组会
- Topic: Combining Multiscale Diffusion Kernels for Learning the Structural and Functional Brain Connectivity
- Speaker: Wen Hongwei
- Date: 10:00 A.M., Friday, Mar 3, 2017
- Place: Intelligent building Meeting Room #6
- Abstract: One of the key strengths of the proposed approach is that it does not require hand-tuning of model parameters but actually learns them as part of the optimization process. The learned parameters may [more...]
- Topic: Modeling the outcome of structural disconnection on resting-state functional connectivity
- Speaker: Wen Hongwei
- Date: 10:30 A.M., Friday, Dec 16, 2016
- Place: Intelligent building Meeting Room #6
- Abstract: A growing body of experimental evidence suggests that functional connectivity at rest is shaped by the un-derlying anatomical structure. Furthermore, the organizational properties of resting-state [more...]
- Topic: 国家奖学金预答辩
- Speaker: Wen Hongwei
- Date: 3:00 P.M., Monday, Oct 10, 2016
- Place: Room 1022
- Abstract: 2016年研究生国家奖学金预答辩
- Topic: 参加2016年国际人类脑图谱会议(Organization for Human Brain Mapping)总结报告
- Speaker: Wen Hongwei
- Date: 10:00 A.M., Friday, Jul 8, 2016
- Place: Room 1022
- Abstract: The Organization for Human Brain Mapping (OHBM) is the primary international organization dedicated to using neuroimaging to discover the organization of the human brain.
- Topic: Similarity network fusion for clinical diagnosis
- Speaker: Wen Hongwei
- Date: 10:00 P.M., Friday, Jun 3, 2016
- Place: Room 1022
- Abstract: Recent technologies have made it cost-effective to collect diverse types of genome-wide data. Computational methods are needed to combine these data to create a comprehensive view of a given disease [more...]
- Topic: Delayed convergence between brain network structure and function in rolandic epilepsy
- Speaker: Wen Hongwei
- Date: 10:00 A.M., Thursday, Jan 21, 2016
- Place: Room 1022
- Abstract: Since SC and FC converge during normal maturation, in this paper, the finding of reduced SC-FC correlation illustrates impaired synergy between brain structure and function. More specifically, since [more...]