Back

Ultrastructural Analysis of Human Uncinate Fasciculus with Spectral-Focusing Coherent Anti-Stokes Raman Spectroscopy

Perlman, K.; Major, J.; Collin, A.; Pineau-Noel, V.; Mardenli, M.; Jerczynski, S.; Davoli, M. A.; Cohen-Adad, J.; Turecki, G.; Cote, D.; Mechawar, N.

2025-09-19 neuroscience
10.1101/2025.09.18.672977 bioRxiv
Show abstract

Characterizing the ultrastructure of myelin in the human brain is key to understanding the neurobiology of both health and disease. In postmortem human brain tissue, electron microscopy is often technically unfeasible due to poorer tissue quality. The uncinate fasciculus (UF) is a long-range white matter association tract that connects the anterior temporal lobe with the orbitofrontal cortex. The UF is not present in rodents yet is highly expanded in humans and non-human primates. As such, its molecular and ultrastructural properties are virtually unknown. Here, we develop and validate a novel spectral-focusing Coherent Anti-Stokes Raman Spectroscopy (sf-CARS) system coupled with a custom AxonDeepSeg segmentation model to characterize UF ultrastructure in the human postmortem brain (n=6). We provide a proof of concept of this new methodological pipeline in the UF temporal segment and observe that the mean axon diameter detected is 0.93 {micro}m {+/-} 0.54 and mean myelin thickness is 0.48 {micro}m {+/-} 0.14. We also observe that the UF axons are thicker than those in the anterior cingulate cortex white matter. We detail and validate the full methodology, including tissue fixation and sectioning, sf-CARS acquisition settings, as well as the AxonDeepSeg deep learning model parameters such that this pipeline can be utilized by others in the field.

Matching journals

The top 6 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.