For their work, scientists used brains obtained from 10 posthumous donors (five men and five women each).
After scanning, scientists made histologicalslices of each brain 20 µm thick. Every 15 sections were stained for the presence of cell bodies using the Golgi method and scanned. Based on the acquired images, a deep machine learning model, and the Big Brain dataset, probabilistic cytoarchitectonic maps of two separate parts of the metathalamus, the medial geniculate body and the lateral geniculate body, were generated.
Scientists note that the metathalamus plays an importantrole in the processing of visual and auditory information. Knowing the structure, layers, and different regions of this part of the brain is important for understanding the functions and pathologies associated with these feelings. However, to date, there has not been a single three-dimensional histological and structured image of this section of the brain.
“The BigBrain dataset helps us understandthe structure of complex subcortical nuclei,” the authors explain. “And new approaches based on deep learning are being used to study the topography and cellular structure of the metathalamus.”
The created 3D maps are placed in the public domain as part of the EBRAINS electronic atlas. The researchers note that their development can be used by scientists around the world.
The developers emphasize that mappingbrain, in addition to expanding our general knowledge of brain structures, is of great clinical importance. Many neurological disorders and dysfunctions are associated with the metathalamus. Detailed information about these brain structures, together with neuroimaging done on a specific patient, will increase the level of diagnostics and neurosurgery.
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