MSc-Thesis: Combining overlap correction and back-to-back regression methods to analyse eye-tracking-EEG co-registration data during natural reading

Author: Yanhong Xu

Supervisor(s): Supervisor 1, Supervisor 2

Year: 2026

Important

Current WIP scripts and simulation prototypes are mainly stored in _research/. For recent updates, see progress_log.md.

Project Description

Research Questions

1. In simulations mimicking co-registration data with known ground truth, does combining overlap correction (deconvolution rERP) with B2B improve the disentanglement and recovery of collinear predictors when fixation-related responses overlap in time?

2. When applied to ZuCo, does the best-performing pipeline yield stable and interpretable estimates for lexical predictors (surprisal, frequency, length) while controlling for oculomotor covariates?

Main goals

1. A simulation framework with controllable temporal overlap and predictor collinearity is implemented using Unfold toolbox.

2. Analysis pipelines spanning the overlap × collinearity conceptual method map, including baseline decoding, deconvolution rERP decoding, B2B, and rERP + B2B variants, are systematically benchmarked against known ground truth.

3. A fixation-aware surprisal predictor is implemented, distinguishing first fixations and refixations.

4. The selected best-performing pipeline(s) will be applied to the ZuCo dataset, including lexical predictors such as word surprisal (from a pretrained language model), log word frequency, and word length, while controlling for oculomotor covariates.

Zotero Library Path

report/thesis.bib

Instruction for a new student

If a fellow student wants to reproduce all your results. What scripts, in which order, with which data need to be run?

Be as specific as possible. Plan to spend at least 1h on this.

Optional: Add a pipeline plot in which the different steps are displayed together with the corresponding scripts.

Overview of Folder Structure

│projectdir          <- Project's main folder. It is initialized as a Git
│                       repository with a reasonable .gitignore file.
│
├── report           <- **Immutable and add-only!**
│   ├── proposal     <- Proposal PDF
│   ├── thesis       <- Final Thesis PDF
│   ├── talks        <- PDFs (and optionally pptx etc) of the Intro,
|   |                   Midterm & Final-Talk
|
├── _research        <- WIP scripts, code, notes, comments,
│   |                   to-dos and anything in an alpha state.
│
├── plots            <- All exported plots go here, best in date folders.
|   |                   Note that to ensure reproducibility it is required that all plots can be
|   |                   recreated using the plotting scripts in the scripts folder.
|
├── notebooks        <- Pluto, Jupyter, Weave or any other mixed media notebooks.*
│
├── scripts          <- Various scripts, e.g. simulations, plotting, analysis,
│   │                   The scripts use the `src` folder for their base code.
│
├── src              <- Source code for use in this project. Contains functions,
│                       structures and modules that are used throughout
│                       the project and in multiple scripts.
│
├── test             <- Folder containing tests for `src`.
│   └── runtests.jl  <- Main test file
│   └── setup.jl     <- Setup test environment
│
├── README.md        <- Top-level README. A fellow student needs to be able to
|   |                   continue your project. Think about her!!
|
├── .gitignore       <- focused on Julia, but some Matlab things as well
│
├── (Manifest.toml)  <- Contains full list of exact package versions used currently.
|── (Project.toml)   <- Main project file, allows activation and installation.
└── (Requirements.txt)<- in case of python project - can also be an anaconda file, MakeFile etc.
                        

*Instead of having a separate notebooks folder, you can also delete it and integrate your notebooks in the scripts folder. However, notebooks should always be marked by adding nb_ in front of the file name.