Abstract #3366

Connectome analysis of world class gymnasts using probabilistic multi-shell multi-tissue constrained spherical deconvolution tracking

Wataru Uchida^1,2, Koji Kamagata¹, Christina Andica¹, Hiroyuki Tomita³, Hidefumi Waki³, Mana Kuramochi^1,2, Yuki Takenaka^1,2, Akifumi Hagiwara^1,4, Makoto Fukuo³, Kouhei Tsuruta¹, Issei Fukuaga¹, Syo Murata¹, Mutsumi Harada³, Shigeki Aoki¹, and Hisashi Naito³

¹Department of Radiology, Juntendo University Graduate School of Medicine, Tokyo, Japan, ²Department of Radiological Sciences, Tokyo Metropolitan University Graduate School of Human Health Sciences, Tokyo, Japan, ³Department of Sports Science, Juntendo University Graduate School of Medicine, Tokyo, Japan, ⁴Department of Radiology, University of Tokyo Graduate School of Medicine, Tokyo, Japan

We analyzed the brain anatomical networks between world-class gymnasts and controls using probabilistic Multi-shell, Multi-tissue Constrained Spherical Deconvolution tracking method. Our results showed higher neural connectivities in gymnasts in the brain areas related to motor activity and visual perception. In addition, a positive correlation between difficulty-score (D-score) and brain connectivity was also in the brain areas including auditory, limbic, associative and visual area. In conclusion, our findings can be useful for a better understanding of neural changes related to gymnastic skills.

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