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Van Rijn, Prof. Hedderik

Hedderik van Rijn
Hedderik van Rijn

Hedderik van Rijn is Professor of Cognitive Science and Neuroscience at the Faculty of Behavioural and Social Sciences. Van Rijn conducts research into the relationship between behaviour and time. In doing so, he hopes to understand how cognitive processing is influenced by time. In 2022, Van Rijn’s research group focused on how our brains experience time. This research was presented in the interactive exhibition ‘TIME WILL TELL’ at the University Museum in Groningen. Van Rijn has also repeatedly conducted research into why we sometimes feel that time is going slowly, while it flies by at other times. In 2017, Van Rijn received a Vici grant for his research proposal on estimating time, entitled ‘The stopwatch in our brains’.

Hedderik van Rijn at the 'Universiteit van Nederland'
Hedderik van Rijn at the 'Universiteit van Nederland'

Contact and more information

Publications

2022

van der Velde, M., Sense, F., Borst, J. P., van Maanen, L., & van Rijn, H. (2022). Capturing Dynamic Performance in a Cognitive Model: Estimating ACT-R Memory Parameters With the Linear Ballistic Accumulator. Topics in Cognitive Science. https://doi.org/10.1111/tops.12614

2021

Maass, S., Wolbers, T., van Rijn, H., & Riemer, M. (2022). Temporal context effects are associated with cognitive status in advanced age. Psychological research-Psychologische forschung, 86, 512-521. https://doi.org/10.1007/s00426-021-01502-9
de Jong, J., Akyurek, E. G., & van Rijn, H. (2021). A common dynamic prior for time in duration discrimination. Psychonomic Bulletin & Review, 28, 1183–1190. https://doi.org/10.3758/s13423-021-01887-z
van der Velde, M., Sense, F., Borst, J., & van Rijn, H. (2021). Alleviating the Cold Start Problem in Adaptive Learning using Data-Driven Difficulty Estimates. Computational Brain and Behavior, 4(2), 231-249. https://doi.org/10.1007/s42113-021-00101-6
Wilschut, T., Sense, F., van der Velde, M., Fountas, Z., Maaß, S. C., & van Rijn, H. (2021). Benefits of Adaptive Learning Transfer From Typing-Based Learning to Speech-Based Learning. Frontiers in Artificial Intelligence, 4, [780131]. https://doi.org/10.3389/frai.2021.780131
van der Velde, M., Sense, F., Borst, J., & van Rijn, H. (2021). Capturing dynamic performance in a cognitive model: Estimating ACT-R memory parameters with the linear ballistic accumulator. Paper presented at International Conference on Cognitive Modeling 2021.
Kruijne, W., & van Rijn, H. (2021). Change biases identify the features that drive time perception. Journal of Experimental Psychology : Human Perception and Performance, 47(9), 1192-1208. https://doi.org/10.1037/xhp0000934
Maaß, S. C., de Jong, J., van Maanen, L., & van Rijn, H. (2021). Conceptually plausible Bayesian inference in interval timing. Royal Society Open Science, 8(8), [201844]. https://doi.org/10.1098/rsos.201844
Berberyan, H. S., van Rijn, H., & Borst, J. P. (2021). Discovering the brain stages of lexical decision: Behavioral effects originate from a single neural decision process. Brain and Cognition, 153, [105786]. https://doi.org/10.1016/j.bandc.2021.105786
Berberyan, H. S., van Maanen, L., van Rijn, H., & Borst, J. (2021). EEG-based Identification of Evidence Accumulation Stages in Decision-Making. Journal of Cognitive Neuroscience, 33(3), 510-527. https://doi.org/10.1162/jocn_a_01663
Vogelzang, M., Guasti, M. T., van Rijn, H., & Hendriks, P. (2021). How children process reduced forms: A computational cognitive modeling approach to pronoun processing in discourse. Cognitive Science, 45(4), [e12951]. https://doi.org/10.1111/cogs.12951
Salet, J. M., Kruijne, W., & van Rijn, H. (2021). Implicit learning of temporal behavior in complex dynamic environments. Psychonomic Bulletin & Review, 28(4), 1270-1280. https://doi.org/10.3758/s13423-020-01873-x
van der Velde, M., Sense, F., Spijkers, R., Meeter, M., & van Rijn, H. (2021). Lockdown Learning: Changes in Online Foreign-Language Study Activity and Performance of Dutch Secondary School Students During the COVID-19 Pandemic. Frontiers in Education, 6, [712987]. https://doi.org/10.3389/feduc.2021.712987
Kruijne, W., Olivers, C. N. L., & van Rijn, H. (2021). Memory for Stimulus Duration Is Not Bound to Spatial Information. Journal of Cognitive Neuroscience, 33(7), 1211-1229. https://doi.org/10.1162/jocn_a_01723
van der Velde, M., Sense, F., Borst, J., den Hartigh, R., Baatenburg de Jong, M., & van Rijn, H. (2021). Memory Performance in Special Forces: Speedier Responses Explain Improved Task Performance after Physical Exertion. Poster session presented at 43rd Annual Meeting of the Cognitive Science Society.
Kruijne, W., Olivers, C. N. L., & van Rijn, H. (2021). Neural Repetition Suppression Modulates Time Perception: Evidence From Electrophysiology and Pupillometry. Journal of Cognitive Neuroscience, 33(7), 1230-1252. https://doi.org/10.1101/2020.07.31.230508, https://doi.org/10.1162/jocn_a_01705
Sense, F., van der Velde, M., & van Rijn, H. (2021). Predicting University Students’ Exam Performance Using a Model-Based Adaptive Fact-Learning System. Journal of Learning Analytics, 8(3), 155-169. https://doi.org/10.18608/jla.2021.6590
Wilschut, T., van der Velde, M., Sense, F., Fountas, Z., & van Rijn, H. (2021). Translating a Typing-Based Adaptive Learning Model to Speech-Based L2 Vocabulary Learning. 245-250. Paper presented at 29th ACM Conference on User Modeling, Adaptation and Personalization. https://doi.org/10.1145/3450613.3456825

2020

van der Mijn, R., & van Rijn, H. (2021). Attention Does Not Affect the Speed of Subjective Time, but Whether Temporal Information Guides Performance: A Large-Scale Study of Intrinsically Motivated Timers in a Real-Time Strategy Game. Cognitive Science, 45(3), [12939]. https://doi.org/10.1111/cogs.12939
van der Mijn, R., Damsma, A., Taatgen, N., & van Rijn, H. (2021). Individual optimization of risky decisions in duration and distance estimations. Attention, Perception, & Psychophysics, 83, 1897–1906. https://doi.org/10.3758/s13414-020-02225-6
van der Velde, M., Sense, F., Borst, J., & van Rijn, H. (2020). Kickstarting adaptive fact learning using hierarchical Bayesian modelling. In T. C. Stewart (Ed.), Proceedings of ICCM 2019 - 17th International Conference on Cognitive Modeling (pp. 275-276). Applied Cognitive Science Lab, Penn State.
Kononowicz, T. W., Sander, T., van Rijn, H., & van Wassenhove, V. (2020). Precision Timing with alpha-beta Oscillatory Coupling: Stopwatch or Motor Control? Journal of Cognitive Neuroscience, 32(9), 1624-1636. https://doi.org/10.1162/jocn_a_01570

2019

Damsma, A., Taatgen, N., de Jong, R., & van Rijn, H. (2020). No evidence for an attentional bias towards implicit temporal regularities. Attention, Perception & Psychophysics, 82(3), 1136-1149. https://doi.org/10.3758/s13414-019-01851-z
Vogelzang, M., Foppolo, F., Guasti, M. T., van Rijn, H., & Hendriks, P. (2020). Reasoning about alternative forms is costly: The processing of null and overt pronouns in Italian using pupillary responses. Discourse Processes, 57(2), 158-183. https://doi.org/10.1080/0163853X.2019.1591127
Velde, van der, M., Sense, F., Borst, J., & Rijn, van, H. (2019). Alleviating the Cold-Start Problem in Adaptive Fact Learning Using Bayesian Modelling. Abstract from 17th NVP Winter Conference on Brain & Cognition, Egmond aan Zee, Netherlands.
van Rij, J., Hendriks, P., van Rijn, H., Baayen, R. H., & Wood, S. N. (2019). Analyzing the Time Course of Pupillometric Data. Trends in hearing, 23, 1-22. https://doi.org/10.1177/2331216519832483
Maaß, S., Van Maanen, L., & Rijn, van, H. (2019). An Improved Bayesian Observer Model to Explain Temporal Context Effects in Clinical and Healthy Aged Populations. Paper presented at 2nd Annual Conference of the Timing Research Forum, Queretaro, Mexico.
Berberyan, H., Rijn, van, H., & Borst, J. (2019). Can we directly observe stages of cognitive processing? HsMM-EEG analysis of a Visual Discrimination Task. Poster session presented at NVP winterconference on Brain & Cognition, Egmond aan Zee, Netherlands. https://doi.org/10.13140/RG.2.2.28411.05924
van Maanen, L., van der Mijn, R., van Beurden, M. H. P. H., Roijendijk, L. M. M., Kingma, B. R. M., Miletić, S., & van Rijn, H. (2019). Core body temperature speeds up temporal processing and choice behavior under deadlines. Scientific Reports, 9, [10053]. https://doi.org/10.1038/s41598-019-46073-3
van den Broek, G. S. E., Segers, E., van Rijn, H., Takashima, A., & Verhoeven, L. (2019). Effects of Elaborate Feedback During Practice Tests: Costs and Benefits of Retrieval Prompts. Journal of experimental psychology-Applied, 25(4), 588-601. https://doi.org/10.1037/xap0000212
Maass, S. C., Schlichting, N., & van Rijn, H. (2019). Eliciting contextual temporal calibration: The effect of bottom-up and top-down information in reproduction tasks. Acta Psychologica, 199, [102898]. https://doi.org/10.1016/j.actpsy.2019.102898
de Jong, J., Voelker, A., van Rijn, H., Stewart, T., & Eliasmith, C. (2019). Flexible timing with delay networks–The scalar property and neural scaling. In Proceedings of the 17th International Conference on Cognitive Modelling (pp. 77-82)
Salet, J., Kruijne, W., & Rijn, van, H. (2019). fMTP: A Unifying Computational Framework of Temporal Preparation Across Time Scales.
Maaß, S., Sense, F., Gluck, K., & van Rijn, H. (2019). Keeping Bystanders Active: Resuscitating Resuscitation Skills. Frontiers in public health, 7, [177]. https://doi.org/10.3389/fpubh.2019.00177
van der Velde, M., Sense, F., Borst, J., & van Rijn, H. (2019). Kickstarting Adaptive Fact Learning Using Bayesian Modelling. Poster session presented at 17th International Conference on Cognitive Modeling, Montreal, Quebec, Canada.
van der Mijn, R., & van Rijn, H. (2019). Motivated Timing in a Real-Time Strategy Game: Starcraft2. Poster session presented at 2nd Annual Conference of the Timing Research Forum, Queretaro, Mexico.
Sense, F., Jastrzembski, T. S., Mozer, M. C. M., Krusmark, M., & Rijn, van, H. (2019). Perspectives on Computational Models of Learning and Forgetting. In T. C. Stewart (Ed.), Proceedings of ICCM 2019: 17th International Conference on Cognitive Modelling (pp. 216-221). Applied Cognitive Science Lab.
Gluck, K., Collins, M. G., Krusmark, M., Sense, F., Maaß, S., & Rijn, van, H. (2019). Predicting Performance in Cardiopulmonary Resuscitation. In T. C. Stewart (Ed.), Proceedings of ICCM 2019: 17th International Conference on Cognitive Modelling (pp. 53-58). Applied Cognitive Science Lab.
Collins, M. W., Jastrzembski, T. S., Krusmark, M., Sense, F., Rijn, van, H., Harris, J., Gaines, A., Haubert, A., & Martinez, S. (2019). Predictive Validity of a Cognitive Model in a Naturalistic Language Learning Task. In T. C. Stewart (Ed.), Proceedings of ICCM 2019: 17th International Conference on Cognitive Modelling Applied Cognitive Science Lab.
van Maanen, L., & van Rijn, H. (2019). The observed locus of semantic interference may not coincide with the functional locus of semantic interference: A commentary on Shitova et al. Cortex, 111, 327-332. https://doi.org/10.1016/j.cortex.2018.10.025
Maaß, S. C., Riemer, M., Wolbers, T., & van Rijn, H. (2019). Timing deficiencies in amnestic Mild Cognitive Impairment: Disentangling clock and memory processes. Behavioral Brain Research, 373, [112110]. https://doi.org/10.1016/j.bbr.2019.112110
Salet, J., Kruijne, W., & Rijn, van, H. (2019). Whac-A-Mole: Implicit Adaptation to Temporal Regularities.
Sense, F., Maaß, S., Gluck, K., & van Rijn, H. (2019). Within-Subject Performance on a Real-Life, Complex Task and Traditional Lab Experiments: Measures of Word Learning, Raven Matrices, Tapping, and CPR. Journal of Cognition, 2(1). https://doi.org/10.5334/joc.65

2018

Schlichting, N., de Jong, R., & van Rijn, H. (2020). Performance-informed EEG analysis reveals mixed evidence for EEG signatures unique to the processing of time. Psychological Research : An International Journal of Perception, Attention, Memory, and Action, 84(2), 352-369. https://doi.org/10.1007/s00426-018-1039-y
Hallez, Q., Damsma, A., Rhodes, D., van Rijn, H., & Droit-Volet, S. (2019). The dynamic effect of context on interval timing in children and adults. Acta Psychologica, 192, 87-93. https://doi.org/10.1016/j.actpsy.2018.10.004
Maass, S. C., & van Rijn, H. (2018). 1-s Productions: A Validation of an Efficient Measure of Clock Variability. Frontiers in Human Neuroscience, 12, [519]. https://doi.org/10.3389/fnhum.2018.00519
Soto-Padilla, A., Ruijsink, R., Span, M., van Rijn, H., & Billeter, J-C. (2018). An automated method to determine the performance of Drosophila in response to temperature changes in space and time. Journal of Visualized Experiments, 2018(140), [ e58350]. https://doi.org/10.3791/58350
Damsma, A., Schlichting, N., Eike, R., & van Rijn, D. (2018). Decoding the influence of context on time perception. Poster session presented at Annual meeting of the society for Neuroscience, San Diego, United States.
Sense, F., van der Velde, M., & van Rijn, H. (2018). Deploying a Model-based Adaptive Fact-Learning System in University Courses. Poster session presented at 16th International Conference on Cognitive Modeling. https://iccm-conference.neocities.org/2018/proceedings/ICCM%202018%20Proceedings.pdf
Sense, F., Meijer, R. R., & van Rijn, H. (2018). Exploration of the Rate of Forgetting as a Domain-Specific Individual Differences Measure. Frontiers in Education, 3, [112]. https://doi.org/10.3389/feduc.2018.00112
Sense, F., & van Rijn, H. (2018). Probabilistic Motor Sequence Learning in a Virtual Reality Serial Reaction Time Task. PLoS ONE, 13(6), [e0198759]. https://doi.org/10.1371/journal.pone.0198759
Schlichting, N., Damsma, A., Ziegler, M. P., de Jong, R., & van Rijn, D. (2018). Quantifying attention and its effect on interval timing. Poster session presented at Annual meeting of the society for Neuroscience, San Diego, United States.
Schlichting, N., de Jong, R., & van Rijn, H. (2018). Robustness of individual differences in temporal interference effects. PLoS ONE, 13(8), [e0202345]. https://doi.org/10.1371/journal.pone.0202345
Schlichting, N., de Jong, R., & van Rijn, D. (2018). Robustness of individual differences in temporal interference effects. Abstract from International Meeting of the Psychonomic Society, Amsterdam, Netherlands.
Schlichting, N., Damsma, A., Aksoy, E. E., Wächter, M., Asfour, T., & van Rijn, D. (2018). Temporal context influences the perceived duration of everyday actions: Assessing the ecological validity of lab-based timing phenomena. Journal of Cognition, 2(1), [4]. https://doi.org/10.5334/joc.4
Soto-Padilla, A., Ruijsink, R., Sibon, O. C. M., van Rijn, H., & Billeter, J-C. (2018). Thermosensory perception regulates speed of movement in response to temperature changes in Drosophila melanogaster. Journal of Experimental Biology, 221(10), [74151]. https://doi.org/10.1242/jeb.174151
Kononowicz, T. W., van Rijn, H., & Meck, W. H. (2018). Timing and Time Perception: A Critical Review of Neural Timing Signatures Before, During, and After the To‐Be‐Timed Interval . In Stevens' Handbook of Experimental Psychology and Cognitive Neuroscience (Vol. 1). JOHN WILEY & SONS INC. https://doi.org/10.1002/9781119170174.epcn114
van Rijn, H. (2018). Towards Ecologically Valid Interval Timing. Trends in Cognitive Sciences, 22(10), 850-852. https://doi.org/10.1016/j.tics.2018.07.008

2017

Damsma, A., van der Mijn, R., & van Rijn, H. (2018). Neural markers of memory consolidation do not predict temporal estimates of encoded items. Neuropsychologia, 117, 36-45. [5]. https://doi.org/10.1016/j.neuropsychologia.2018.04.039
Maaß, S., Sense, F., Walsh, M. M., Gluck, K., & van Rijn, D. (2017). Cognitive modeling of cardiopulmonary resuscitation knowledge and skill spanning months to years. Poster session presented at 15th International Conference on Cognitive Modeling, Coventry, United Kingdom.
Maaß, S., & van Rijn, D. (2017). Instantaneous modulations of perceived time: A review and empirical data. Poster session presented at 1st Conference of The Timing Research Forum, Strasbourg, France.
van der Mijn, R., Damsma, A., & van Rijn, D. (2017). Neural markers of memory consolidation do not predict temporal estimates of encoded items. Poster session presented at Winter Conference Nederlandse Vereniging voor Psychonomie 2017, Egmond aan Zee, Netherlands.
Damsma, A., van der Mijn, R., & van Rijn, D. (2017). Neural markers of memory consolidation do not predict temporal estimates of encoded items. Abstract from TEX2017 - Trieste Encounters in Cognitive Sciences, Trieste, Italy.
Damsma, A., de Jong, R., Taatgen, N., & van Rijn, D. (2017). No Evidence For Improved Attention Towards Implicit Temporal Regularities. Poster session presented at 1st Conference of The Timing Research Forum, Strasbourg, France.
Damsma, A., de Jong, R., Taatgen, N., & van Rijn, D. (2017). No Evidence For Improved Attention Towards Implicit Temporal Regularities. Poster session presented at Winter Conference Nederlandse Vereniging voor Psychonomie 2017, Egmond aan Zee, Netherlands.
Damsma, A., & van Rijn, D. (2017). Pupil dilation indexes the metrical hierarchy of unattended rhythmic violations. Abstract from Conference on Music & Eye-Tracking, Frankfurt, Germany.
Damsma, A., & van Rijn, D. (2017). Pupil dilation indexes the metrical hierarchy of unattended rhythmic violations. Abstract from 19th European Conference on Eye Movements, Wuppertal, Germany.
Damsma, A., & van Rijn, H. (2017). Pupillary response indexes the metrical hierarchy of unattended rhythmic violations. Brain and Cognition, 111, 95-103. https://doi.org/10.1016/j.bandc.2016.10.004
Schlichting, N., de Jong, R., & van Rijn, D. (2017). Robustness of individual differences in temporal interference effects. Poster session presented at 1st Conference of The Timing Research Forum, Strasbourg, France.
Schlichting, N., de Jong, R., & van Rijn, D. (2017). Robustness of individual differences in temporal interference effects. Abstract from TEX2017 - Trieste Encounters in Cognitive Sciences, Trieste, Italy.
Vogelzang, M., Mills, A. C., Reitter, D., van Rij, J., Hendriks, P., & van Rijn, H. (2017). Toward cognitively constrained models of language processing: A review. Frontiers in Communication, 2(11), 1-19. https://doi.org/10.3389/fcomm.2017.00011
Akyürek, E. G., Kappelmann, N., Volkert, M., & van Rijn, H. (2017). What you see is what you remember: Visual chunking by temporal integration enhances working memory. Journal of Cognitive Neuroscience, 29(12), 2025-2036. https://doi.org/10.1162/jocn_a_01175

2016

van Rijn, H. (2016). Accounting for memory mechanisms in interval timing: a review. Current Opinion in Behavioral Sciences, 8, 245-249. https://doi.org/10.1016/j.cobeha.2016.02.016
Sense, F., Behrens, F., Meijer, R. R., & van Rijn, H. (2016). An Individual's Rate of Forgetting Is Stable Over Time but Differs Across Materials. Topics in Cognitive Science, 8(1), 305-321. https://doi.org/10.1111/tops.12183
van Rijn, H., & Taatgen, N. A. (2016). An integrative account of psychological time. In S. E. F. Chipman (Ed.), The Oxford Handbook of Cognitive Science (pp. 151-168). Oxford University Press. https://doi.org/10.1093/oxfordhb/9780199842193.013.18
Nijboer, M., Borst, J., van Rijn, H., & Taatgen, N. (2016). Contrasting single and multi-component working-memory systems in dual tasking. Cognitive psychology, 86, 1-26. https://doi.org/10.1016/j.cogpsych.2016.01.003
Schlichting, N., de Jong, R., & van Rijn, D. (2016). Disentangling temporal & numerical magnitude processing. Poster session presented at Time in Tokyo, Tokyo, Japan.
Schlichting, N., de Jong, R., & van Rijn, D. (2016). Disentangling temporal & numerical magnitude processing. Poster session presented at Annual meeting of the Society for Neuroscience, San Diego, United States.
van der Mijn, R., Damsma, A., & van Rijn, H. (2016). Does Memory Consolidation Act as the Trigger of Interval Timing?. Poster session presented at Time in Tokyo, Tokyo, Japan.
Nijboer, M., Borst, J. P., van Rijn, D., & Taatgen, N. A. (2016). Driving and Multitasking: The Good, the Bad, and the Dangerous. Frontiers in Psychology, 7, [1718]. https://doi.org/10.3389/fpsyg.2016.01718
Nieuwenstein, M., Linde, M., & van Rijn, H. (2016). Dwelling on memorability: Effects of long-term picture memorability on the attentional blink. Poster session presented at Psychonomic Society's 57th Annual Meeting , Boston, United States.
van Rijn, H. (2016). Felt Time: The Psychology of How We Perceive Time. Nature, 531(7596), 577-578. https://doi.org/10.1038/531577a
Sense, F., Maaß, S., & van Rijn, D. (2016). Interactions of declarative and procedural memory in real-life tasks: validating CPR as a new paradigm. Poster session presented at 14th International Conference on Cognitive Modeling , Pennsylvania, United States.
Sense, F., & van Rijn, D. (2016). Learn more in less time: Applying memory models to personalize fact learning. Poster session presented at BCN winter meeting, Groningen, Netherlands.
Boehm, U., Hawkins, G. E., Brown, S., Rijn, van, H., & Wagenmakers, E-J. (2016). Of monkeys and men: Impatience in perceptual decision-making. Psychonomic Bulletin & Review, 23(3), 738-749. https://doi.org/10.3758/s13423-015-0958-5
Sense, F., Meijer, R. R., & van Rijn, H. (2016). On the Link between Fact Learning and General Cognitive Ability. In A. Papafragou, D. Grodner, D. Mirman, & J. C. Trueswell (Eds.), Proceedings of the 38th Annual Conference of the Cognitive Science Society Cognitive Science Society.
Rijn, van, H., Borst, J., Taatgen, N., & van Maanen, L. (2016). On the necessity of integrating multiple levels of abstraction in a single computational framework. Current Opinion in Behavioral Sciences, 11, 116-120. https://doi.org/10.1016/j.cobeha.2016.07.007
Vogelzang, M., Hendriks, P., & van Rijn, H. (2016). Pupillary responses reflect ambiguity resolution in pronoun processing. Language, Cognition and Neuroscience, 31(7), 876-885. https://doi.org/10.1080/23273798.2016.1155718
van Rijn, D., Maaß, S., & Sprenger, S. (2016). The pupillary signatures of post-error slowing and error awareness. 356-357. Paper presented at Conference of Experimental Psychologists, Heidelberg, Germany.
Nieuwenstein, M., & van Rijn, H. (2016). Unconscious thought beyond multi-attribute choice: A meta-analysis. Poster session presented at 37th Annual Conference of the Society for Judgment and Decision Making, Boston, United States.

2015

Open Science Collaboration (2015). Estimating the reproducibility of psychological science. Science, 349(6251), [aac4716]. https://doi.org/10.1126/science.aac4716
van Rij, J., Wieling, M., Baayen, R. H., & van Rijn, D. (2015). itsadug: Interpreting Time Series and Autocorrelated Data Using GAMMs.
Kononowicz, T. W., Sander, T., & van Rijn, H. (2015). Neuroelectromagnetic signatures of the reproduction of supra-second durations. Neuropsychologia, 75, 201-213. https://doi.org/10.1016/j.neuropsychologia.2015.06.001
Nieuwenstein, M., Wierenga, T., Morey, R., Wicherts, J., Blom, T., Wagenmakers, E-J., & van Rijn, H. (2015). On making the right choice: A meta-analysis and large-scale replication attempt of the unconscious thought advantage. Judgment and decision making, 10(1), 1-17. http://journal.sjdm.org/14/14321/jdm14321.html
Gu, B-M., van Rijn, H., & Meck, W. H. (2015). Oscillatory multiplexing of neural population codes for interval timing and working memory. Neuroscience and Biobehavioral Reviews, 48, 160-185. https://doi.org/10.1016/j.neubiorev.2014.10.008
Vogelzang, M., Hendriks, P., & van Rijn, D. (2015). Processing overt and null subject pronouns in Italian: A cognitive model. In D. C. Noelle, R. Dale, A. S. Warlaumont, J. Yoshimi, T. Matlock, C. D. Jennings, & P. P. Maglio (Eds.), Proceedings of the 37th Annual Conference of the Cognitive Science Society (pp. 2499-2504). Cognitive Science Society. https://mindmodeling.org/cogsci2015/papers/0429/paper0429.pdf
Damsma, A., & van Rijn, H. (2015). Pupil Dilation Reflects Unattended Violations of The Beat. Poster session presented at NVP Winter Conference 2015, Egmond aan Zee, Netherlands.
Böhm, U., Marsman, M., Matzke, D., van Rijn, D., & Wagenmakers, E-J. (2015). Shortcuts in analysing hierarchical data may create spurious effects. Poster session presented at 27th Annual Convention of the Association for Psychological Science, New York, United States.
Kononowicz, T. W., & van Rijn, H. (2015). Single trial beta oscillations index time estimation. Neuropsychologia, 75, 381-389. https://doi.org/10.1016/j.neuropsychologia.2015.06.014
Sense, F., Behrens, F., Meijer, R., & van Rijn, H. (2015). Stability of individual parameters in a model of optimal fact learning. In N. A. Taatgen, M. K. van Vugt, J. P. Borst, & K. Mehlhorn (Eds.), Proceedings of the 13th International Conference on Cognitive Modeling (pp. 136-141). University of Groningen. http://iccm-conference.org/previous-conferences
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