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Intensive Courses on Statistical Methods for Brain Data
일시: 2011년 10월 14일(금)~15일(토)
장소: 서울대학교 상산수리과학관 101호
[Organizing Committee]
- 임요한 (서울대학교)
- 황동욱 (국가수리과학연구소)
[Invited Speakers]
- 김용대 (서울대학교 통계학과)
- 예종철 (KAIST 바이오및뇌공학과)
- 임요한 (서울대학교 통계학과)
- 정무경 (U. Wisconsin-Madison / 서울대학교 뇌인지과학과)
[Program]
Oct 14 (Friday)
09:00-09:20 등록
09:20-09:30 개회사
09:30-12:20 임요한 - Multiple Testing Procedure
09:30-10:20 Motivation and Overview
- Multiple testing problem and brain data analysis
- Multiple testing framework
- Errors in multiple testing
10:30-11:20 Methods
- General type-I error rate
- Family wise error rate
- Tail probability error rate
11:30-12:20 Application and Other Testing issues
12:30-14:00 Lunch
14:00-16:50 예종철 - Random Field Theory for Neuroimage Analysis
14:00-14:50 Random Field Theory I
- Excursion probability and p-value
- Gaussian fields
15:00-15:50 Random Field Theory II
- Calculation of excursion probability
. Rice's formula for stochastic process
. Homogeneous random fields
. Inhomogeneous random fields
16:00-16:50 Application to Neuroimage Analysis and Conclusion
17:30-19:30 Banquet
Oct 15 (Saturday)
09:00-11:50 김용대 - Sparse Regression
09:00-19:50 Introduction to Sparse Regression
- Variable selection
- Penalized regression
- Lasso
- Nonconvex penalties - Various penalties
10:00-10:50 Algorithm and Asymptotics
- Solution path algorithms for Lasso
- CCCP algorithm for nonconvex penalties
- Persistency, selection consistency, and oracle property
- Minimax optimality
11:00-11:50 Sparse Covariance Estimation and Application to Brain Network
- Covariance selection problem
- Sparse covariance estimation
- Semidefinite program
- Application to brain network
12:00-13:30 Lunch
13:30-16:20 정무경 - Neuroimage Analysis with SurfStat
13:30-14:20 Basic Brain Image Processing
- Volume data processing and visualization
- Surface data processing and visualization
- Network data processing and visualization
14:30-15:20 Statistical Computing in Brain Imaging
- Image smoothing (volume, surface, network)
- Monte-Carlo simulation
- Simulating random fields
- Simulating random networks
15:30-16:20 SurfStat and Its Extension
- Cortical structure and thickness modeling
- Subcortical structure (amygdala, hippocampus) modeling
- Multivariate linear models with SurfStat
- Mixed effect models with SurfStat
- Brain network analysis
16:30-17:00 Closing
[Registration]
- 참가신청 마감: 2011년 10월 7일 (금)
- 참가비: 없음
- 참가신청 (NIMS 등록페이지로 연결)
[Venue]
- 서울대학교 상산수리과학관 101호 (DAUM 지도 연결)
[Co-organized by]
- 계산뇌과학회
- 서울대학교 데이터과학 연구센터
[Sponsored by]
- 국가수리과학연구소 (NIMS)
- 서울대학교 데이터과학 연구센터
[Contact]
- E-mail: office@cbrain.org
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