Ian Krajbich - Academia.edu (original) (raw)

Papers by Ian Krajbich

Neuron, 2018

Highlights d Human subjects learn to detect patterns in sequences of images while undergoing fMRI... more Highlights d Human subjects learn to detect patterns in sequences of images while undergoing fMRI d Behavior is well explained by a Bayesian patternlearning model d Distinct networks track uncertainty about the pattern and the predicted image

Judgment and Decision Making

A core principle in decision science is that people choose according to their subjective values. ... more A core principle in decision science is that people choose according to their subjective values. These values are often measured using unincentivized scales with arbitrary units (e.g., from 0 to 10) or using incentivized willingness-to-pay (WTP) with dollars and cents. What is unclear is whether using WTP actually improves choice predictions. In two experiments, we compare the effects of three different subjective valuation procedures: an unincentivized rating scale, the same scale with incentives, and incentivized WTP. We use these subjective values to predict behavior in a subsequent binary food-choice task. The unincentivized rating task performed better than the incentivized WTP task and no worse than the incentivized rating task. These findings challenge the view that subjective valuation tasks need to be incentivized. At least for low-stakes decisions, commonly used measures such as WTP may reduce predictive power.

Judgment and Decision Making

Revealed preference is the dominant approach for inferring preferences, but it is limited in that... more Revealed preference is the dominant approach for inferring preferences, but it is limited in that it relies solely on discrete choice data. When a person chooses one alternative over another, we cannot infer the strength of their preference or predict how likely they will be to make the same choice again. However, the choice process also produces response times (RTs), which are continuous and easily observable. It has been shown that RTs often decrease with strength-of-preference. This is a basic property of sequential sampling models such as the drift diffusion model. What remains unclear is whether this relationship is sufficiently strong, relative to the other factors that affect RTs, to allow us to reliably infer strength-of-preference across individuals. Using several experiments, we show that even when every subject chooses the same alternative, we can still rank them based on their RTs and predict their behavior on other choice problems. We can also use RTs to predict whether...

Psychological Review, 2022

for comments, and to Stephanie Smith, Marios Philiastides and Bernd Weber for sharing their data.... more for comments, and to Stephanie Smith, Marios Philiastides and Bernd Weber for sharing their data. I.K. gratefully acknowledges financial support from National Science Foundation Career Grant No.

Recent studies have suggested close functional links between visual attention and decision making... more Recent studies have suggested close functional links between visual attention and decision making. This suggests that the corresponding mechanisms may interface in brain regions known to be crucial for guiding visual attention – such as the frontal eye field (FEF). Here, we combined brain stimulation, eye tracking and computational approaches to explore this possibility. We show that inhibitory transcranial magnetic stimulation (TMS) over the right FEF has a causal impact on decision-making, reducing the effect of gaze dwell time on choice while also increasing reaction times. We computationally characterize this putative mechanism by using the attentional drift diffusion model (aDDM), which reveals that FEF inhibition reduces the relative discounting of the non-fixated option in the comparison process. Our findings establish an important causal role of the right FEF in choice, elucidate the underlying mechanism, and provide support for one of the key causal hypotheses associated wi...

Time is an extremely valuable resource but little is known about the efficiency of time allocatio... more Time is an extremely valuable resource but little is known about the efficiency of time allocation in decision-making. Empirical evidence suggests that in many ecologically relevant situations, decision difficulty and the relative reward from making a correct choice, compared to an incorrect one, are inversely linked, implying that it is optimal to use relatively less time for difficult choice problems. This applies, in particular, to value-based choices, in which the relative reward from choosing the higher valued item shrinks as the values of the other options get closer to the best option and are thus more difficult to discriminate. Here, we experimentally show that people behave sub-optimally in such contexts. They do not respond to incentives that favour the allocation of time to choice problems in which the relative reward for choosing the best option is high; instead they spend too much time on problems in which the reward difference between the options is low. We demonstrate...

The young field of neuroeconomics has already produced many important insights into the neurobiol... more The young field of neuroeconomics has already produced many important insights into the neurobiological underpinnings of decision making. However, at this early stage it is still unclear how much influence the field will have on mainstream economics. Here, I show how a neuroeconomics approach can shed light on two classic economic problems. First, I show that it is possible to predict individuals’ values for public goods, using functional magnetic resonance imaging (fMRI)-based pattern classification. With such predictions in hand, I demonstrate that it is possible to solve the free-rider problem, by taxing individuals based both on the values that they themselves report and on the predicted values (using fMRI). I go on to more generally prove that by using any informative signal of value, it is possible to overcome classic impossibility results in mechanism design. This allows us to construct mechanisms that simultaneously satisfy dominant strategy incentive compatibility, voluntar...

Experiments are increasingly moving online. This poses a major challenge for researchers who rely... more Experiments are increasingly moving online. This poses a major challenge for researchers who rely on in-lab techniques such as eye-tracking. Researchers in computer science have developed web-based eye-tracking applications (WebGazer; Papoutsaki et al., 2016) but they have yet to see use in behavioral research. This is likely due to the extensive calibration and validation procedure, inconsistent temporal resolution (Semmelmann & Weigelt, 2018), and the challenge of integrating it into experimental software. Here, we incorporate WebGazer into a widely used JavaScript library among behavioral researchers (jsPsych) and adjust the procedure and code to reduce calibration/validation and improve the temporal resolution (from 100-1000 ms to 20-30 ms). We test this procedure with a decision-making study on Amazon MTurk, replicating previous in-lab findings on the relationship between gaze and choice, with little degradation in spatial or temporal resolution. This provides evidence that onl...

Proceedings of the National Academy of Sciences, 2020

SignificanceChoices that consist of risky versus certain options are pervasive and consequential,... more SignificanceChoices that consist of risky versus certain options are pervasive and consequential, leading many researchers to investigate when and which individuals select risk over certainty. The present research takes an alternative approach and measures computer mouse movements to assess how people arrive at these decisions. We show that measuring mouse movements while participants are deciding between a risky gamble and a certain payout powerfully detects their conflict about the options, and that this conflict strongly predicts their risk preferences. Further, mouse movements are predictive of risk preferences even when choice outcomes are not. The present research thus demonstrates the unique utility of dynamic measures of choice, as well as the predictive and theoretical importance of conflict in risky decision-making.

How do we choose when confronted with many alternatives (e.g., choosing which soda to buy at the ... more How do we choose when confronted with many alternatives (e.g., choosing which soda to buy at the supermarket)? While studies of the decision mechanisms underlying two- to three-alternative choice are common in the literature, there is comparably little decision modeling work with larger 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 comparing these models in a many-alternative value-based choice experiment with 9, 16, 25 or 36 choice alternatives. We find that human subjects' choice behaviour does not match the assumptions of satisficing or optimal choice, while a hybrid of the two captures response times and choices well. Yet, only a process of gaze-driven evidence accumulation is able to...

Journal of the Economic Science Association, 2019

Until recently, research in experimental economics had largely ignored the choice process, focusi... more Until recently, research in experimental economics had largely ignored the choice process, focusing instead on choice outcomes. This is consistent with the traditional focus of the economics profession as a whole on the specific decisions themselves, but has also in part been due to the technological limitations of collecting process data. The equipment for measurement can be expensive and knowledge may be lacking in terms of data analysis best practices. Some recent developments have changed the landscape and brought process data to the forefront of experimental research. First, the measurement technology has improved substantially in quality, availability, and relevance in the marketplace. For example, as little as 15 years ago, eye-tracking involved subjects wearing equipment that was strapped to their heads, with tiny cameras sitting just centimeters below their eyes. Setups would cost many thousands of dollars and had limited temporal and spatial resolution. These days, eye-trackers are sold commercially (e.g., for videogaming) and can be purchased for as little as $100. Modern eye-tracking cameras can fit in your pocket and sit innocuously below the computer monitor. Moreover, with an ever-increasing fraction of economic transactions occurring online and most "smart" devices already built with backward facing cameras (and other biosensors), it is only a matter of time before these data are readily available alongside standard browsing and purchasing data. Second, as economists use behavioral insights and data to refine their theories of decision-making, a clear scientific role for process data has emerged. For example, the now prominent topic of rational inattention makes predictions that relate decision processes to outcomes (Caplin and Dean 2015). These predictions can be readily tested using established process-tracing tools. Third, field and online experiments have emerged in the last 15 years and made substantial impacts on experimental economics. To best complement work in the field and online, laboratory experimenters must leverage their comparative advantage, namely having subjects in a controlled laboratory setting. Process data, which are considerably more difficult to collect in the field, are conducive to laboratory methods. This comparative advantage buttresses the tendency for studies using process data to make up an increasing share of the laboratory experiments that are conducted. 3 Some types of choice-process data that have been studied There are many dimensions of the choice process that can be studied. These methods vary in their accessibility, their intrusiveness, and what they can reveal. They range from the readily observable and unidimensional, e.g., response times, to the complex and high-dimensional, e.g., brain activation patterns or verbal communication. Below, we briefly review the most common measures and highlight recent advances using these methods.

Nature Communications, 2018

Social decision making involves balancing conflicts between selfishness and pro-sociality. The co... more Social decision making involves balancing conflicts between selfishness and pro-sociality. The cognitive processes underlying such decisions are not well understood, with some arguing for a single comparison process, while others argue for dual processes (one intuitive and one deliberative). Here, we propose a way to reconcile these two opposing frameworks. We argue that behavior attributed to intuition can instead be seen as a starting point bias of a sequential sampling model (SSM) process, analogous to a prior in a Bayesian framework. Using mini-dictator games in which subjects make binary decisions about how to allocate money between themselves and another participant, we find that pro-social subjects become more pro-social under time pressure and less pro-social under time delay, while selfish subjects do the opposite. Our findings help reconcile the conflicting results concerning the cognitive processes of social decision making and highlight the importance of modeling the dyn...

SSRN Electronic Journal, 2017

Revealed preference is the dominant approach for inferring preferences, but it relies on discrete... more Revealed preference is the dominant approach for inferring preferences, but it relies on discrete, stochastic choices. The choice process also produces response times (RTs) which are continuous and can often be observed in the absence of informative choice outcomes. Moreover, there is a consistent relationship between RTs and strength-of-preference, namely that people make slower decisions as they approach indifference. This relationship arises from optimal solutions to sequential information sampling problems. Here, we investigate several ways in which this relationship can be used to infer preferences when choice outcomes are uninformative or unavailable. We show that RTs from a single twoalternative choice problem can be enough to usefully rank people according to their degree of loss aversion. Using a large number of choice problems, we are further able to recover individual utility-function parameters from RTs alone (no choice outcomes) in three different choice domains. Finally, we are able to use long RTs to predict which choices are inconsistent with a subject's utility function and likely to later be reversed. These results provide a proof of concept for a novel "method of revealed indifference".

Psychological Science, 2019

In the original article, the graphs in Figs. 4a and 4b were inadvertently reversed. This Corrigen... more In the original article, the graphs in Figs. 4a and 4b were inadvertently reversed. This Corrigendum is correcting that error: Fig. 4a will now be the graph for the multiplicative model, and Fig. 4b will now be the graph for the additive model, as identified in the original figure caption and related discussion in the text.

Nature Human Behaviour, 2019

Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch ge... more Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden. Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen. Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. Terms of use: Documents in EconStor may be saved and copied for your personal and scholarly purposes. You are not to copy documents for public or commercial purposes, to exhibit the documents publicly, to make them publicly available on the internet, or to distribute or otherwise use the documents in public.

Journal of the Economic Science Association, 2019

When making decisions, people tend to look back and forth between the alternatives until eventual... more When making decisions, people tend to look back and forth between the alternatives until eventually making a choice. Eye-tracking research has established that these shifts in attention are strongly linked to choice outcomes. A predominant framework for understanding the dynamics of the choice process, and thus the effects of attention, is sequential sampling of information. However, existing methods for estimating the attention parameters in these models are computationally costly and overly flexible, and yield estimates with unknown precision and bias. Here we propose an estimation method that relies on a link between sequential sampling models and random utility models (RUM). This method uses familiar econometric tools (i.e. Logit regression) and yields estimates that appear to be unbiased and relatively precise compared to existing methods, in a small fraction of the computation time. The RUM thus appears to be a useful tool for estimating the effects of attention on choice.

Nature Communications, 2016

Organisms appear to learn and make decisions using different strategies known as model-free and m... more Organisms appear to learn and make decisions using different strategies known as model-free and model-based learning; the former is mere reinforcement of previously rewarded actions and the latter is a forward-looking strategy that involves evaluation of action-state transition probabilities. Prior work has used neural data to argue that both model-based and model-free learners implement a value comparison process at trial onset, but model-based learners assign more weight to forward-looking computations. Here using eye-tracking, we report evidence for a different interpretation of prior results: model-based subjects make their choices prior to trial onset. In contrast, model-free subjects tend to ignore model-based aspects of the task and instead seem to treat the decision problem as a simple comparison process between two differentially valued items, consistent with previous work on sequential-sampling models of decision making. These findings illustrate a problem with assuming th...

Proceedings of the National Academy of Sciences of the United States of America, Jan 2, 2017

Models of reinforcement learning (RL) are prevalent in the decision-making literature, but not al... more Models of reinforcement learning (RL) are prevalent in the decision-making literature, but not all behavior seems to conform to the gradual convergence that is a central feature of RL. In some cases learning seems to happen all at once. Limited prior research on these "epiphanies" has shown evidence of sudden changes in behavior, but it remains unclear how such epiphanies occur. We propose a sequential-sampling model of epiphany learning (EL) and test it using an eye-tracking experiment. In the experiment, subjects repeatedly play a strategic game that has an optimal strategy. Subjects can learn over time from feedback but are also allowed to commit to a strategy at any time, eliminating all other options and opportunities to learn. We find that the EL model is consistent with the choices, eye movements, and pupillary responses of subjects who commit to the optimal strategy (correct epiphany) but not always of those who commit to a suboptimal strategy or who do not commit ...

Organizational Research Methods, 2016

At its inception, neuroeconomics promised to revolutionize economics. That promise has not yet be... more At its inception, neuroeconomics promised to revolutionize economics. That promise has not yet been realized, and neuroeconomics has seen limited penetration into mainstream economics. Nevertheless, it would be a mistake to declare that neuroeconomics has failed. Quite to the contrary, the yearly rate of neuroeconomics papers has roughly doubled since 2005. While the number of direct applications to economics remains limited, due to the infancy of the field, we have learned an amazing amount about how the brain makes decisions. In this article, we review some of the major topics that have emerged in neuroeconomics and highlight findings that we believe will form the basis for future applications to economics. When possible, we focus on existing applications to economics and future directions for that research.

Proceedings of the Royal Society B: Biological Sciences, 2016

Time is an extremely valuable resource but little is known about the efficiency of time allocatio... more Time is an extremely valuable resource but little is known about the efficiency of time allocation in decision-making. Empirical evidence suggests that in many ecologically relevant situations, decision difficulty and the relative reward from making a correct choice, compared to an incorrect one, are inversely linked, implying that it is optimal to use relatively less time for difficult choice problems. This applies, in particular, to value-based choices, in which the relative reward from choosing the higher valued item shrinks as the values of the other options get closer to the best option and are thus more difficult to discriminate. Here, we experimentally show that people behave sub-optimally in such contexts. They do not respond to incentives that favour the allocation of time to choice problems in which the relative reward for choosing the best option is high; instead they spend too much time on problems in which the reward difference between the options is low. We demonstrate...

Neuron, 2018

Highlights d Human subjects learn to detect patterns in sequences of images while undergoing fMRI... more Highlights d Human subjects learn to detect patterns in sequences of images while undergoing fMRI d Behavior is well explained by a Bayesian patternlearning model d Distinct networks track uncertainty about the pattern and the predicted image

Judgment and Decision Making

A core principle in decision science is that people choose according to their subjective values. ... more A core principle in decision science is that people choose according to their subjective values. These values are often measured using unincentivized scales with arbitrary units (e.g., from 0 to 10) or using incentivized willingness-to-pay (WTP) with dollars and cents. What is unclear is whether using WTP actually improves choice predictions. In two experiments, we compare the effects of three different subjective valuation procedures: an unincentivized rating scale, the same scale with incentives, and incentivized WTP. We use these subjective values to predict behavior in a subsequent binary food-choice task. The unincentivized rating task performed better than the incentivized WTP task and no worse than the incentivized rating task. These findings challenge the view that subjective valuation tasks need to be incentivized. At least for low-stakes decisions, commonly used measures such as WTP may reduce predictive power.

Judgment and Decision Making

Revealed preference is the dominant approach for inferring preferences, but it is limited in that... more Revealed preference is the dominant approach for inferring preferences, but it is limited in that it relies solely on discrete choice data. When a person chooses one alternative over another, we cannot infer the strength of their preference or predict how likely they will be to make the same choice again. However, the choice process also produces response times (RTs), which are continuous and easily observable. It has been shown that RTs often decrease with strength-of-preference. This is a basic property of sequential sampling models such as the drift diffusion model. What remains unclear is whether this relationship is sufficiently strong, relative to the other factors that affect RTs, to allow us to reliably infer strength-of-preference across individuals. Using several experiments, we show that even when every subject chooses the same alternative, we can still rank them based on their RTs and predict their behavior on other choice problems. We can also use RTs to predict whether...

Psychological Review, 2022

for comments, and to Stephanie Smith, Marios Philiastides and Bernd Weber for sharing their data.... more for comments, and to Stephanie Smith, Marios Philiastides and Bernd Weber for sharing their data. I.K. gratefully acknowledges financial support from National Science Foundation Career Grant No.

Recent studies have suggested close functional links between visual attention and decision making... more Recent studies have suggested close functional links between visual attention and decision making. This suggests that the corresponding mechanisms may interface in brain regions known to be crucial for guiding visual attention – such as the frontal eye field (FEF). Here, we combined brain stimulation, eye tracking and computational approaches to explore this possibility. We show that inhibitory transcranial magnetic stimulation (TMS) over the right FEF has a causal impact on decision-making, reducing the effect of gaze dwell time on choice while also increasing reaction times. We computationally characterize this putative mechanism by using the attentional drift diffusion model (aDDM), which reveals that FEF inhibition reduces the relative discounting of the non-fixated option in the comparison process. Our findings establish an important causal role of the right FEF in choice, elucidate the underlying mechanism, and provide support for one of the key causal hypotheses associated wi...

Time is an extremely valuable resource but little is known about the efficiency of time allocatio... more Time is an extremely valuable resource but little is known about the efficiency of time allocation in decision-making. Empirical evidence suggests that in many ecologically relevant situations, decision difficulty and the relative reward from making a correct choice, compared to an incorrect one, are inversely linked, implying that it is optimal to use relatively less time for difficult choice problems. This applies, in particular, to value-based choices, in which the relative reward from choosing the higher valued item shrinks as the values of the other options get closer to the best option and are thus more difficult to discriminate. Here, we experimentally show that people behave sub-optimally in such contexts. They do not respond to incentives that favour the allocation of time to choice problems in which the relative reward for choosing the best option is high; instead they spend too much time on problems in which the reward difference between the options is low. We demonstrate...

The young field of neuroeconomics has already produced many important insights into the neurobiol... more The young field of neuroeconomics has already produced many important insights into the neurobiological underpinnings of decision making. However, at this early stage it is still unclear how much influence the field will have on mainstream economics. Here, I show how a neuroeconomics approach can shed light on two classic economic problems. First, I show that it is possible to predict individuals’ values for public goods, using functional magnetic resonance imaging (fMRI)-based pattern classification. With such predictions in hand, I demonstrate that it is possible to solve the free-rider problem, by taxing individuals based both on the values that they themselves report and on the predicted values (using fMRI). I go on to more generally prove that by using any informative signal of value, it is possible to overcome classic impossibility results in mechanism design. This allows us to construct mechanisms that simultaneously satisfy dominant strategy incentive compatibility, voluntar...

Experiments are increasingly moving online. This poses a major challenge for researchers who rely... more Experiments are increasingly moving online. This poses a major challenge for researchers who rely on in-lab techniques such as eye-tracking. Researchers in computer science have developed web-based eye-tracking applications (WebGazer; Papoutsaki et al., 2016) but they have yet to see use in behavioral research. This is likely due to the extensive calibration and validation procedure, inconsistent temporal resolution (Semmelmann & Weigelt, 2018), and the challenge of integrating it into experimental software. Here, we incorporate WebGazer into a widely used JavaScript library among behavioral researchers (jsPsych) and adjust the procedure and code to reduce calibration/validation and improve the temporal resolution (from 100-1000 ms to 20-30 ms). We test this procedure with a decision-making study on Amazon MTurk, replicating previous in-lab findings on the relationship between gaze and choice, with little degradation in spatial or temporal resolution. This provides evidence that onl...

Proceedings of the National Academy of Sciences, 2020

SignificanceChoices that consist of risky versus certain options are pervasive and consequential,... more SignificanceChoices that consist of risky versus certain options are pervasive and consequential, leading many researchers to investigate when and which individuals select risk over certainty. The present research takes an alternative approach and measures computer mouse movements to assess how people arrive at these decisions. We show that measuring mouse movements while participants are deciding between a risky gamble and a certain payout powerfully detects their conflict about the options, and that this conflict strongly predicts their risk preferences. Further, mouse movements are predictive of risk preferences even when choice outcomes are not. The present research thus demonstrates the unique utility of dynamic measures of choice, as well as the predictive and theoretical importance of conflict in risky decision-making.

How do we choose when confronted with many alternatives (e.g., choosing which soda to buy at the ... more How do we choose when confronted with many alternatives (e.g., choosing which soda to buy at the supermarket)? While studies of the decision mechanisms underlying two- to three-alternative choice are common in the literature, there is comparably little decision modeling work with larger 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 comparing these models in a many-alternative value-based choice experiment with 9, 16, 25 or 36 choice alternatives. We find that human subjects' choice behaviour does not match the assumptions of satisficing or optimal choice, while a hybrid of the two captures response times and choices well. Yet, only a process of gaze-driven evidence accumulation is able to...

Journal of the Economic Science Association, 2019

Until recently, research in experimental economics had largely ignored the choice process, focusi... more Until recently, research in experimental economics had largely ignored the choice process, focusing instead on choice outcomes. This is consistent with the traditional focus of the economics profession as a whole on the specific decisions themselves, but has also in part been due to the technological limitations of collecting process data. The equipment for measurement can be expensive and knowledge may be lacking in terms of data analysis best practices. Some recent developments have changed the landscape and brought process data to the forefront of experimental research. First, the measurement technology has improved substantially in quality, availability, and relevance in the marketplace. For example, as little as 15 years ago, eye-tracking involved subjects wearing equipment that was strapped to their heads, with tiny cameras sitting just centimeters below their eyes. Setups would cost many thousands of dollars and had limited temporal and spatial resolution. These days, eye-trackers are sold commercially (e.g., for videogaming) and can be purchased for as little as $100. Modern eye-tracking cameras can fit in your pocket and sit innocuously below the computer monitor. Moreover, with an ever-increasing fraction of economic transactions occurring online and most "smart" devices already built with backward facing cameras (and other biosensors), it is only a matter of time before these data are readily available alongside standard browsing and purchasing data. Second, as economists use behavioral insights and data to refine their theories of decision-making, a clear scientific role for process data has emerged. For example, the now prominent topic of rational inattention makes predictions that relate decision processes to outcomes (Caplin and Dean 2015). These predictions can be readily tested using established process-tracing tools. Third, field and online experiments have emerged in the last 15 years and made substantial impacts on experimental economics. To best complement work in the field and online, laboratory experimenters must leverage their comparative advantage, namely having subjects in a controlled laboratory setting. Process data, which are considerably more difficult to collect in the field, are conducive to laboratory methods. This comparative advantage buttresses the tendency for studies using process data to make up an increasing share of the laboratory experiments that are conducted. 3 Some types of choice-process data that have been studied There are many dimensions of the choice process that can be studied. These methods vary in their accessibility, their intrusiveness, and what they can reveal. They range from the readily observable and unidimensional, e.g., response times, to the complex and high-dimensional, e.g., brain activation patterns or verbal communication. Below, we briefly review the most common measures and highlight recent advances using these methods.

Nature Communications, 2018

Social decision making involves balancing conflicts between selfishness and pro-sociality. The co... more Social decision making involves balancing conflicts between selfishness and pro-sociality. The cognitive processes underlying such decisions are not well understood, with some arguing for a single comparison process, while others argue for dual processes (one intuitive and one deliberative). Here, we propose a way to reconcile these two opposing frameworks. We argue that behavior attributed to intuition can instead be seen as a starting point bias of a sequential sampling model (SSM) process, analogous to a prior in a Bayesian framework. Using mini-dictator games in which subjects make binary decisions about how to allocate money between themselves and another participant, we find that pro-social subjects become more pro-social under time pressure and less pro-social under time delay, while selfish subjects do the opposite. Our findings help reconcile the conflicting results concerning the cognitive processes of social decision making and highlight the importance of modeling the dyn...

SSRN Electronic Journal, 2017

Revealed preference is the dominant approach for inferring preferences, but it relies on discrete... more Revealed preference is the dominant approach for inferring preferences, but it relies on discrete, stochastic choices. The choice process also produces response times (RTs) which are continuous and can often be observed in the absence of informative choice outcomes. Moreover, there is a consistent relationship between RTs and strength-of-preference, namely that people make slower decisions as they approach indifference. This relationship arises from optimal solutions to sequential information sampling problems. Here, we investigate several ways in which this relationship can be used to infer preferences when choice outcomes are uninformative or unavailable. We show that RTs from a single twoalternative choice problem can be enough to usefully rank people according to their degree of loss aversion. Using a large number of choice problems, we are further able to recover individual utility-function parameters from RTs alone (no choice outcomes) in three different choice domains. Finally, we are able to use long RTs to predict which choices are inconsistent with a subject's utility function and likely to later be reversed. These results provide a proof of concept for a novel "method of revealed indifference".

Psychological Science, 2019

In the original article, the graphs in Figs. 4a and 4b were inadvertently reversed. This Corrigen... more In the original article, the graphs in Figs. 4a and 4b were inadvertently reversed. This Corrigendum is correcting that error: Fig. 4a will now be the graph for the multiplicative model, and Fig. 4b will now be the graph for the additive model, as identified in the original figure caption and related discussion in the text.

Nature Human Behaviour, 2019

Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch ge... more Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden. Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen. Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. Terms of use: Documents in EconStor may be saved and copied for your personal and scholarly purposes. You are not to copy documents for public or commercial purposes, to exhibit the documents publicly, to make them publicly available on the internet, or to distribute or otherwise use the documents in public.

Journal of the Economic Science Association, 2019

When making decisions, people tend to look back and forth between the alternatives until eventual... more When making decisions, people tend to look back and forth between the alternatives until eventually making a choice. Eye-tracking research has established that these shifts in attention are strongly linked to choice outcomes. A predominant framework for understanding the dynamics of the choice process, and thus the effects of attention, is sequential sampling of information. However, existing methods for estimating the attention parameters in these models are computationally costly and overly flexible, and yield estimates with unknown precision and bias. Here we propose an estimation method that relies on a link between sequential sampling models and random utility models (RUM). This method uses familiar econometric tools (i.e. Logit regression) and yields estimates that appear to be unbiased and relatively precise compared to existing methods, in a small fraction of the computation time. The RUM thus appears to be a useful tool for estimating the effects of attention on choice.

Nature Communications, 2016

Organisms appear to learn and make decisions using different strategies known as model-free and m... more Organisms appear to learn and make decisions using different strategies known as model-free and model-based learning; the former is mere reinforcement of previously rewarded actions and the latter is a forward-looking strategy that involves evaluation of action-state transition probabilities. Prior work has used neural data to argue that both model-based and model-free learners implement a value comparison process at trial onset, but model-based learners assign more weight to forward-looking computations. Here using eye-tracking, we report evidence for a different interpretation of prior results: model-based subjects make their choices prior to trial onset. In contrast, model-free subjects tend to ignore model-based aspects of the task and instead seem to treat the decision problem as a simple comparison process between two differentially valued items, consistent with previous work on sequential-sampling models of decision making. These findings illustrate a problem with assuming th...

Proceedings of the National Academy of Sciences of the United States of America, Jan 2, 2017

Models of reinforcement learning (RL) are prevalent in the decision-making literature, but not al... more Models of reinforcement learning (RL) are prevalent in the decision-making literature, but not all behavior seems to conform to the gradual convergence that is a central feature of RL. In some cases learning seems to happen all at once. Limited prior research on these "epiphanies" has shown evidence of sudden changes in behavior, but it remains unclear how such epiphanies occur. We propose a sequential-sampling model of epiphany learning (EL) and test it using an eye-tracking experiment. In the experiment, subjects repeatedly play a strategic game that has an optimal strategy. Subjects can learn over time from feedback but are also allowed to commit to a strategy at any time, eliminating all other options and opportunities to learn. We find that the EL model is consistent with the choices, eye movements, and pupillary responses of subjects who commit to the optimal strategy (correct epiphany) but not always of those who commit to a suboptimal strategy or who do not commit ...

Organizational Research Methods, 2016

At its inception, neuroeconomics promised to revolutionize economics. That promise has not yet be... more At its inception, neuroeconomics promised to revolutionize economics. That promise has not yet been realized, and neuroeconomics has seen limited penetration into mainstream economics. Nevertheless, it would be a mistake to declare that neuroeconomics has failed. Quite to the contrary, the yearly rate of neuroeconomics papers has roughly doubled since 2005. While the number of direct applications to economics remains limited, due to the infancy of the field, we have learned an amazing amount about how the brain makes decisions. In this article, we review some of the major topics that have emerged in neuroeconomics and highlight findings that we believe will form the basis for future applications to economics. When possible, we focus on existing applications to economics and future directions for that research.

Proceedings of the Royal Society B: Biological Sciences, 2016

Time is an extremely valuable resource but little is known about the efficiency of time allocatio... more Time is an extremely valuable resource but little is known about the efficiency of time allocation in decision-making. Empirical evidence suggests that in many ecologically relevant situations, decision difficulty and the relative reward from making a correct choice, compared to an incorrect one, are inversely linked, implying that it is optimal to use relatively less time for difficult choice problems. This applies, in particular, to value-based choices, in which the relative reward from choosing the higher valued item shrinks as the values of the other options get closer to the best option and are thus more difficult to discriminate. Here, we experimentally show that people behave sub-optimally in such contexts. They do not respond to incentives that favour the allocation of time to choice problems in which the relative reward for choosing the best option is high; instead they spend too much time on problems in which the reward difference between the options is low. We demonstrate...