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Description
The medial geniculate nucleus (MGB) is part of the metathalamus and plays an important role in processing auditory information. Previous maps of the human brain did not include subdivisions of the MGB – limiting their use for data integration, modelling and simulation. Here we aim at overcoming this limitation by creating cytoarchitectonic maps of the MGB in the BigBrain (Amunts et al., 2013) with the help of a deep-learning based brain mapping tool (Schiffer et al., 2020). In a first step the MGB was analyzed on 57 sections of the BigBrain dataset based on cytoarchitectonic criteria. Three subdivisions were identified and mapped in both hemispheres. In a next step, a deep-learning based tool with a convolutional neural network architecture was trained to delineate these subdivisions on additional 132 sections of the BigBrain. After an initial quality check, the maps were non-linearly transformed into the 3D BigBrain space and smoothed. The resulting whole brain maps serve as a histological reference for clinical and neuroscientific research investigating medial geniculate function and accompany recent advances in spatial resolution of in vivo imaging techniques therein. The maps are publicly available and can be accessed via the EBRAINS Knowledge Graph and the Human Brain Project’s interactive atlas viewer (https://interactive-viewer.apps.hbp.eu/).
