Neurobiologically interpretable causal connectome for predicting young adult depression: A graph neural network study.

Journal: Journal of affective disorders
Published Date:

Abstract

BACKGROUND: There is a surprising lack of neuroimaging studies of depression that not only identify the whole brain causal connectivity features but also explore whether these features have neurobiological correlates.

Authors

  • SungHwan Kim
    Department of Biostatistics, University of Pittsburgh, Pittsburgh, PA, USA Department of Statistics, Korea University, Seoul, South Korea.
  • Su Hyun Bong
    Graduate School of Medical Science and Engineering, Korea Advanced Institute for Science and Technology (KAIST), Daejeon, Republic of Korea.
  • Seokho Yun
    Department of Psychiatry, Yeungnam University Medical Center, Yeungnam University College of Medicine, Daegu, Korea.
  • Dohyun Kim
    Convergence Research Center for Diagnosis, Treatment, and Care of Dementia, Korea Institute of Science and Technology, Seoul, South Korea.
  • Jae Hyun Yoo
    Graduate School of Medical Science and Engineering, Korea Advanced Institute for Science and Technology (KAIST), Daejeon, Republic of Korea; Department of Psychiatry, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea.
  • Kyu Sung Choi
    Graduate School of Medical Science and Engineering, Korea Advanced Institute for Science and Technology (KAIST), Daejeon, Republic of Korea.
  • Haeorum Park
    Graduate School of Medical Science and Engineering, Korea Advanced Institute for Science and Technology (KAIST), Daejeon, Republic of Korea.
  • Hong Jin Jeon
    Department of Psychiatry, Depression Center, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea.
  • Jong-Hoon Kim
    Department of Psychiatry, Gil Medical Center, Gachon University College of Medicine, Gachon University, Incheon, Republic of Korea.
  • Joon Hwan Jang
    Department of Human Systems Medicine, Seoul National University College of Medicine, 103 Daehak-ro, Jongro-gu, Seoul, 03080, Republic of Korea. jhjang602@snu.ac.kr.
  • Bumseok Jeong
    Graduate School of Medical Science and Engineering, Korea Advanced Institute for Science and Technology (KAIST), Daejeon, Republic of Korea.