Behaviour + EEG analyses for two related studies on imagined movement accuracy (that is, do we make "errors" during motor imagery?), and how scalp‑level dynamics reflect those processes.
Left: Behavioural task. Right: EEG results — work in progress; plotting cleanup pending.
At a glance:
- Behaviour (Published): Participants performed (overtly or imagined) a complex motor task designed to challenge motor acuity. Results support notion of motor imagery accuracy; similarly affected by drivers of overt movement error.
- EEG: Approach: task‑locked theta/alpha/beta dynamics modeled with hierarchical GAMs (mgcv); contrasts via difference‑of‑smooths; confirmatory cluster‑based permutation inference. Results interpretation pending (manuscript in prep).
/_Scripts/— all analysis code (behaviour + EEG).
Convention: scripts00–03= Behaviour paper; scripts04+= EEG paper./external/— EEG preprocessing pipeline (git submodule, pinned to a specific commit)./legacy/— dissertation‑era code (read‑only)./media/— curated figures displayed here (bulk plot dumps are ignored)./_Data/— local‑only; only_Data/eeg/BESA-81.csv(channel map) is tracked.renv.lock,.Rprofile— reproducible R environment via renv.
- Behavioural:
- Behavioural task: single-session touchscreen path-tracing with imagery and overt execution, repeated vs random shapes, varying complexity and stimulus durations.
- Metrics: overt error = DTW-aligned mean Euclidean deviation; performance = z(speed/error); imagery expected performance obtained by fitting a hierarchical model to overt trials and projecting to imagery.
- Modelling: Bayesian multilevel regressions (participant random effects; standardized predictors, weakly informative priors) tested self-reported accuracy ~ expected/actual performance with condition interactions; secondary models examined movement time ~ condition × stimulus-time × complexity.
- EEG: (WIP); manuscript in prep. See scripts under
/_Scripts/.
- Behaviour:
Ingram, T. G. J., Hurst, A. J., Solomon, J. P., Stratas, A., & Boe, S. G. (2022). Imagined movement accuracy is strongly associated with drivers of overt movement error and weakly associated with imagery vividness. Journal of Experimental Psychology: Human Perception and Performance, 48(12), 1362–1372. https://doi.org/10.1037/xhp0001064
- EEG: (WIP); manuscript in prep. See scripts under
/_Scripts/.
Reproduce (collapsed)
Clone with submodules
git clone --recurse-submodules https://github.com/toniolio/DEMI.git
cd DEMI
Restore R environment
R -q -e 'install.packages("renv", repos="https://cloud.r-project.org"); renv::restore(); renv::status()'
Data live under _Data/ (local only). See scripts in /_Scripts/ for run order and expected inputs.
Submodule (EEG preprocessing) — details (collapsed)
The pipeline in /external/ is pinned to a specific commit.
To intentionally update it:
cd external/DEMI_EEG_Pipeline
git fetch origin
git checkout <new-commit-or-tag>
cd ../..
git add external/DEMI_EEG_Pipeline
git commit -m "external: bump EEG pipeline to <sha|tag>"
Please cite this repository and the related manuscripts when using the code, figures, or results.
- Use GitHub’s Cite this repository button (powered by this repo’s
CITATION.cff) to export BibTeX/APA/EndNote. - The full citation metadata (authors, title, version, release date) live in
CITATION.cff.
Code in this repository is released under the MIT License. See LICENSE.