Computational neuroimaging strategies for single patient predictions

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• 作者：K.E. Stephan^a ; ^b ; ^c ; F. Schlagenhauf^d ; ^e ; Q.J.M. Huys^a ; ^f ; S. Raman^a ; E.A. Aponte^a ; K.H. Brodersen^a ; L. Rigoux^a ; ^c ; R.J. Moran^b ; ^g ; J. Daunizeau^a ; ^h ; R.J. Dolan^b ; ⁱ ; K.J. Friston^b ; A. Heinz^d ; ^j
• 关键词：Generative model ; fMRI ; EEG ; Bayesian ; Model selection ; Model comparison ; Model evidence ; Generative embedding ; Classification ; Clustering ; Computational psychiatry ; Translational neuromodeling
• 刊名：NeuroImage
• 出版年：2017
• 出版时间：15 January 2017
• 年：2017
• 卷：145
• 期：part_PB
• 页码：180-199
• 全文大小：1965 K
• 卷排序：145

文摘

Reviews computational neuroimaging strategies for single patient predictions. Generative models for inferring individual disease mechanisms in psychiatry and neurology. Mapping inferred mechanisms to clinical predictions by Bayesian model selection and generative embedding. Links a mechanistic model-based approach to statistical perspectives by machine learning.