Methodology for identification of basis profile curves in human CCEP data

Note: This collection is in preliminary form while the manuscript describing it is in review, so that reviewers may access the code and reproduce the methodology. Code and sample data are in the file “bpc_scripts.zip”. Please read the attached manuscript draft, as well as the readme file within the zipped folder, titled: "kjm_bpcmethod_readme.pdf".

Manuscript title: Basis profile curve identification to understand electrical stimulation effects in human brain networks

Authors: Kai J Miller, Klaus-Robert Mueller, Dora Hermes

Description: We present a new machine learning framework to probe how brain regions interact using single-pulse electrical stimulation. Unlike previous studies, this approach does not assume a form for how one brain area will respond to stimulation in another area, but rather discovers the shape of the response in time from the data. We call the set of characteristic discovered response shapes “basis profile curves” (BPCs), and show how these can be mapped back onto the brain quantitatively. An illustrative example is included from one of our human patients to characterize inputs to the parahippocampal gyrus. A code package is in the zip file “bpc_scripts.zip”, downloadable from https://purl.stanford.edu/rc201dv0636 so the reader may explore the technique for own data, or study sample data provided to reproduce the illustrative case presented in the manuscript. Please read the