The dynamics of choice among multiple alternatives

McMillen, Tyler; Holmes, Philip

doi:10.1016/j.jmp.2005.10.003

Cited by 138 publications

(181 citation statements)

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“…Furthermore, the optimal statistical test associated with the case of multiple alternatives is unknown, and only approximations have been proposed (32,33). Out of the alternatives that have been proposed, the multihypothesis sequential probability ratio test (MSPRT) is a particularly appealing one, because it reduces to the SPRT in the case of two options, and is asymptotically optimal in the sense that for sufficiently low error rates it minimizes expected decision time (5,25,33,35).Second, the classic DDM and leaky integrator models have ignored the role that visual attention plays in the choice process. This gap is an important limitation because both casual observation and previous research suggest that visual fixations play a role in the decision-making process (18,36,37).…”

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“…The question is difficult because a large number of possible extensions with significantly different behavioral and neurobiological properties are possible (5,27,(30)(31)(32)(33)(34). Furthermore, the optimal statistical test associated with the case of multiple alternatives is unknown, and only approximations have been proposed (32,33). Out of the alternatives that have been proposed, the multihypothesis sequential probability ratio test (MSPRT) is a particularly appealing one, because it reduces to the SPRT in the case of two options, and is asymptotically optimal in the sense that for sufficiently low error rates it minimizes expected decision time (5,25,33,35).…”

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Multialternative drift-diffusion model predicts the relationship between visual fixations and choice in value-based decisions

Krajbich¹,

Rangel

2011

Proc. Natl. Acad. Sci. U.S.A.

663

817

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How do we make decisions when confronted with several alternatives (e.g., on a supermarket shelf)? Previous work has shown that accumulator models, such as the drift-diffusion model, can provide accurate descriptions of the psychometric data for binary value-based choices, and that the choice process is guided by visual attention. However, the computational processes used to make choices in more complicated situations involving three or more options are unknown. We propose a model of trinary value-based choice that generalizes what is known about binary choice, and test it using an eye-tracking experiment. We find that the model provides a quantitatively accurate description of the relationship between choice, reaction time, and visual fixation data using the same parameters that were estimated in previous work on binary choice. Our findings suggest that the brain uses similar computational processes to make binary and trinary choices.A basic goal of decision neuroscience is to characterize the computational processes used by individuals to make different types of decisions, as well as the neurobiological substrates of such computations (1-5). A significant amount of effort has been devoted to characterizing these processes in the realm of perceptual decision making involving two-alternative forced choices (2, 6-8). However, many important decisions do not fit this framework: they involve choices among multiple alternatives (n > 2) associated with different reward values (e.g., which food to select from a buffet table). Here we investigate these types of decisions.The standard drift-diffusion model (DDM), as well as closely related versions, such as the leaky competitive accumulator (LCA) model (3, 4, 9), have been highly successful in providing quantitative explanations of the psychometrics, chronometrics, and neurometrics of binary perceptual choice (2, 10-16), and more recently in binary value-based choice (17-20). These models assume that decisions are made by accumulating stochastic information over time until the net evidence in favor of one option exceeds a prespecified threshold. The size of the threshold can be chosen to optimally balance the benefit of accumulating more information with the cost of taking more time to reach a decision (21). Consider, for example, the canonical dot-motion task that has been widely used to study perceptual decision making. Here the stimulus itself is stochastic and each instant is thought to provide noisy but informative evidence for the net direction of movement in the display. Thus, as the individual accumulates more evidence, his knowledge about the true net direction of movement increases (2).The DDM has also been shown to provide highly accurate descriptions of accuracy and response times in domains such as memory retrieval and decision-making, where the stimuli are not explicitly stochastic (17,19,20,(22)(23)(24)(25)(26)(27)(28); this suggests that these decisions might be made using a similar process of random information accumulation and integration. To see why, ...

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Multialternative drift-diffusion model predicts the relationship between visual fixations and choice in value-based decisions

Krajbich¹,

Rangel

2011

Proc. Natl. Acad. Sci. U.S.A.

663

817

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“…It is based on attractor dynamics and winner-take-all competition of 2 discrete selective populations of neurons (pools), each representing 1 alternative. Choice behavior, regardless of the number of alternatives, was captured successfully by some firing-rate models of neural networks (9)(10)(11)(12). However, it is difficult to relate these rate models to possible physiological realizations of multiplechoice decision making.…”

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The encoding of alternatives in multiple-choice decision making

Albantakis

Deco

2009

Proc. Natl. Acad. Sci. U.S.A.

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During the last decades, research on binary decision making elucidated some of the basic neural mechanisms underlying the decision-making process. Recently, the focus of experimental as well as modeling studies began to shift from simple binary choices to decision making with multiple alternatives. In this article, we address the question how different numbers of choice alternatives might be handled and encoded in the brain. We present a minimal, biophysically realistic spiking neuron model for decision making with multiple alternatives. Our model accounts for the relevant aspects of recent experimental data of a random-dot motiondiscrimination task on both the cellular and behavioral level. Notably, all network parameters and inputs in our network are independent of the number of possible alternatives used in the tested experimental paradigms (2 and 4 alternatives and 2 alternatives with an angular separation of 90°). This avoids the use of extra top-down regulation mechanisms to adapt the network to the number of choices. Furthermore, we show that increasing the number of neurons encoding each choice alternative is positively related to the network's capacity of choice-number-independent decision making. Consequently, our results suggest a physiological advantage of a pooled, multineuron representation of choice alternatives.attractor networks ͉ parietal cortex ͉ random-dot motion ͉ computational model A lready decades ago, decision making between multiple alternatives was the subject of psychophysical reaction-time studies, which revealed an increase in reaction times with the number of choices (1). With the objective of shedding light on the neural mechanisms underlying decision making, experimental and theoretical studies mainly focused on the simplest case of binary choice (2-4). Thereby, the lateral intraparietal area (LIP) was identified as a candidate for bounded integration in the decision process. Its neural activity correlates with the choices and reaction times of monkeys performing the random-dot motion (RDM) task (Fig. 1A), a well-established paradigm to test for accumulation and integration of evidence during decision making (5-7).One biophysically realistic spiking neuron model of LIP that successfully simulated behavioral and physiological data from the binary RDM task was proposed by Wang (8). It is based on attractor dynamics and winner-take-all competition of 2 discrete selective populations of neurons (pools), each representing 1 alternative. Choice behavior, regardless of the number of alternatives, was captured successfully by some firing-rate models of neural networks (9-12). However, it is difficult to relate these rate models to possible physiological realizations of multiplechoice decision making.Last year, experimental studies extended the RDM paradigm to more than 2 alternatives (11, 13). Churchland et al. (13) compared behavioral data and recordings from single LIP neurons of a 4-choice RDM task with the original 2-alternative task. Reaction times and error rates for 4 alternatives...

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“…When attention is focused on certain attributes of a subject, it becomes easier to disregard the other attributes [8,9]. Consuming dietary supplements can prime consumers to pay more attention to health.…”

Section: Hypothesis Developmentmentioning

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Complementarity in dietary supplements and foods: are supplement users vegetable eaters?

Kang

Joo

Choi

et al. 2017

Food & Nutrition Research

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Background: The consumption of fruits, vegetables, and dietary supplements correlate. Most previous studies have aimed to identify the determinants of supplement uses or the distinct features of supplement users; this literature lacks a discussion on dietary supplement consumption as a predictor of fruit and vegetable consumption. Objective: This study examines how dietary supplement consumption correlates with fruit and vegetable consumption by combining scanner data and surveys of Korean household grocery shopping. Methods: Propensity score matching (PSM) is used to identify the relationship between dietary supplement consumption and fruit and vegetable consumption in a household. A logit regression using supplement consumption as the dependent variable is used. Then, the supplement takers (the treatment group) are matched with non-takers (the control group) based on the propensity scores estimated in the logit regression. The fruit and vegetable consumption levels of the groups are then compared. Results: We found that dietary supplement use is associated with higher fruit and vegetable consumption. This supports the health consciousness hypothesis based on attention bias, availability heuristics, the focusing effect, and the consumption episode effect. It rejects the health substitute hypothesis based on economic substitutes and mental accounting. Conclusions: Future research on the health benefits of dietary supplements should address the complementary consumption of fruits/vegetables and their health benefits to avoid misstating the health effects of supplements.

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The dynamics of choice among multiple alternatives

Cited by 138 publications

References 39 publications

Multialternative drift-diffusion model predicts the relationship between visual fixations and choice in value-based decisions

Multialternative drift-diffusion model predicts the relationship between visual fixations and choice in value-based decisions

The encoding of alternatives in multiple-choice decision making

Complementarity in dietary supplements and foods: are supplement users vegetable eaters?

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