Sentence Comprehension as a Cognitive Process: A Computational Approach (ISBN: 9781107133112

Shravan Vasishth and Felix Engelmann


This web page accompanies a book to be published by Cambridge University Press. Here, we provide all the code and data that lie behind the modelling presented in the book and the related articles.



Funding

This project was funded by the Volkswagen Foundation (grant 89 953).


Download book source code and data

The github repository behind this page is here. The book source code is available there.


Instructions for reproducing analyses:
  1. Clone the repository (if you know how to use github), or download the master directory as a zip archive (if you are unfamiliar with github)
  2. Download the data.zip directory and place it in the main directory of this repository. Without these data the R code that comes with the book will not work.
  3. Reproduce the figures and code in the book by running VasishthEngelmannSCCP.R incrementally. Alternatively, compile the whole book by running the bash script run.sh.



Shiny app

This Shiny app provides an untuitive interface to derive quantitative predictions for some standard similarity-based interference designs, using existing data (some 100 experiments' data summaries). Please refresh the page if the Shiny app becomes inactive.

Main references
Shravan Vasishth, Bruno Nicenboim, Felix Engelmann, and Frank Burchert. Computational models of retrieval processes in sentence processing. Trends in Cognitive Sciences, 23:968-982, 2019. [ DOI | code | pdf ]
Felix Engelmann, Lena A. Jäger, and Shravan Vasishth. The effect of prominence and cue association in retrieval processes: A computational account. Cognitive Science, 2020. [ code | pdf | www: ]



The ACT-R implementation (lisp)

The Lewis and Vasishth ACT-R model for sentence processing: lisp code extended by Felix Engelmann; see here.


The R implementation (inter-act)

This is an implementation that considerably simplifies the assumptions of the model, and uses R. Download from here.


The Stan implementations

Bruno Nicenboim and Shravan Vasishth. Models of retrieval in sentence comprehension: A computational evaluation using Bayesian hierarchical modeling. Journal of Memory and Language, 99:1-34, 2018. [ DOI | code | pdf ]


Paula Lissón et al implementation: A computational evaluation of two models of retrieval processes in sentence processing. Submitted. {T}he case of aphasia pdf.