Using deep learning to investigate the neuroimaging correlates of psychiatric and neurological disorders: Methods and applications

Deep learning (DL) is a family of machine learning methods that has gained considerable attention in the scientific community, breaking benchmark records in areas such as speech and visual recognition. DL differs from conventional machine learning methods by virtue of its ability to learn the optimal representation from the raw data through consecutive nonlinear transformations, achieving increasingly higher levels of abstraction and complexity. Given its ability to detect abstract and complex patterns, DL has been applied in neuroimaging studies of psychiatric and neurological disorders, which are characterised by subtle and diffuse alterations. Here we introduce the underlying concepts of DL and review…

• FD
  Fundação de Amparo à Pesquisa do Estado de São Paulo

  Award: 2013/05168-7
• MR
  Medical Research Council

  Award: ID99859
• FP
  Fundação para a Ciência e a Tecnologia

  Award: SFRH/BD/103907/2014