human: Given a node-centered hypergraph: <hypergraph>, where nodes represent authors and hyperedges represent groups of authors who co-authored the same paper.

Details of the hypergraph:
Center node: "White matter plasticity in the corticospinal tract of musicians: A diffusion tensor imaging study"
  Abstract: Abstract   With the advent of diffusion tensor imaging (DTI), the study of plastic changes in white matter architecture due to long-term practice has attracted increasing interest. Professional musicians provide an ideal model for investigating white matter plasticity because of their early onset of extensive auditory and sensorimotor training. We performed fiber tractography and subsequent voxelwise analysis, region of interest (ROI) analysis, and detailed slicewise analysis of diffusion parameters in the corticospinal tract (CST) on 26 professional musicians and a control group of 13 participants. All analyses resulted in significantly lower fractional anisotropy (FA) values in both the left and the right CST in the musician group. Furthermore, a right-greater-than-left asymmetry of FA was observed regardless of group. In the musician group, diffusivity was negatively correlated with the onset of musical training in childhood. A subsequent median split into an early and a late onset musician group (median = 7 years) revealed increased diffusivity in the CST of the early onset group as compared to both the late onset group and the controls. In conclusion, these DTI-based findings might indicate plastic changes in white matter architecture of the CST in professional musicians. Our results imply that training-induced changes in diffusion characteristics of the axonal membrane may lead to increased radial diffusivity as reflected in decreased FA values.

Connected through hyperedge HE-1 (induced by source paper "Enhancement of auditory-evoked potentials in musicians reflects an influence of expertise but not selective attention"):
  with members:
    (none)

Question: Please tell me which research area the center author belongs to. The 4 classes are: Computer science, Mathematics, Engineering, Economics, Psychology, Business. Directly output the class name.

gpt: Economics