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Digital Images

Arcuate Fasiculus, tractography

Katja Heuer and Roberto Toro

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Credit: Arcuate Fasiculus, tractography. Credit: Katja Heuer and Roberto Toro. Attribution 4.0 International (CC BY 4.0)

About this work


The image shows a reconstruction of the physical connections between the different regions in an adult human brain. Via these connections, brain activity can travel from one part of the brain to another. The data for this image was obtained using diffusion-weighted magnetic resonance imaging - a non-invasive neuroimaging method that allows us to build detailed representations of brain connections in vivo. The geometry of these connections in the adult brain is of a daunting complexity. At the time of their formation, however, the brain is smaller and its shape simpler. To produce this image we deformed the brain in an attempt to recover this original simplicity. Using similar tools as those of ancient cartographers, we deformed the brain to combine multiple points of view into a single image showing the global structure of the brain's connections. The image shows a mercator transformation of the 3D space embedding a dense human brain tractography. The tractography was computed from high-angular resolution diffusion weighted imaging data. The unfolding was performed from a ventral point of view and shows the arrival of white matter fibres to the neocortex. The cerebellum is at the bottom of the image at the midline, immediately to the sides are the left and right temporal lobes, and the interhemispheric margin appears at the left and right borders of the image. One major fibre bundle has been selected for colorful representation of the arcuate fasciculus, an important part of the network supporting language production and comprehension. Diffusion weighted magnetic resonance imaging (DWI) is a neuroimaging technique where signal intensity at different brain regions is modulated by the local anisotropy of water diffusion. Using DWI data we can evaluate the existence of large white matter fibre bundles, estimate their local direction, and reconstruct their pathways. The resulting reconstruction of the macroscopic structure of brain connections is very complex. We developed a computer program which performs a mercator transformation of the reconstructed streamlines. Our aim was to simplify their geometry to obtain a more intuitive representation of the global brain connectivity.


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