEG and human behavior, and to evaluate model results and compare models. Due to our research and knowledge on the subject matter, our examples in this paper will focus on testing specific hypotheses in human decision-making theory. However, most of the motivation and discussion of this paper applies across many modeling procedures and applications. We provide Python (and linked R) code examples in the tutorial and appendix. Readers are encouraged to try the exercises at the end of the document.
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Affiliation(s)
- Michael D Nunez
- Psychological Methods, University of Amsterdam, Amsterdam, The Netherlands.
| | - Kianté Fernandez
- Department of Psychology, University of California, Los Angeles, CA, USA
| | - Ramesh Srinivasan
- Department of Cognitive Sciences, University of California, Irvine, CA, USA
- Department of Biomedical Engineering, University of California, Irvine, CA, USA
- Institute of Mathematical Behavioral Sciences, University of California, Irvine, CA, USA
| | - Joachim Vandekerckhove
- Department of Cognitive Sciences, University of California, Irvine, CA, USA
- Institute of Mathematical Behavioral Sciences, University of California, Irvine, CA, USA
- Department of Statistics, University of California, Irvine, CA, USA
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3
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Eum B, Dolbier S, Rangel A. Peripheral Visual Information Halves Attentional Choice Biases. Psychol Sci 2023; 34:984-998. [PMID: 37470671 DOI: 10.1177/09567976231184878] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/21/2023] Open
Abstract
A growing body of research has shown that simple choices involve the construction and comparison of values at the time of decision. These processes are modulated by attention in a way that leaves decision makers susceptible to attentional biases. Here, we studied the role of peripheral visual information on the choice process and on attentional choice biases. We used an eye-tracking experiment in which participants (N = 50 adults) made binary choices between food items that were displayed in marked screen "shelves" in two conditions: (a) where both items were displayed, and (b) where items were displayed only when participants fixated within their shelves. We found that removing the nonfixated option approximately doubled the size of the attentional biases. The results show that peripheral visual information is crucial in facilitating good decisions and suggest that individuals might be influenceable by settings in which only one item is shown at a time, such as e-commerce.
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Affiliation(s)
- Brenden Eum
- Department of Humanities and Social Sciences, California Institute of Technology
| | | | - Antonio Rangel
- Department of Humanities and Social Sciences, California Institute of Technology
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4
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Molter F, Thomas AW, Huettel SA, Heekeren HR, Mohr PNC. Gaze-dependent evidence accumulation predicts multi-alternative risky choice behaviour. PLoS Comput Biol 2022; 18:e1010283. [PMID: 35793388 PMCID: PMC9292127 DOI: 10.1371/journal.pcbi.1010283] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2021] [Revised: 07/18/2022] [Accepted: 06/07/2022] [Indexed: 11/18/2022] Open
Abstract
Choices are influenced by gaze allocation during deliberation, so that fixating an alternative longer leads to increased probability of choosing it. Gaze-dependent evidence accumulation provides a parsimonious account of choices, response times and gaze-behaviour in many simple decision scenarios. Here, we test whether this framework can also predict more complex context-dependent patterns of choice in a three-alternative risky choice task, where choices and eye movements were subject to attraction and compromise effects. Choices were best described by a gaze-dependent evidence accumulation model, where subjective values of alternatives are discounted while not fixated. Finally, we performed a systematic search over a large model space, allowing us to evaluate the relative contribution of different forms of gaze-dependence and additional mechanisms previously not considered by gaze-dependent accumulation models. Gaze-dependence remained the most important mechanism, but participants with strong attraction effects employed an additional similarity-dependent inhibition mechanism found in other models of multi-alternative multi-attribute choice. Faced with different choice alternatives, such as food options or risky prospects, our decisions and allocation of gaze (that is where we look) are closely linked, such that items that are looked at longer are often more likely to be chosen. In simple decisions (e.g., choosing between two chocolate bars), these decisions and their associations with gaze allocation are well described by computational models that assume accumulation of evidence in favour of each alternative over time and discounting of momentarily unattended information. However, an important question is whether this class of models can also describe choice behaviour in more complex settings. Specifically, so-called context effects, where preferences between two alternatives can vary with the addition of a third alternative, challenge many models of simple decision making. Our study addresses this question by evaluating gaze-dependent evidence accumulation models in a setting where choices between two risky lotteries are systematically influenced by a third alternative. We find gaze-dependent models to be able to describe context effects because decision-makers‘ gaze allocation also varies with different sets of alternatives.
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Affiliation(s)
- Felix Molter
- School of Business & Economics, Freie Universität Berlin, Berlin, Germany
- Center for Cognitive Neuroscience, Freie Universität Berlin, Berlin, Germany
- WZB Berlin Social Science Center, Berlin, Germany
- * E-mail:
| | - Armin W. Thomas
- Center for Cognitive Neuroscience, Freie Universität Berlin, Berlin, Germany
- Department of Electrical Engineering and Computer Science, Technische Universität Berlin, Berlin, Germany
- Department of Psychology, Stanford University, Stanford, California, United States of America
| | - Scott A. Huettel
- Center for Cognitive Neuroscience, Duke University, Durham, North Carolina, United States of America
- Department for Psychology and Neuroscience, Duke University, Durham, North Carolina, United States of America
| | - Hauke R. Heekeren
- Center for Cognitive Neuroscience, Freie Universität Berlin, Berlin, Germany
- Department for Education and Psychology, Freie Universität Berlin, Berlin, Germany
| | - Peter N. C. Mohr
- School of Business & Economics, Freie Universität Berlin, Berlin, Germany
- Center for Cognitive Neuroscience, Freie Universität Berlin, Berlin, Germany
- WZB Berlin Social Science Center, Berlin, Germany
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5
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Abstract
For over 100 years, eye movements have been studied and used as indicators of human sensory and cognitive functions. This review evaluates how eye movements contribute to our understanding of the processes that underlie decision-making. Eye movement metrics signify the visual and task contexts in which information is accumulated and weighed. They indicate the efficiency with which we evaluate the instructions for decision tasks, the timing and duration of decision formation, the expected reward associated with a decision, the accuracy of the decision outcome, and our ability to predict and feel confident about a decision. Because of their continuous nature, eye movements provide an exciting opportunity to probe decision processes noninvasively in real time. Expected final online publication date for the Annual Review of Vision Science, Volume 8 is September 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.
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Affiliation(s)
- Miriam Spering
- Department of Ophthalmology & Visual Sciences and the Djavad Mowafaghian Center for Brain Health, University of British Columbia, Vancouver, Canada;
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6
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Zhu T. Accounting for the last-sampling bias in perceptual decision-making. Cognition 2022; 223:105049. [DOI: 10.1016/j.cognition.2022.105049] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2021] [Revised: 01/24/2022] [Accepted: 01/26/2022] [Indexed: 11/16/2022]
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7
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Ramírez-Ruiz J, Moreno-Bote R. Optimal Allocation of Finite Sampling Capacity in Accumulator Models of Multialternative Decision Making. Cogn Sci 2022; 46:e13143. [PMID: 35523123 PMCID: PMC9285422 DOI: 10.1111/cogs.13143] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2021] [Revised: 02/07/2022] [Accepted: 04/16/2022] [Indexed: 11/28/2022]
Abstract
When facing many options, we narrow down our focus to very few of them. Although behaviors like this can be a sign of heuristics, they can actually be optimal under limited cognitive resources. Here, we study the problem of how to optimally allocate limited sampling time to multiple options, modeled as accumulators of noisy evidence, to determine the most profitable one. We show that the effective sampling capacity of an agent increases with both available time and the discriminability of the options, and optimal policies undergo a sharp transition as a function of it. For small capacity, it is best to allocate time evenly to exactly five options and to ignore all the others, regardless of the prior distribution of rewards. For large capacities, the optimal number of sampled accumulators grows sublinearly, closely following a power law as a function of capacity for a wide variety of priors. We find that allocating equal times to the sampled accumulators is better than using uneven time allocations. Our work highlights that multialternative decisions are endowed with breadth–depth tradeoffs, demonstrates how their optimal solutions depend on the amount of limited resources and the variability of the environment, and shows that narrowing down to a handful of options is always optimal for small capacities.
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Affiliation(s)
- Jorge Ramírez-Ruiz
- Center for Brain and Cognition, Department of Information and Communication Technologies, Universitat Pompeu Fabra
| | - Rubén Moreno-Bote
- Center for Brain and Cognition, Department of Information and Communication Technologies, Universitat Pompeu Fabra.,Serra Húnter Fellow Programme, Universitat Pompeu Fabra
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8
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Frömer R, Shenhav A. Filling the gaps: Cognitive control as a critical lens for understanding mechanisms of value-based decision-making. Neurosci Biobehav Rev 2022; 134:104483. [PMID: 34902441 PMCID: PMC8844247 DOI: 10.1016/j.neubiorev.2021.12.006] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2021] [Revised: 12/01/2021] [Accepted: 12/04/2021] [Indexed: 12/26/2022]
Abstract
While often seeming to investigate rather different problems, research into value-based decision making and cognitive control have historically offered parallel insights into how people select thoughts and actions. While the former studies how people weigh costs and benefits to make a decision, the latter studies how they adjust information processing to achieve their goals. Recent work has highlighted ways in which decision-making research can inform our understanding of cognitive control. Here, we provide the complementary perspective: how cognitive control research has informed understanding of decision-making. We highlight three particular areas of research where this critical interchange has occurred: (1) how different types of goals shape the evaluation of choice options, (2) how people use control to adjust the ways they make their decisions, and (3) how people monitor decisions to inform adjustments to control at multiple levels and timescales. We show how adopting this alternate viewpoint offers new insight into the determinants of both decisions and control; provides alternative interpretations for common neuroeconomic findings; and generates fruitful directions for future research.
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Affiliation(s)
- R Frömer
- Cognitive, Linguistic, and Psychological Sciences, Carney Institute for Brain Science, Brown University, Providence, RI, United States.
| | - A Shenhav
- Cognitive, Linguistic, and Psychological Sciences, Carney Institute for Brain Science, Brown University, Providence, RI, United States.
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9
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Woo TF, Law CK, Ting KH, Chan CCH, Kolling N, Watanabe K, Chau BKH. Distinct Causal Influences of Dorsolateral Prefrontal Cortex and Posterior Parietal Cortex in Multiple-Option Decision Making. Cereb Cortex 2021; 32:1390-1404. [PMID: 34470053 DOI: 10.1093/cercor/bhab278] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2020] [Revised: 07/14/2021] [Accepted: 07/15/2021] [Indexed: 11/13/2022] Open
Abstract
Our knowledge about neural mechanisms underlying decision making is largely based on experiments that involved few options. However, it is more common in daily life to choose between many options, in which processing choice information selectively is particularly important. The current study examined whether the dorsolateral prefrontal cortex (dlPFC) and posterior parietal cortex (PPC) are of particular importance to multiple-option decision making. Sixty-eight participants received anodal high definition-transcranial direct current stimulation (HD-tDCS) to focally enhance dlPFC or PPC in a double-blind sham-controlled design. Participants then performed a multiple-option decision making task. We found longer fixations on poorer options were related to less optimal decisions. Interestingly, this negative impact was attenuated after applying anodal HD-tDCS over dlPFC, especially in choices with many options. This suggests that dlPFC has a causal role in filtering choice-irrelevant information. In contrast, these effects were absent after participants received anodal HD-tDCS over PPC. Instead, the choices made by these participants were more biased towards the best options presented on the side contralateral to the stimulation. This suggests PPC has a causal role in value-based spatial selection. To conclude, the dlPFC has a role in filtering undesirable options, whereas the PPC emphasizes the desirable contralateral options.
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Affiliation(s)
- Tsz-Fung Woo
- Department of Rehabilitation Sciences, The Hong Kong Polytechnic University, Hong Kong
| | - Chun-Kit Law
- Department of Rehabilitation Sciences, The Hong Kong Polytechnic University, Hong Kong
| | - Kin-Hung Ting
- University Research Facility in Behavioral and Systems Neuroscience, The Hong Kong Polytechnic University, Hong Kong
| | - Chetwyn C H Chan
- Department of Psychology, The Education University of Hong Kong, Hong Kong
| | - Nils Kolling
- Department of Psychiatry, University of Oxford, Oxford OX3 7JX, UK.,Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, OX3 9DU, UK.,Oxford Centre for Human Brain Activity (OHBA), University of Oxford, Oxford, OX3 7JX, UK
| | - Kei Watanabe
- Department of Frontier Biosciences, Osaka University, Osaka 565-0871, Japan
| | - Bolton K H Chau
- Department of Rehabilitation Sciences, The Hong Kong Polytechnic University, Hong Kong.,University Research Facility in Behavioral and Systems Neuroscience, The Hong Kong Polytechnic University, Hong Kong
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10
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Thomas AW, Molter F, Krajbich I. Uncovering the computational mechanisms underlying many-alternative choice. eLife 2021; 10:e57012. [PMID: 33821787 PMCID: PMC8025657 DOI: 10.7554/elife.57012] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2020] [Accepted: 03/01/2021] [Indexed: 11/23/2022] Open
Abstract
How do we choose when confronted with many alternatives? There is surprisingly little decision modelling work with large choice sets, despite their prevalence in everyday life. Even further, there is an apparent disconnect between research in small choice sets, supporting a process of gaze-driven evidence accumulation, and research in larger choice sets, arguing for models of optimal choice, satisficing, and hybrids of the two. Here, we bridge this divide by developing and comparing different versions of these models in a many-alternative value-based choice experiment with 9, 16, 25, or 36 alternatives. We find that human choices are best explained by models incorporating an active effect of gaze on subjective value. A gaze-driven, probabilistic version of satisficing generally provides slightly better fits to choices and response times, while the gaze-driven evidence accumulation and comparison model provides the best overall account of the data when also considering the empirical relation between gaze allocation and choice.
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Affiliation(s)
- Armin W Thomas
- Technische Universität BerlinBerlinGermany
- Freie Universität BerlinBerlinGermany
- Center for Cognitive Neuroscience BerlinBerlinGermany
- Max Planck School of CognitionBerlinGermany
| | - Felix Molter
- Freie Universität BerlinBerlinGermany
- Center for Cognitive Neuroscience BerlinBerlinGermany
- WZB Berlin Social Science CenterBerlinGermany
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