I’m wonder if there are some approaches that could subdivide cortical layers according to its cortical depth (e.g. depth based on the interface between grey matter and white matter). For example, I have a high-resolution anatomical image and a V2 mask, I’m going to separate V2 into superficial, middle and deep layers. Would it be possible to do this kind of analysis with AFNI?
Yes, there are multiple approaches on how to get estimates of cortical depths with AFNI tools.
E.g. identifying voxels of a given cortical depth with 3dSurf2Vol using Freesurfer GM and WM surfaces as input. Note the arguments –f_p1_fr and -f_pn_fr that defines the range of cortical depth.
See a full example here: https://layerfmri.com/2017/11/26/getting-layers-in-epi-space/ (go to point 4.) )
Daniel Glen also developed a set of new tools on estimations of cortical thickness that can be used to obtained estimates of cortical depths referred to in his HBM poster (https://ww5.aievolution.com/hbm1801/index.cfm?do=abs.viewAbs&abs=1326[/url]) and here: [url=https://layerfmri.com/2018/01/04/layer-fmri-software-in-the-field/#AFNI]https://layerfmri.com/2018/01/04/layer-fmri-software-in-the-field/#AFNI. Maybe they are of interest too?