Accounting for attention in sequential sampling models of decision making

Sequential Tests of Statistical Hypotheses

Wald, A. (1945) · The Annals of Mathematical Statistics · doi:10.1214/aoms/1177731118 · Cited by 1,679 · see citing works

Diffusion decision model: Current issues and history

Ratcliff, R., Smith, P. L., Brown, S. D., & McKoon, G. (2016) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2016.01.007 · Cited by 1,630 · see citing works

Visual fixations and the computation and comparison of value in simple choice

Krajbich, I., Armel, C., & Rangel, A. (2010) · Nature Neuroscience · doi:10.1038/nn.2635 · Cited by 1,408 · see citing works

Sequential Tests of Statistical Hypotheses

Wald, A. (1992) · Springer series in statistics · doi:10.1007/978-1-4612-0919-5_18 · Cited by 1,365 · see citing works

Gaze bias both reflects and influences preference

Shimojo, S., Simion, C., Shimojo, E., & Scheier, C. (2003) · Nature Neuroscience · doi:10.1038/nn1150 · Cited by 924 · see citing works

Multialternative decision field theory: A dynamic connectionst model of decision making.

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

Krajbich, I. M., & Rangel, A. (2011) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1101328108 · Cited by 732 · see citing works

Sequential Sampling Models in Cognitive Neuroscience: Advantages, Applications, and Extensions

Forstmann, B. U., Ratcliff, R., & Wagenmakers, E. (2015) · Annual Review of Psychology · doi:10.1146/annurev-psych-122414-033645 · Cited by 613 · see citing works

Biasing simple choices by manipulating relative visual attention

Armel, K. C., Beaumel, A., & Rangel, A. (2008) · Judgment and Decision Making · doi:10.1017/s1930297500000413 · Cited by 420 · see citing works

Decision Making and Sequential Sampling from Memory

Shadlen, M. N., & Shohamy, D. (2016) · Neuron · doi:10.1016/j.neuron.2016.04.036 · Cited by 412 · see citing works

Perceptual Decision Making in Rodents, Monkeys, and Humans

Hanks, T. D., & Summerfield, C. (2017) · Neuron · doi:10.1016/j.neuron.2016.12.003 · Cited by 388 · see citing works

The decision value computations in the vmPFC and striatum use a relative value code that is guided by visual attention

Lim, S.-L., O'Doherty, J. P., & Rangel, A. (2011) · The Journal of Neuroscience · doi:10.1523/jneurosci.1246-11.2011 · Cited by 329 · see citing works

Eye tracking and pupillometry are indicators of dissociable latent decision processes.

Cavanagh, J. F., Wiecki, T. V., Kochar, A., & Frank, M. J. (2014) · Journal of Experimental Psychology: General · doi:10.1037/a0035813 · Cited by 289 · see citing works

The multiattribute linear ballistic accumulator model of context effects in multialternative choice.

Trueblood, J. S., Brown, S. D., & Heathcote, A. (2014) · Psychological Review · doi:10.1037/a0036137 · Cited by 272 · see citing works

Simultaneous modeling of visual saliency and value computation improves predictions of economic choice

Towal, R. B., Mormann, M. M., & Christof Koch, A. (2013) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1304429110 · Cited by 254 · see citing works

Dynamic Stochastic Models for Decision Making under Time Constraints

Diederich, A. (1997) · Journal of Mathematical Psychology · doi:10.1006/jmps.1997.1167 · Cited by 244 · see citing works

Biasing moral decisions by exploiting the dynamics of eye gaze

Pärnamets, P., Johansson, P., Hall, L., Balkenius, C., Spivey, M. J., & Richardson, D. C. (2015) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1415250112 · Cited by 219 · see citing works

Optimal policy for value-based decision-making

Tajima, S., Drugowitsch, J., & Pouget, A. (2016) · Nature Communications · doi:10.1038/ncomms12400 · Cited by 209 · see citing works

Eye Movements in Risky Choice

Stewart, N., Hermens, F., & Matthews, W. J. (2015) · Journal of Behavioral Decision Making · doi:10.1002/bdm.1854 · Cited by 152 · see citing works

Multialternative decision by sampling: A model of decision making constrained by process data.

Noguchi, T., & Stewart, N. (2018) · Psychological Review · doi:10.1037/rev0000102 · Cited by 149 · see citing works

Modulation of Premotor and Primary Motor Cortical Activity during Volitional Adjustments of Speed-Accuracy Trade-Offs

Thura, D., & Cisek, P. (2016) · Journal of Neuroscience · doi:10.1523/jneurosci.2230-15.2016 · Cited by 148 · see citing works

Search for Information on Multiple Products

Ke, T. T., Shen, Z. M., & Villas‐Boas, J. M. (2016) · Management Science · doi:10.1287/mnsc.2015.2316 · Cited by 145 · see citing works

The Attentional Drift Diffusion Model of Simple Perceptual Decision-Making

Tavares, G., Perona, P., & Rangel, A. (2017) · Frontiers in Neuroscience · doi:10.3389/fnins.2017.00468 · Cited by 145 · see citing works

Eye Tracking Reveals Processes that Enable Conjoint Choices to Become Increasingly Efficient with Practice

Meißner, M., Musalem, A., & Huber, J. C. (2015) · Journal of Marketing Research · doi:10.1509/jmr.13.0467 · Cited by 139 · see citing works

Prospect theory reflects selective allocation of attention.

Pachur, T., Schulte‐Mecklenbeck, M., Murphy, R. O., & Hertwig, R. (2018) · Journal of Experimental Psychology General · doi:10.1037/xge0000406 · Cited by 122 · see citing works

Attention and choice across domains.

Smith, S. M., & Krajbich, I. M. (2018) · Journal of Experimental Psychology General · doi:10.1037/xge0000482 · Cited by 121 · see citing works

Gaze bias differences capture individual choice behaviour

Thomas, A. W., Molter, F., Krajbich, I. M., Heekeren, H. R., & Mohr, P. N. C. (2019) · Nature Human Behaviour · doi:10.1038/s41562-019-0584-8 · Cited by 116 · see citing works

Orbitofrontal Cortex Value Signals Depend on Fixation Location during Free Viewing

McGinty, V. B., Rangel, A., & Newsome, W. T. (2016) · Neuron · doi:10.1016/j.neuron.2016.04.045 · Cited by 112 · see citing works

Competing theories of multialternative, multiattribute preferential choice.

Turner, B. M., Schley, D. R., Muller, C. G., & Tsetsos, K. (2017) · Psychological Review · doi:10.1037/rev0000089 · Cited by 106 · see citing works

Improving Out-of-Sample Predictions Using Response Times and a Model of the Decision ProcessPreprint

Clithero, J. A. (2016) · SSRN Electronic Journal · doi:10.1016/j.jebo.2018.02.007 · Cited by 99 · see citing works

Goal-directed visual attention drives health goal priming: An eye-tracking experiment.

van der Laan, L. N., Papies, E. K., Hooge, I. T. C., & Smeets, P. A. M. (2016) · Health Psychology · doi:10.1037/hea0000410 · Cited by 97 · see citing works

An attentional drift diffusion model over binary-attribute choice

Fisher, G. (2017) · Cognition · doi:10.1016/j.cognition.2017.06.007 · Cited by 92 · see citing works

Gaze data reveal distinct choice processes underlying model-based and model-free reinforcement learning

Konovalov, A., & Krajbich, I. M. (2016) · Nature Communications · doi:10.1038/ncomms12438 · Cited by 86 · see citing works

Visual attention in multi-attributes choices: What can eye-tracking tell us?

Krucien, N., Ryan, M., & Hermens, F. (2017) · Journal of Economic Behavior & Organization · doi:10.1016/j.jebo.2017.01.018 · Cited by 79 · see citing works

Tastiness but not healthfulness captures automatic visual attention: Preliminary evidence from an eye-tracking study

Motoki, K., Saito, T. I., Nouchi, R., Kawashima, R., & Sugiura, M. (2017) · Food Quality and Preference · doi:10.1016/j.foodqual.2017.09.014 · Cited by 73 · see citing works

Eye‐tracking Social Preferences

Jiang, T. X., Potters, J., & Funaki, Y. (2015) · Journal of Behavioral Decision Making · doi:10.1002/bdm.1899 · Cited by 67 · see citing works

Salient nutrition labels increase the integration of health attributes in food decision-making

Enax, L., Krajbich, I. M., & Weber, B. (2016) · Judgment and Decision Making · doi:10.1017/s1930297500004563 · Cited by 66 · see citing works

The eyes have it: Using eye tracking to inform information processing strategies in multi‐attributes choices

Ryan, M., Krucien, N., & Hermens, F. (2017) · Health Economics · doi:10.1002/hec.3626 · Cited by 63 · see citing works

Testing necessary regional frontal contributions to value assessment and fixation-based updating

Vaidya, A. R., & Fellows, L. K. (2015) · Nature Communications · doi:10.1038/ncomms10120 · Cited by 56 · see citing works

Examining the relationship between visual attention and stated preferences: A discrete choice experiment using eye-tracking

Balcombe, K., Fraser, I., Williams, L., et al. (2017) · Journal of Economic Behavior & Organization · doi:10.1016/j.jebo.2017.09.023 · Cited by 54 · see citing works

The influence of attention on value integration

Kunar, M. A., Watson, D. G., Tsetsos, K., & Nick Chater, A. (2017) · Attention Perception & Psychophysics · doi:10.3758/s13414-017-1340-7 · Cited by 52 · see citing works

Perceptual but not complex moral judgments can be biased by exploiting the dynamics of eye-gaze.

Newell, B. R., & Pelley, M. E. L. (2018) · Journal of Experimental Psychology General · doi:10.1037/xge0000386 · Cited by 50 · see citing works

Implications of visual attention phenomena for models of preferential choice.

Mullett, T. L., & Stewart, N. (2016) · Decision · doi:10.1037/dec0000049 · Cited by 44 · see citing works

Bayesian analysis of the piecewise diffusion decision model

Holmes, W. R., & Trueblood, J. S. (2017) · Behavior Research Methods · doi:10.3758/s13428-017-0901-y · Cited by 41 · see citing works

Multi-attribute, multi-alternative models of choice: Choice, reaction time, and process tracing

Cohen, A. L., Kang, N., & Leise, T. (2017) · Cognitive Psychology · doi:10.1016/j.cogpsych.2017.08.001 · Cited by 39 · see citing works

Finding the right fit: A comparison of process assumptions underlying popular drift-diffusion models.

Ashby, N. J. S., Jekel, M., Dickert, S., & Glöckner, A. (2016) · Journal of Experimental Psychology Learning Memory and Cognition · doi:10.1037/xlm0000279 · Cited by 32 · see citing works

Multi-stage sequential sampling models with finite or infinite time horizon and variable boundaries

Diederich, A., & Oswald, P. (2016) · Journal of Mathematical Psychology · doi:10.1016/j.jmp.2016.02.010 · Cited by 31 · see citing works

The Role of Salience and Attention in Choice under Risk: An Experimental InvestigationPreprint

Mormann, M. M. (2016) · SSRN Electronic Journal · doi:10.2139/ssrn.2778822 · Cited by 31 · see citing works

A computational model of the attention process in risky choice.

Johnson, J. G., & Busemeyer, J. R. (2016) · Decision · doi:10.1037/dec0000050 · Cited by 30 · see citing works

Attentional accounting: Voluntary spatial attention increases budget category prioritization.

Mrkva, K., & Leaf Van Boven, A. (2017) · Journal of Experimental Psychology General · doi:10.1037/xge0000347 · Cited by 28 · see citing works

Value-based decision making via sequential sampling with hierarchical competition and attentional modulation

Colas, J. T. (2017) · PLoS ONE · doi:10.1371/journal.pone.0186822 · Cited by 19 · see citing works

Gaze Bias Differences Capture Individual Choice BehaviorPreprint

Thomas, A. W., Molter, F., Krajbich, I., Heekeren, H., & Mohr, P. N. C. (2017) · bioRxiv · doi:10.1101/228825 · Cited by 13 · see citing works

Information foraging for perceptual decisions.

Ludwig, C. J. H., & Evens, D. R. (2016) · Journal of Experimental Psychology Human Perception & Performance · doi:10.1037/xhp0000299 · Cited by 12 · see citing works

Learning Where to Look for High Value Improves Decision Making Asymmetrically

Colas, J., & Lu, J. (2017) · Frontiers in Psychology · doi:10.3389/fpsyg.2017.02000 · Cited by 11 · see citing works

Paying attention to attention in depression

Keller, A. S., Leikauf, J. E., Holt-Gosselin, B., Staveland, B. R., & Williams, L. M. (2019) · Translational Psychiatry · doi:10.1038/s41398-019-0616-1 · Cited by 329 · see citing works

Interpretable abstractions of artificial neural networks predict behavior and neural activity during human information gathering

D’Ambrogio, S., Grohn, J., Khalighinejad, N., Mattar, M. G., Hunt, L., & Rushworth, M. F. S. (2026) · Nature Neuroscience · doi:10.1038/s41593-026-02342-9 · Cited by 1 · see citing works

Susquehanna Chorale Spring Concert "Roots and Wings"

Hawkins, D. (2017)

Keeping Conflicts Latent: "Salient" versus "Non-Salient" Interpersonal Conflict Management Strategies of Japanese

Nakatsugawa, S. (2013) · Cited by 5 · see citing works

A Computational Method to Find Salient Features

(2008)

Detecting Salient Regions Based on "What" and "Where" Pathways of Visual Systems

(2006)

An algorithm to cluster the search results based-on the association rules

(2006)