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神经影像学中的因果推理简介An introduction to causal inference in neuroimaging |
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| 课程网址: | http://videolectures.net/bbci2014_grosse_wentrup_causal_inference... |
| 主讲教师: | Moritz Grosse-Wentrup |
| 开课单位: | 马克斯·普朗克研究所 |
| 开课时间: | 2014-04-03 |
| 课程语种: | 英语 |
| 中文简介: |  |
| 课程简介: | A variety of causal inference methods has been introduced to neuroimaging in recent years, including Causal Bayesian Networks, Dynamic Causal Modeling (DCM), Granger Causality, and Linear Non-Gaussian Acyclic Models (LINGAM). While all these methods aim to provide insights into how brain processes interact, they are based on rather different concepts of causality. In this talk, I will review the theoretical foundations of each of these methods, describe their inherent assumptions, and discuss the resulting consequences for the analysis and interpretation of neuroimaging data. |
| 关 键 词: | 神经影像学; 因果贝叶斯网络; 动态因果建模; 格兰杰因果关系; 线性非高斯非循环模型 |
| 课程来源: | 视频讲座网 |
| 数据采集: | 2021-11-26：zkj |
| 最后编审: | 2021-11-26：zkj |
| 阅读次数: | 86 |