A review on neural network models of schizophrenia and autism spectrum disorder
作者: Pablo LanillosDaniel OlivaAnja PhilippsenYuichi YamashitaYukie NagaiGordon Cheng
作者单位: 1Donders Institute for Brain, Cognition and Behavior, Radboud University, Nijmengen, The Netherlands
2Institute for Cognitive Systems, Technical University of Munich, Arcisstraße 21, Munich, Germany
3International Research Center for Neurointelligence, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo, Japan
4Department of Functional Brain Research, National Center of Neurology and Psychiatry, 4-1-1 Ogawa-Higashi, Kodaira, Tokyo, Japan
刊名: Neural Networks, 2020, Vol.122 , pp.338-363
来源数据库: Elsevier Journal
DOI: 10.1016/j.neunet.2019.10.014
关键词: Neural networksSchizophreniaAutism spectrum disorderComputational psychiatryPredictive coding
原始语种摘要: Abstract(#br)This survey presents the most relevant neural network models of autism spectrum disorder and schizophrenia, from the first connectionist models to recent deep neural network architectures. We analyzed and compared the most representative symptoms with its neural model counterpart, detailing the alteration introduced in the network that generates each of the symptoms, and identifying their strengths and weaknesses. We additionally cross-compared Bayesian and free-energy approaches, as they are widely applied to model psychiatric disorders and share basic mechanisms with neural networks. Models of schizophrenia mainly focused on hallucinations and delusional thoughts using neural dysconnections or inhibitory imbalance as the predominating alteration. Models of autism rather...
全文获取路径: Elsevier  (合作)
影响因子:1.927 (2012)

  • schizophrenia 精神分裂症
  • autism 孤独症
  • disorder 无序
  • psychiatry 精神病学
  • delusional 妄想的
  • excessive 过度
  • network 网络
  • neural 神经系统的
  • spectrum 光谱
  • sensorimotor 感觉运动的