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Cherkasova, M. V., Clark, L., Barton, J. J. S., Schulzer, M., Shafiee, M., Kingstone, A. F., Stoessl, A. J., & Winstanley, C. A. (2018) · Journal of Neuroscience · doi:10.1523/jneurosci.1171-18.2018 · Cited by 58 · see citing works

Auditory information enhances post-sensory visual evidence during rapid multisensory decision-making

Franzen, L., Delis, I., De Sousa, G., Kayser, C., & Philiastides, M. G. (2020) · Nature Communications · doi:10.1038/s41467-020-19306-7 · Cited by 57 · see citing works

Irrational time allocation in decision-making

Oud, B., Krajbich, I. M., Miller, K. J., Cheong, J. H., Botvinick, M., & Fehr, E. (2016) · Proceedings of the Royal Society B Biological Sciences · doi:10.1098/rspb.2015.1439 · Cited by 51 · see citing works

Applications and Innovations of Eye‐movement Research in Judgment and Decision Making

Ashby, N. J. S., Johnson, J. G., Krajbich, I. M., & Wedel, M. (2016) · Journal of Behavioral Decision Making · doi:10.1002/bdm.1956 · Cited by 54 · see citing works

Computational modeling of epiphany learning

Chen, W. J., & Krajbich, I. M. (2017) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1618161114 · Cited by 52 · see citing works

High-value decisions are fast and accurate, inconsistent with diminishing value sensitivity

Shevlin, B. R. K., Smith, S. M., Hausfeld, J., & Krajbich, I. M. (2022) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2101508119 · Cited by 57 · see citing works

Filling the gaps: Cognitive control as a critical lens for understanding mechanisms of value-based decision-making

Frömer, R., & Shenhav, A. (2021) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2021.12.006 · Cited by 50 · see citing works

A Computational Cognitive Biomarker for Early-Stage Huntington’s Disease

Wiecki, T. V., Antoniades, C. A., Stevenson, A. D., Christopher Kennard, C., Borowsky, B., Owen, G. N., Leavitt, B. R., Roos, R. A. C., Dürr, A., Tabrizi, S. J., et al. (2016) · PLoS ONE · doi:10.1371/journal.pone.0148409 · Cited by 51 · see citing works

How similarity between choice options affects decisions from experience: The accentuation-of-differences model.

Spektor, M. S., Gluth, S., Fontanesi, L., & Rieskamp, J. (2019) · Psychological Review · doi:10.1037/rev0000122 · Cited by 51 · see citing works

Aberrant decision-making and drug addiction — how strong is the evidence?

Ekhtiari, H., Victor, T. A., & Paulus, M. P. (2016) · Current Opinion in Behavioral Sciences · doi:10.1016/j.cobeha.2016.09.002 · Cited by 48 · see citing works

Error-related pupil dilation is sensitive to the evaluation of different error types

Maier, M. E., Ernst, B., & Steinhauser, M. (2018) · Biological Psychology · doi:10.1016/j.biopsycho.2018.12.013 · Cited by 45 · see citing works

A multiattribute attentional drift diffusion model

Fisher, G. (2021) · Organizational Behavior and Human Decision Processes · doi:10.1016/j.obhdp.2021.04.004 · Cited by 54 · see citing works

Challenges and promises for translating computational tools into clinical practice

Ahn, W., & Busemeyer, J. R. (2016) · Current Opinion in Behavioral Sciences · doi:10.1016/j.cobeha.2016.02.001 · Cited by 44 · see citing works

Attentional economics links value-modulated attentional capture and decision-making

Pearson, D., Watson, P., Albertella, L., & Pelley, M. E. L. (2022) · Nature Reviews Psychology · doi:10.1038/s44159-022-00053-z · Cited by 45 · see citing works

Dopamine Promotes Cognitive Effort by Biasing the Benefits Versus Costs of Cognitive WorkPreprint

Westbrook, A., van den Bosch, R., Määttä, J. I., Hofmans, L., Papadopetraki, D., Cools, R., & Frank, M. (2019) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/778134 · Cited by 41 · see citing works

Intra‐individual variability in task performance after cognitive training is associated with long‐term outcomes in children

Cubillo, A., Hermes, H., Berger, E., Winkel, K., Schunk, D., Fehr, E., & Hare, T. A. (2022) · Developmental Science · doi:10.1111/desc.13252 · Cited by 39 · see citing works

Uncovering the computational mechanisms underlying many-alternative choice

Thomas, A. W., Molter, F., & Krajbich, I. M. (2021) · eLife · doi:10.7554/elife.57012 · Cited by 45 · see citing works

Attention bias modification in drug addiction: Enhancing control of subsequent habits

Parvaz, M., Malaker, P., Zilverstand, A., Moeller, S. J., Alia-Klein, N., & Goldstein, R. (2021) · Proceedings of the National Academy of Sciences of the United States of America · doi:10.1073/pnas.2012941118 · Cited by 34 · see citing works

Goals, usefulness and abstraction in value-based choice

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Emotional arousal and discount rate in intertemporal choice are reference dependent.

Lempert, K. M., Glimcher, P. W., & Phelps, E. A. (2015) · Journal of Experimental Psychology General · doi:10.1037/xge0000047 · Cited by 37 · see citing works

Cost-benefit trade-offs in decision-making and learning

Sidarus, N., Palminteri, S., & Chambon, V. (2019) · PLoS Comput. Biol. · doi:10.1371/journal.pcbi.1007326 · Cited by 34 · see citing works

Decision Making and Oddball Effects on Pupil Size: Evidence for a Sequential Process

Strauch, C., Koniakowsky, I. M., & Huckauf, A. (2020) · Journal of Cognition · doi:10.5334/joc.96 · Cited by 34 · see citing works

Regulation of evidence accumulation by pupil-linked arousal processes

Keung, W., Hagen, T. A., & Wilson, R. C. (2019) · Nature Human Behaviour · doi:10.1038/s41562-019-0551-4 · Cited by 47 · see citing works

Slower speaking rate reduces listening effort among listeners with cochlear implants

Winn, M., & Teece, K. H. (2020) · Ear and Hearing · doi:10.1097/aud.0000000000000958 · Cited by 23 · see citing works

Uncertainty in learning, choice, and visual fixation

Stojić, H., Orquin, J. L., Dayan, P., Dolan, R., & Speekenbrink, M. (2019) · Proceedings of the National Academy of Sciences of the United States of America · doi:10.1073/pnas.1911348117 · Cited by 32 · see citing works

Identifying Uncertainty States during Wayfinding in Indoor Environments: An EEG Classification Study

Zhu, B., Cruz-Garza, J. G., Yang, Q., Shoaran, M., & Kalantari, S. (2021) · Advanced Engineering Informatics · doi:10.1016/j.aei.2022.101718 · Cited by 34 · see citing works

How can neuroscience inform economics?

Krajbich, I. M., & Dean, M. (2015) · Current Opinion in Behavioral Sciences · doi:10.1016/j.cobeha.2015.07.005 · Cited by 33 · see citing works

Long-term stress and trait anxiety affect brain network balance in dynamic cognitive computations

Liu, L., Wu, J., Geng, H., Liu, C., Luo, Y., Luo, J., & Qin, S. (2021) · Cerebral Cortex · doi:10.1093/cercor/bhab393 · Cited by 34 · see citing works

Dopamine regulates decision thresholds in human reinforcement learning in males

Chakroun, K., Wiehler, A., Wagner, B., Mathar, D., Ganzer, F., van Eimeren, T., Sommer, T., & Peters, J. (2023) · Nature Communications · doi:10.1038/s41467-023-41130-y · Cited by 33 · see citing works

Computational neuroscience across the lifespan: Promises and pitfalls

van den Bos, W., Bruckner, R., Nassar, M. R., Mata, R., & Eppinger, B. (2017) · Developmental Cognitive Neuroscience · doi:10.1016/j.dcn.2017.09.008 · Cited by 30 · see citing works

An uncertainty-based model of the effects of fixation on choice

Li, Z., & Ma, W. J. (2021) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1009190 · Cited by 39 · see citing works

Reconsidering the path for neural and physiological methods in consumer psychology

Clithero, J. A., Karmarkar, U. R., Nave, G., & Plaßmann, H. (2023) · Journal of Consumer Psychology · doi:10.1002/jcpy.1397 · Cited by 38 · see citing works

Attitudes and attention

Gwinn, R., & Krajbich, I. M. (2019) · Journal of Experimental Social Psychology · doi:10.1016/j.jesp.2019.103892 · Cited by 31 · see citing works

Loss Aversion Reflects Information Accumulation, Not Bias: A Drift-Diffusion Model Study

Clay, S. N., Clithero, J. A., Harris, A. M., & Reed, C. L. (2017) · Frontiers in Psychology · doi:10.3389/fpsyg.2017.01708 · Cited by 30 · see citing works

Correlation of Neural Activity with Behavioral Kinematics Reveals Distinct Sensory Encoding and Evidence Accumulation Processes During Active Tactile Sensing

Delis, I., Dmochowski, J., Sajda, P., & Wang, Q. (2018) · NeuroImage · doi:10.1016/j.neuroimage.2018.03.035 · Cited by 33 · see citing works

Cross-Task Contributions of Frontobasal Ganglia Circuitry in Response Inhibition and Conflict-Induced Slowing

Jahfari, S., Ridderinkhof, K. R., Collins, A. G. E., Knapen, T. H. J., Waldorp, L., & Frank, M. J. (2018) · Cerebral Cortex · doi:10.1093/cercor/bhy076 · Cited by 30 · see citing works

The influence of visual attention on memory-based preferential choice

Weilbächer, R. A., Krajbich, I. M., Rieskamp, J., & Gluth, S. (2021) · Cognition · doi:10.1016/j.cognition.2021.104804 · Cited by 28 · see citing works

Biased Intensity Judgements of Visceral Sensations After Learning to Fear Visceral Stimuli: A Drift Diffusion Approach

Zaman, J., Madden, V. J., Iven, J., Wiech, K., Weltens, N., Ly, H. G., Vlaeyen, J. W. S., Oudenhove, L. V., & Diest, I. V. (2017) · Journal of Pain · doi:10.1016/j.jpain.2017.04.011 · Cited by 28 · see citing works

Back to Pupillometry: How Cortical Network State Fluctuations Tracked by Pupil Dynamics Could Explain Neural Signal Variability in Human Cognitive Neuroscience

Schwalm, M., & Jubal, E. R. (2017) · eNeuro · doi:10.1523/eneuro.0293-16.2017 · Cited by 29 · see citing works

Food decision-making under time pressure

Huseynov, S., & Palma, M. A. (2020) · Food Quality and Preference · doi:10.1016/j.foodqual.2020.104072 · Cited by 27 · see citing works

Shocking secret you won’t believe! Emotional arousal in clickbait headlines

Pengnate, S. F. (2019) · Online Information Review · doi:10.1108/oir-05-2018-0172 · Cited by 26 · see citing works

Pre-stimulus pupil dilation and the preparatory control of attention

Irons, J. L., Jeon, M., & Leber, A. B. (2017) · PLoS ONE · doi:10.1371/journal.pone.0188787 · Cited by 27 · see citing works

Prosocial Preferences Condition Decision Effort and Ingroup Biased Generosity in Intergroup Decision-Making

Rahal, R.-M., Fiedler, S., & Dreu, C. K. W. D. (2020) · Scientific Reports · doi:10.1038/s41598-020-64592-2 · Cited by 24 · see citing works

Visual fixation patterns during economic choice reflect covert valuation processes that emerge with learning

Cavanagh, S. E., Malalasekera, W. M. N., Miranda, B., Hunt, L. T., & Kennerley, S. W. (2019) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1906662116 · Cited by 26 · see citing works

Information Processing

Jerit, J., & Kam, C. D. (2023) · Oxford University Press eBooks · doi:10.1093/oxfordhb/9780197541302.013.14 · Cited by 25 · see citing works

Modeling Eye Movements and Response Times in Consumer Choice

Krajbich, I. M., & Smith, S. M. (2015) · Journal of Agricultural & Food Industrial Organization · doi:10.1515/jafio-2015-0016 · Cited by 24 · see citing works

Dissociable mappings of tonic and phasic pupillary features onto cognitive processes involved in mental arithmetic

Hoffing, R. C., Lauharatanahirun, N., Forster, D. E., Garcia, J. O., Vettel, J. M., & Thurman, S. M. (2020) · PLoS ONE · doi:10.1371/journal.pone.0230517 · Cited by 26 · see citing works

Combining pupillometry and drift-diffusion models reveals auditory category learning dynamicsPreprint

McHaney, J. R., Roark, C. L., McGinley, M. J., & Chandrasekaran, B. (2024) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2024.04.16.589753 · Cited by 2 · see citing works

What Eye Tracking Can Reveal about Dynamic Decision-Making

Vachon, F., & Tremblay, S. (2019) · AHFE international · doi:10.54941/ahfe100226 · Cited by 5 · see citing works

Pupil Dilation and Eye Movements Can Reveal Upcoming Choice in Dynamic Decision-Making

Peysakhovich, V., Vachon, F., Vallières, B. R., Dehais, F., & Tremblay, S. (2015) · Proceedings of the Human Factors and Ergonomics Society Annual Meeting · doi:10.1177/1541931215591043 · Cited by 13 · see citing works

Reviewed by:

Wolfgang Einhäuser, A., Koch, C., Carter, O. L., Heekeren, H. R., Planck, M., & Summerfield, C. (2010)

Pupil dilation betrays the timing of decisions

Wolfgang Einhäuser, A. (2010) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2010.00018 · Cited by 146 · see citing works