Starting on my first forward modelling. The goal is to input SEEG recordings (mostly in cortex, some hippocampus) and .pial files made by freesurfer. As output, I want to use BEM to estimate the signal at the surface of the cortex, and then compare this to actual signals that were simultaneously recorded using surface strips and grids. I don’t need to estimate the sources, only do the forward modeling. My interest is in how the depth/surface distinction modifies the signals and the kind of spatio-temporal dynamics that can be observed, depending on volume conduction effects, contact spacing etc.
Anyone could point me to an existing python script that I can modify, it would be much appreciated. All of my searches so far have found EEG/MEG head models, or been rather exotic.