京都大å¦åŒ»å¦éƒ¨ / æ±äº¬å¤§å¦å¤§å¦é™¢æ–°é ˜åŸŸå‰µæˆç§‘å¦ç ”究科　　　三浦 å²³[講演者] / é‡Žå£ æ€œ[ノート作æˆè€…]　(Miura,Takashi /)
No.1698
京都大å¦åŒ»å¦éƒ¨ / æ±äº¬å¤§å¦å¤§å¦é™¢æ–°é ˜åŸŸå‰µæˆç§‘å¦ç ”究科　　　三浦 å²³[講演者] / é‡Žå£ æ€œ[ノート作æˆè€…]　(Miura,Takashi /)
Hierarchical Models in the Brain
This paper describes a general model that subsumes many parametric models for continuous data. The model comprises hidden layers of state-space or dynamic causal models, arranged so that the output of one provides input to another. The ensuing hierarchy furnishes a model for many types of data, of arbitrary complexity. Special cases range from the general linear model for static data to generalise
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