Brain regions recorded by electrophysiology cannot usually be determined by histology alone: the tip of the probe is difficult to pinpoint, so while the trajectory is clear, the exact depth of the probe is not.
The function AP_align_probe_histology is an old function to do this alignment. In essence, it allows the user to slide the full possible trajectory of the probe until it matches certain electrophysiological features (e.g. a gap in units where a ventricle is expected), and then labels the trajectory with depths relative to the probe.
This is an outdated function which relies on specific loaded variables, and it will eventually be improved. In the meantime:
Electrophysiological landmarks are most reliable, if available. For example, if the top of the probe is outside of the brain, the surface of the cortex can be identified through LFP or the first units.
Brain regions recorded by electrophysiology cannot usually be determined by histology alone: the tip of the probe is difficult to pinpoint, so while the trajectory is clear, the exact depth of the probe is not.
The function
AP_align_probe_histologyis an old function to do this alignment. In essence, it allows the user to slide the full possible trajectory of the probe until it matches certain electrophysiological features (e.g. a gap in units where a ventricle is expected), and then labels the trajectory with depths relative to the probe.This is an outdated function which relies on specific loaded variables, and it will eventually be improved. In the meantime:
alignatlasdatais an alignment tool from Enny van Beest: https://github.com/EnnyvanBeest/GeneralNeuropixelAnalysisFunctions/blob/main/Histology/alignatlasdata.matlaselectrophysiologyis an alignment tool from Mayo Faulkner at the IBL (in python, requires IBL data/naming conventions): https://github.com/int-brain-lab/iblapps/tree/master/atlaselectrophysiology