TY - JOUR

T1 - SEAM

T2 - An integrated activation-coupled model of sentence processing and eye movements in reading

AU - Rabe, Maximilian M.

AU - Paape, Dario

AU - Mertzen, Daniela

AU - Vasishth, Shravan

AU - Engbert, Ralf

N1 - Funding Information: This work was funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) , projects 317633480 (SFB 1287 Limits of Variability in Language) and 318763901 (SFB 1294 Data Assimilation). We also acknowledge support by Norddeutscher Verbund für Hoch- und Höchstleistungsrechnen (HLRN, project no. bbx00001 ) for providing high-performance computing resources. Publisher Copyright: © 2023 The Authors

PY - 2024/2

Y1 - 2024/2

N2 - Models of eye-movement control during reading, developed largely within psychology, usually focus on visual, attentional, lexical, and motor processes but neglect post-lexical language processing; by contrast, models of sentence comprehension processes, developed largely within psycholinguistics, generally focus only on post-lexical language processes. We present a model that combines these two research threads, by integrating eye-movement control and sentence processing. Developing such an integrated model is extremely challenging and computationally demanding, but such an integration is an important step toward complete mathematical models of natural language comprehension in reading. We combine the SWIFT model of eye-movement control (Seelig et al., 2023) with key components of the Lewis and Vasishth sentence processing model (Lewis and Vasishth, 2005). This integration becomes possible, for the first time, due in part to recent advances in successful parameter identification in dynamical models, which allows us to investigate profile log-likelihoods for individual model parameters. We present a fully implemented proof-of-concept model demonstrating how such an integrated model can be achieved; our approach includes Bayesian model inference with Markov Chain Monte Carlo (MCMC) sampling as a key computational tool. The integrated Sentence-Processing and Eye-Movement Activation-Coupled Model (SEAM) can successfully reproduce eye movement patterns that arise due to similarity-based interference in reading. To our knowledge, this is the first-ever integration of a complete process model of eye-movement control with linguistic dependency completion processes in sentence comprehension. In future work, this proof of concept model will need to be evaluated using a comprehensive set of benchmark data.

AB - Models of eye-movement control during reading, developed largely within psychology, usually focus on visual, attentional, lexical, and motor processes but neglect post-lexical language processing; by contrast, models of sentence comprehension processes, developed largely within psycholinguistics, generally focus only on post-lexical language processes. We present a model that combines these two research threads, by integrating eye-movement control and sentence processing. Developing such an integrated model is extremely challenging and computationally demanding, but such an integration is an important step toward complete mathematical models of natural language comprehension in reading. We combine the SWIFT model of eye-movement control (Seelig et al., 2023) with key components of the Lewis and Vasishth sentence processing model (Lewis and Vasishth, 2005). This integration becomes possible, for the first time, due in part to recent advances in successful parameter identification in dynamical models, which allows us to investigate profile log-likelihoods for individual model parameters. We present a fully implemented proof-of-concept model demonstrating how such an integrated model can be achieved; our approach includes Bayesian model inference with Markov Chain Monte Carlo (MCMC) sampling as a key computational tool. The integrated Sentence-Processing and Eye-Movement Activation-Coupled Model (SEAM) can successfully reproduce eye movement patterns that arise due to similarity-based interference in reading. To our knowledge, this is the first-ever integration of a complete process model of eye-movement control with linguistic dependency completion processes in sentence comprehension. In future work, this proof of concept model will need to be evaluated using a comprehensive set of benchmark data.

KW - Bayesian inference

KW - Dynamical models

KW - Eye-movement control

KW - Oculomotor control

KW - Reading

KW - Sentence processing

UR - http://www.scopus.com/inward/record.url?scp=85180607003&partnerID=8YFLogxK

U2 - 10.1016/j.jml.2023.104496

DO - 10.1016/j.jml.2023.104496

M3 - Journal article

AN - SCOPUS:85180607003

VL - 135

JO - Journal of Memory and Language

JF - Journal of Memory and Language

SN - 0749-596X

M1 - 104496

ER -