Publications
Preprints
March, J., & Gluth, S. (in-principle acceptance at eLife). The Hungry Lens: Hunger Shifts Attention and Attribute Weighting in Dietary Choice.
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Ludwig, C. J. H., Stuchlý, E., & Malhotra, G. (Accepted/In press). Grounding computational cognitive models. Psychological Review.
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Bruckner, R., Nassar, M. R., Li, S.-C., & Eppinger, B. (Accepted/Preprint). Differences in learning across the lifespan emerge via resource-rational computations. Psychological Review.
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Ganesh, P., Donner, T. H., Cichy, R. M., Schuck, N. W., Finke, C., & Bruckner, R. (Preprint). Pupil-linked arousal encodes uncertainty-weighted prediction errors.
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2024
Ganesh, P., Cichy, R. M., Schuck N. W., Finke, C., & Bruckner, R. (2024). Adaptive integration of perceptual and reward information in an uncertain world. eLife, 13:RP99266.
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Wulf, M., Yesilada, M., Holford, D., Abels, C. M., Radosevic, M., Stuchly, E., ... & Hahn, U. (2024). Tracking the development of COVID-19-related PsyArXIV preprints. Collabra Psychology, 10(1), 121378.
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Bruckner, R., & Nassar, M. R. (2024). Decision-making under uncertainty. Elsevier eBooks, 213–233.
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O’Leary, J. D., Bruckner, R., Autore, L., & Ryan, T. J. (2023). Natural forgetting reversibly modulates engram expression. eLife, 12:RP92860.
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Deakin, J., Schofield, A., & Heinke, D. (2024). Support for the Time-Varying Drift Rate Model of Perceptual Discrimination in dynamic and static noise using Bayesian Model-Fitting Methodology. Entropy, 26(8), 642.
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Ting, C., & Gluth, S. (2024). Unraveling information processes of decision-making with eye-tracking data. Frontiers in Behavioral Economics, 3, 1384713.
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Bavard, S., Stuchlý, E., Konovalov, A., & Gluth, S. (2024). Humans can infer social preferences from decision speed alone. PLoS Biology, 22(6), e3002686.
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Gopnarayan, M., Aru, J., & Gluth, S. (2024). From DDMs to DNNs: Using process data and models of decision making to improve human-AI interactions. Decision, 11(4), 468–480.
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Anlló, H., Bavard, S., … Palminteri, S. et al. (2024). Comparing experience- and description-based economic preferences across 11 countries. Nature Human Behaviour, 8(8), 1554–1567.
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Saulin, A., Ting, C., Engelmann, J. B., & Hein, G. (2024). Connected in bad times and in good times: Empathy induces stable social closeness. Journal of Neuroscience, 44(23), e1108232024.
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Gluth, S., & Fontanesi, L. (2024). Cognitive modeling in neuroeconomics. In: Forstmann, B., Turner, B. (eds) An Introduction to Model-Based Cognitive Neuroscience (2nd ed.) (pp. 327–359). Springer: Cham, Switzerland.
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2023
Ting, C.C., Salem-Garvia, N., Palminteri, S., Engelmann, J. B. & Lebreton, M. (2023). Neural and computational underpinnings of biased confidence in human reinforcement learning. Nature Communications, 14, 6896.
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Ke, S. C., Gupta, A., Lo, Y. H., Ting, C. C., & Tseng, P. (2023). The hidden arrow in the FedEx logo: Do we really unconsciously see it? Cognitive Research: Principles and Implications, 40.
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Bavard, S., Palminteri, S. (2023). The functional form of value normalization in human reinforcement learning. eLife, 83891.
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Kramer, P.M., Gluth, S. (2023). Episodic Memory Retrieval Affects the Onset and Dynamics of Evidence Accumulation during Value-based Decisions. Journal of Cognitive Neuroscience, 35, 692-714.
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Grob, A.-M., Milivojevic, B., Alink, A., Doeller, C. F., & Schwabe, L. (2023). Stress disrupts insight-driven mnemonic reconfiguration in the medial temporal lobe. Neuroimage, 2065, 119804.
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2022
Fontanesi, L., Shenhav, A., & Gluth, S. (2022). Disentangling choice value and choice conflict in sequential decisions under risk. PLOS Computational Biology, 1010478.
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Mennella, R., Bavard, S., Mentec, I., A., & Grèzes, J. (2022). Spontaneous instrumental avoidance learning in social contexts. Scientific Reports, 17528.
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Sommer, T., Hennies, N., Lewis, P., A., & Alink, A. (2022). The assimilation of novel information into schemata and its efficient consolidation. Journal of Neuroscience, 42(30), 5916–5929.
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Mathôt, S., & March, J. (2022). Conducting linguistic experiments online with OpenSesame and OSWeb. Language Learning, 72(4), 1017–1048.
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Vandendriessche, H., Demmou, A., Bavard, S., Yadak, J., Lemogne, C., Mauras, T., & Palminteri, S. (2022). Contextual influence of reinforcement learning performance of depression: evidence for a negativity bias? Psychological Medicine, 53(10), 4696–4706.
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Kraemer, P., M., Weilbächer, R., A., Mechera-Ostrovsky, T. & Gluth, S. (2022) Cognitive and neural principles of a memory bias on preferential choices. Current Research in Neurobiology, 3, 100029.
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2021
Krenz, V., Sommer, T., Alink, A., Roozendaal, B., & Schwabe, L. (2021). Noradrenergic arousal after encoding reverses the course of systems consolidation in humans. Nature Communications, 12, 6054.
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Chai, Y., Liu, T. T., Marrett, S., Li, L., Khojandi, A., Handwerker, D. A., Alink, A., Muckli, L. & Bandettini, P. A. (2021). Topographical and laminar distribution of audiovisual processing within human planum temporale. Progress in Neurobiology, 102121.
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Alink, A., & Blank, H. (2021). Can expectation suppression be explained by reduced attention to predictable stimuli?. NeuroImage, 231, 117824.
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Spektor, M.S., Bhatia, S., & Gluth, S. (2021). The elusiveness of context effects in decision making, Trends in Cognitive Science, 25, Issue 10, 843 - 854.
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Weilbächer, R.A., Krajbich, I.,Rieskamp, J., & Gluth, S. (2021). The influence of visual attention on memory-based preferential choice, Cognition, 215.
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Kraemer, P.M., Fontanesi, L., Spektor, M.S., & Gluth, S. (2021). Response time models separate single- and dual-process accounts of memory-based decisions. Psychonomic Bulletin & Review, 28, 304–323.
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2020
Weilbächer, R.A., Kraemer, P.M., & Gluth, S. (2020). The reflection effect in memory-based decisions. Psychological Science, 31, 1439–1451.
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Ting, C.C., Palminteri, S., Engelmann, J.B., & Lebreton, M. (2020). Robust valence-induced biases on motor response and confidence in human reinforcement learning. Cognitive, Affective, & Behavioral Neuroscience, 20, 1184–1199.
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Gluth, S., Kern, N., & Vitali, C.L. (2020). Reply to: Divisive normalization does influence decisions with multiple alternatives. Nature Human Behaviour, 4, 1121–1123.
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Gluth, S., Kern, N., Kortmann, M., & Vitali, C.L. (2020). Value-based attention but not divisive normalization influence decisions with multiple alternatives. Nature Human Behaviour, 4, 634–645.
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Kraemer, P.M., Weilbächer, R.A., Fontanesi, L., & Gluth, S. (2020). Neural bases of financial decision making: from spikes to large-scale brain connectivity. In J. Traczyk & T. Zaleskiewicz (Eds.), Psychological Perspectives on Financial Decision Making (pp. 3–19). Cham: Springer.
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2019
Gluth, S.*, & Jarecki, J.B. * (2019). On the importance of power analyses for cognitive modeling. Computational Brain and Behavior, 2, 266–270.
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Gluth, S., & Meiran, N. (2019). Leave-One-Trial-Out, LOTO, a general approach to Link single-trial parameters of cognitive models to neural data. eLife, 8, e42607.
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Busemeyer, J.R., Gluth, S., Rieskamp, J., & Turner, B. (2019). Cognitive and neural bases of multi-attribute, multi-alternative value-based decisions. Trends in Cognitive Sciences, 23, 251–263.
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Spektor, M.S., Gluth, S., Fontanesi, L., & Rieskamp, J. (2019). How similarity between choice options affects decisions from experience: The accentuation-of-differences model. Psychological Review, 126, 52–88.
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Fontanesi, L., Gluth, S., Spektor, M.S., & Rieskamp, J. (2019). A reinforcement learning diffusion decision model for value-based decisions. Psychonomic Bulletin & Review, 4, 1099 – 1121.
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Spilcke-Liss, J., Zhu, J., Gluth, S., Spezio, M., & Gläscher, J. (2019). Semantic incongruency interferes with endogenous attention in cross-modal integration of semantically congruent objects. Frontiers in Integrative Neuroscience, 13, 53.
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Huber, R., & Gluth, S. (2019). Psychologische Konsequenzen von Armut: Möglichkeiten und Grenzen zielorientierter Präventationsmassnahmen. In C. Mattes & C. Knöpfel (Eds.), Armutsbekämpfung durch Schuldenprävention (pp. 91–105). Wiesbaden: Springer VS.
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2018
Gluth, S.*, Spektor, M.S.*, & Rieskamp, J. (2018). Value-based attentional capture affects multi-alternative decision making. eLife, 7, e39659.
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Farashahi, S., Ting, C.C., Kao, C.H., Wu, S.W., & Soltani, A. (2018). Dynamic combination of sensory and reward information under time pressure. PLoS Computational Biology, e1006070.
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Mechera-Ostrovsky, T., & Gluth, S. (2018). Memory beliefs drive the memory bias on value-based decisions. Scientific Reports, 8, e10592.
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2017
Gluth, S., Hotaling, J.M., & Rieskamp, J. (2017). The attraction effect modulates reward prediction errors and intertemporal choices. Journal of Neuroscience, 37, 371–382.
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Gluth, S., & Rieskamp, J. (2017). Variability in behavior that cognitive models do not explain can be Linked to neuroimaging data. Journal of Mathematical Psychology, 76, 104–116.
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Weilbächer, R.A., & Gluth, S. (2017). The interplay of hippocampus and ventromedial prefrontal cortex in memory-based decision making. Brain Sciences, 7, 4.
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2010 – 2016
Gluth, S., & Fontanesi, L. (2016). Wiring the altruistic brain. Science, 351, 1028–1029.
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Gluth, S., Sommer, T., Rieskamp, J., & Büchel, C. (2015). Effective connectivity between hippocampus and ventromedial prefrontal cortex controls preferential choices from memory. Neuron, 86, 1078–1090.
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Ting, C.C., Yu, C.C., Maloney, L.T., & Wu, S.W. (2015). Neural mechanisms for integrating prior knowledge and likelihood in value-based probabilistic inference. Journal of Neuroscience, 35, 1792–1805.
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Clos, M., Schwarze, U., Gluth, S., Bunzeck, N., & Sommer, T. (2015). Goal- and retrieval-dependent activity in the striatum during memory recognition. Neuropsychologia, 72, 1–11.
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Gluth, S., Rieskamp, J., & Büchel, C. (2014). Neural evidence for adaptive strategy selection in value-based decision making. Cerebral Cortex, 24, 2009–2021.
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Gluth, S., Rieskamp, J., & Büchel, C. (2013). Deciding not to decide: Computational and neural evidence for hidden behavior in sequential choice. PLoS Computational Biology, 9, e1003309.
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Gluth, S., Rieskamp, J., & Büchel, C. (2013). Classic EEG motor potentials track the emergence of value-based decisions. NeuroImage, 79, 394–403.
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Boll, S., Gamer, M., Gluth, S., Finsterbusch, J., & Büchel, C. (2013). Separate amygdala subregions signal surprise and predictiveness during associative fear learning in humans. European Journal of Neuroscience, 37, 758–767.
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Gluth, S., Rieskamp, J., & Büchel, C. (2012). Deciding when to decide: Time-variant sequential sampling models explain the emergence of value-based decisions in the human brain. Journal of Neuroscience, 32, 10686–10698.
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Brassen, S., Gamer, M., Peters, J., Gluth, S., & Büchel, C. (2012). Don’t look back in anger! Responsiveness to missed chances in successful and non-successful aging. Science, 336, 612–614.
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Burzynska, A.Z., Nagel, I.E., Preuschhof, C., Gluth, S., Bäckman, L., Li, S.C., Lindenberger, U., & Heekeren, H.R. (2012). Cortical thickness is Linked to executive functioning in adulthood and aging. Human Brain Mapping, 33, 1607–1620.
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Ebner, N.C., Gluth, S., Johnson, M.R., Raye, C.L., Mitchell, K.J., & Johnson, M.K. (2011). Medial prefrontal cortex activity when thinking about others depends on their age. Neurocase, 17, 260–269.
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Gluth, S., Ebner, N.C., & Schmiedek, F. (2010). Attitudes toward younger and older adults: The German Aging Semantic Differential. International Journal of Behavioral Development, 34, 147–158.
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*equal contribution