Abstract

Structural connectivity of the brain can be conceptionalized as a multiscale organization. The present study is built on 3D-Polarized Light Imaging (3D-PLI), a neuroimaging technique targeting the reconstruction of nerve fiber orientations and therefore contributing to the analysis of brain connectivity. Spatial orientations of the fibers are derived from birefringence measurements of unstained histological sections that are interpreted by means of a voxel-based analysis. This implies that a single fiber orientation vector is obtained for each voxel, which reflects the net effect of all comprised fibers. We have utilized two polarimetric setups providing an object space resolution of 1.3 μm/px (microscopic setup) and 64 μm/px (macroscopic setup) to carry out 3D-PLI and retrieve fiber orientations of the same tissue samples, but at complementary voxel sizes (i.e., scales). The present study identifies the main sources which cause a discrepancy of the measured fiber orientations observed when measuring the same sample with the two polarimetric systems. As such sources the differing optical resolutions and diverging retardances of the implemented waveplates were identified. A methodology was implemented that enables the compensation of measured different systems' responses to the same birefringent sample. This opens up new ways to conduct multiscale analysis in brains by means of 3D-PLI and to provide a reliable basis for the transition between different scales of the nerve fiber architecture.

Highlights

  • Decoding the human brain is one of the major targets for neuroscientists and researchers around the world

  • Correlation between large-area polarimeter (LAP) and polarizing microscope (PM) Measurements The fiber direction angles and retardation values measured with the PM and the LAP were compared in scatterplots

  • The main purpose of this study was to develop a strategy to combine polarized light imaging (3D-PLI) measurements which were captured at different optical resolutions obtained with different setups

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Summary

Introduction

Decoding the human brain is one of the major targets for neuroscientists and researchers around the world. The mapping of the nerve fiber architecture of the brain is a multiscale challenge as the size of the structures range from a few nanometers for the diameter of microfilaments to several centimeters for long distance inter-hemispheric fibers. It is difficult or even impossible to integrate most of the multimodal imaging data sets. This is caused by the lack of tools to bridge different scales and types of structural descriptions, preventing the investigation of the organization of the brain at different levels of detail. A solution of such a problem is to realize a “multiscale approach” with imaging setups that provide complementary resolutions, and rely on the same imaging technique

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