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Authors:Li-Kai Cheng  Yu-Hsien Chiu  Ying-Chia Lin  Wei-Chi Li  Tzu-Yi Hong  Ching-Ju Yang  Chung-Heng Shih  Tzu-Chen Yeh  Wen-Yih Isaac Tseng  Hsin-Yen Yu  Jen-Chuen Hsieh  Li-Fen Chen
Institution:1. Institute of Brain Science, National Yang Ming Chiao Tung University, Taipei, Taiwan;2. Center for Advanced Imaging Innovation and Research (CAI2R), NYU Grossman School of Medicine, New York, New York, USA;3. Institute of Brain Science, National Yang Ming Chiao Tung University, Taipei, Taiwan

Integrated Brain Research Unit, Department of Medical Research, Taipei Veterans General Hospital, Taipei, Taiwan;4. Institute of Brain Science, National Yang Ming Chiao Tung University, Taipei, Taiwan

Department of Radiology, Taipei Veterans General Hospital, Taipei, Taiwan;5. Institute of Medical Device and Imaging, National Taiwan University College of Medicine, Taipei, Taiwan;6. Graduate Institute of Arts and Humanities Education, Taipei National University of the Arts, Taipei, Taiwan

Abstract:Numerous studies have reported that long-term musical training can affect brain functionality and induce structural alterations in the brain. Singing is a form of vocal musical expression with an unparalleled capacity for communicating emotion; however, there has been relatively little research on neuroplasticity at the network level in vocalists (i.e., noninstrumental musicians). Our objective in this study was to elucidate changes in the neural network architecture following long-term training in the musical arts. We employed a framework based on graph theory to depict the connectivity and efficiency of structural networks in the brain, based on diffusion-weighted images obtained from 35 vocalists, 27 pianists, and 33 nonmusicians. Our results revealed that musical training (both voice and piano) could enhance connectivity among emotion-related regions of the brain, such as the amygdala. We also discovered that voice training reshaped the architecture of experience-dependent networks, such as those involved in vocal motor control, sensory feedback, and language processing. It appears that vocal-related changes in areas such as the insula, paracentral lobule, supramarginal gyrus, and putamen are associated with functional segregation, multisensory integration, and enhanced network interconnectivity. These results suggest that long-term musical training can strengthen or prune white matter connectivity networks in an experience-dependent manner.
Keywords:brain asymmetry  emotion  graph theory  language  structural connectivity  vocal training
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