Estimation of vocational aptitudes using functional brain networks

Yul Wan Sung, Yousuke Kawachi, Uk Su Choi, Daehun Kang, Chihiro Abe, Yuki Otomo, Seiji Ogawa

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)


The success of human life in modern society is highly dependent on occupation. Therefore, it is very important for people to identify and develop a career plan that best suits their aptitude. Traditional test batteries for vocational aptitudes are not oriented to measure developmental changes in job suitability because repeated measurements can introduce bias as the content of the test batteries is learned. In this study, we attempted to objectively assess vocational aptitudes by measuring functional brain networks and identified functional brain networks that intrinsically represented vocational aptitudes for 19 job divisions in a General Aptitude Test Battery. In addition, we derived classifiers based on these networks to predict the aptitudes of our test participants for each job division. Our results suggest that the measurement of brain function can indeed yield an objective evaluation of vocational aptitudes; this technique will enable a person to follow changes in one's job suitability with additional training or learning, paving a new way to advise people on career development.

Original languageEnglish
Pages (from-to)3636-3651
Number of pages16
JournalHuman Brain Mapping
Issue number9
Publication statusPublished - 2018 Sep
Externally publishedYes


  • brain function networks
  • classifier
  • multiclass
  • resting-state fMRI
  • support vector machine
  • vocational aptitudes

ASJC Scopus subject areas

  • Anatomy
  • Radiological and Ultrasound Technology
  • Radiology Nuclear Medicine and imaging
  • Neurology
  • Clinical Neurology


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