NeonateTriCorr

This code base is using the Julia Language and DrWatson to make a reproducible scientific project named

NeonateTriCorr

To (locally) reproduce this project, do the following:

0. Download this code base. Notice that raw data are typically not included in the git-history and may need to be downloaded independently.
1. Open a Julia console and do:

   julia> using Pkg
   julia> Pkg.add("DrWatson") # install globally, for using `quickactivate`
   julia> Pkg.activate("path/to/this/project")
   julia> Pkg.instantiate()
   

This will install all necessary packages for you to be able to run the scripts and everything should work out of the box, including correctly finding local paths.

Data pipeline

To obtain triple correlations of recordings from the Helsinki dataset use the following steps. Generally, for scripts ending in .jl, the instruction "run X.jl" means "type include("path/to/X.jl")." Best practice is to run Y/X.jl as include(scriptsdir("Y","X.jl")).

0. Activate this project (such as by typing Pkg.activate("path/to/this/project"))
1. Download patient recordings with download_helsinki_eegs(patient_numbers::Vector{Int})
2. Set PAT to be the number of a downloaded patient (PAT=X), and then run contributions_timeseries/contributions_patPAT.jl (alternatively: run contributions_patPAT_artifacts.jl to obtain triple correlation for all timepoints, including those annotated as artifacts). I typically ran this using SLURM on a cluster, so that the contributions were computed in parallel jobs.
3. To compare the differences between seizure and non-seizure epochs, run reanalysis/diffs_motifs.jl (alternatively: with _artifacts suffix).
4. To attempt to detect seizures, run reanalysis/detect_seizures_motif_0.jl.
5. Repeat the previous two steps with diffs_aeeg.jl and detect_seizures_aeeg.jl respectively to run the same analyses on aEEG-transformed recordings.

Reproduce figures

To reproduce the figures, first follow steps 0-2 of the Data Pipeline instructions above. Then the scripts/figures scripts will reproduce all figures except the first (which resulted from plotting snippets of preprocessed EEG loaded using the load_helsinki_eeg function, exported, and then imported to MATLAB).