The in vivo validation of diffusion MRI (dMRI)-based tractography has beenshown to be a challenging task [Maier-hein et al.]. Therefore, we have been investigating how 3D Polarized Light Imaging (3D-PLI) could be used as a validation tool for dMRI-based fiber orientation estimation and tractography. PLI is an optical imaging technique that provides us with high-resolution fiber orientation measurements at micrometer scale. For this reason, it has been presented as a good candidate for the afore mentioned validation tasks [Axer et al,2011, Alimi et al, 2019 submitted]. In some previous works [alimi2017,18isbi,18ismrm,19,19submitted] we introduced an approach to close the resolution gap between dMRI and 3D-PLI. The study of the brain network from the topological point of view has seen an increasing interest in the last years [Sizemore et al, 2018, Chung et al, 2017]. In this work, we show how tractograms obtained at different spatial scales using 3D-PLI human brain datasets can bein spected using homology theory to perform a quantitative comparison between them. In particular, we investigate the persistence of the number of connected components in brain networks estimated from data at different resolutions.