Project B03
Modelling the connection between eye-movement control, sentence processing, and brain signals
PI(s): Prof. Dr. Shravan Vasishth & Prof. Dr. Ralf Engbert & Prof. Dr. Milena Rabovsky-Schad
This project extends our previous mathematical modelling of the integration of eye-movement control and syntactic processing to include electrophysiological indicators during reading. We work with a process-oriented model in which prediction of behaviour is implemented at the level of individual subjects. As a long-term goal, we plan to also include neural processes in the model via electrophysiological markers to obtain a well-founded theoretical explanation of the dynamics of natural reading comprehension and its connection with individually variable eye movements and event-related potentials.
in Phase 1:
Modelling the interaction between eye-movement control and parsing processes
PI(s): Prof. Dr. Ralf Engbert & Prof. Dr. Shravan Vasishth
This project aims to develop mathematical/computational models to investigate how eye movements and natural language parsing processes influence and interact with each other. Based on novel experimental designs and an integrated modeling approach, we will seek to explain how the dynamical interaction of subprocesses (vision, attention, parsing, sensorimotor control) generates the observed variability in language processing between and within participants under varying task demands.
Members
Papers
| Author(s) | Title | Year | Published in | Links |
|---|---|---|---|---|
| Vasishth, S., Mertzen, D., Jäger, L.A., & Gelman, A. | The statistical significance filter leads to overoptimistic expectations of replicability. | 2018 | Journal of Memory and Language, 103, 151-175. DOI: 10.1016/j.jml.2018.07.004 | |
| Vasishth, S., Nicenboim, B., Engelmann, F., & Burchert, F. | Computational models of retrieval processes in sentence processing. | 2019 | Trends in Cognitive Sciences, 23(11), 968–982. DOI: 10.1016/j.tics.2019.09.003 | |
| Chandra, J., Krügel, A., & Engbert, R. | Experimental test of Bayesian saccade targeting under reversed reading direction. | 2019 | Attention, Perception, & Psychophysics, 82, 1230-1240. DOI: 10.3758/s13414-019-01814-4 | |
| Engelmann, F., Jäger, L. A., & Vasishth, S. | The effect of prominence and cue association in retrieval processes: A computational account. | 2019 | Cognitive Science, 43, e12800. DOI: 10.1111/cogs.12800 | |
| Seelig, S. A., Rabe, M. M., Malem-Shinitski, N., Risse, S., Reich, S., & Engbert, R. | Bayesian parameter estimation for the SWIFT model of eye-movement control during reading. | 2020 | Journal of Mathematical Psychology, 95, 102313. DOI: 10.1016/j.jmp.2019.102313 | |
| Rabe, M. M., Vasishth, S., Hohenstein, S., Kliegl, R., & Schad, D. J. | hypr: An R package for hypothesis-driven contrast coding. | 2020 | The Journal of Open Source Software, 5(48), 2134. DOI: 10.21105/joss.02134 | |
| Jäger, L. A., Mertzen, D., Van Dyke, J. A., & Vasishth, S. | Interference patterns in subject-verb agreement and reflexives revisited: A large-sample study. | 2020 | Journal of Memory and Language, 111, 104063. DOI: 10.1016/j.jml.2019.104063 | |
| Vasishth, S. | Using Approximate Bayesian Computation for estimating parameters in the cue-based retrieval model of sentence processing. | 2020 | MethodsX, 7, 100850. DOI: 10.1016/j.mex.2020.100850 | |
| Rabe, M. M., Chandra, J., Krügel, A., Seelig, S. A., Vasishth, S., & Engbert, R. | A Bayesian Approach to dynamical modeling of eye-movement control in reading normal, mirrored, and scrambled texts. | 2021 | Psychological Review, 128(5), 803–823. DOI: 10.1037/rev0000268 | |
| Paape, D., Vasishth, S., & Engbert, R. | Does Local Coherence Lead to Targeted Regressions and Illusions of Grammaticality? | 2021 | Open Mind (2022) 5: 42–58. DOI: 10.1162/opmi_a_00041 | |
| Engbert, R., Rabe, M. M., Schwetlick, L., Seelig, S. A., Reich, S., & Vasishth, S. | Data assimilation in dynamical cognitive science. | 2022 | Trends in Cognitive Sciences, 26(2), 99-102. DOI: 10.1016/j.tics.2021.11.006 | |
| Yadav, H., Smith, G., Reich, S., & Vasishth, S. | Number feature distortion modulates cue-based retrieval in reading. | 2023 | Journal of Memory and Language, 129, 104400. DOI: 10.1016/j.jml.2022.104400 | |
| Mertzen, D., Paape, D., Dillon, B. W., Engbert, R., & Vasishth, S. | Syntactic and semantic interference in sentence comprehension: Support from English and German eye-tracking data. | 2023 | Glossa: Psycholinguistics, 2(1), 8, 1-48. DOI: 10.5070/G60111266 | |
| Rabe, M. M., Paape, D., Mertzen, D., Vasishth, S., & Engbert, R. | SEAM: An integrated activation-coupled model of sentence processing and eye movements in reading. | 2024 | Journal of Memory and Language, 135, 104496 DOI: 10.1016/j.jml.2023.104496 | |
| Mertzen, D., Laurinavichyute, A., Dillon, B. W., Engbert, R., & Vasishth, S. | Crosslinguistic evidence against interference from extra-sentential distractors | 2024 | Journal of Memory and Language, 137, 104514. DOI: 10.1016/j.jml.2024.104514 | |
| Engbert, R., & Rabe, M. M. | A tutorial on Bayesian inference for dynamical modeling of eye-movement control during reading. | 2024 | Journal of Mathematical Psychology, 119, 102843. DOI: 10.1016/j.jmp.2024.102843 | |
| Schoknecht, P., Yadav, H., & Vasishth, S. | Do syntactic and semantic similarity lead to interference effects? Evidence from self-paced reading and event-related potentials using German. | 2025 | Journal of Memory and Language, 141, 104599. DOI: 10.1016/j.jml.2024.104599 | |
| Mertzen, D. | A cross-linguistic investigation of similarity-based interference in sentence comprehension. | 2022 | PhD Thesis. Potsdam: Universitätsverlag Potsdam. DOI: 10.25932/publishup-55668 | |
| Rabe, M. M. | Modeling the interaction of sentence processing and eye-movement control in reading. | 2024 | PhD Thesis. Potsdam: Universitätsverlag Potsdam. DOI: 10.25932/publishup-62279 | |
| Vasishth, S., & Engelmann, F. | Sentence Comprehension as a Cognitive Process: A Computational Approach. | 2021 | Cambridge: Cambridge University Press. |
