腦功能連結分析
Advanced brain connectivity analysis
學期
114-2
學分
0
學分
當期課號
132707
永久課號
LSNS30043
開課單位
神經科學研究所
授課教師
尼大衛、郭文瑞
校區
陽明
類別
選修
上課時間表
| 節 | 週一 |
|---|---|
2 09:00–09:50 | 腦功能連結分析 YL823（陽明） 3 節連堂 |
3 10:10–11:00 | |
4 11:10–12:00 |
* 根據陽明交大上課時間表所列
概述
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先修科目
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備註
無備註
教學方式
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評分方式
課堂參與 class participation: 25% 期末報告 final report: 75%
課程大綱
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週次計畫
| 週次 | 主題 |
|---|---|
| 第 1 週 | Content: Course orientation Homework for the next week: Install Matlab and SPM12 |
| 第 2 週 | Content: Introduction to fMRI data preprocessing using SPM (I) • What is SPM? Basic preprocessing steps of fMRI data • Introduction to dataset • Handout of dataset Homework for the next week: Import data into SPM Preprocess data of all 10 subjects Install DPARSF Read DPARSF and DPABI papers |
| 第 3 週 | Content: Introduction to fMRI data preprocessing using SPM (II) • Student discussion of data preprocessing • How to quality check your data Conceptual introduction to functional brain connectivity Functional connectivity using DPARSF • How to preprocess data in DPARSF (linear detrend, regression, filter) • Define seed points • Run FC analysis • How to setup a contrast • How to do 1-sample t-test in SPM Homework for the next week: Choose RSN papers to read Preprocess data in DPARSF for next week calculate FC and SPM |
| 第 4 週 | Content: Student presentation (30 min) of RSN papers Homework for the next week: Hand out DMN and SAL papers to read Choose a paper using DPARSF and seed analysis Make a presentation of the selected paper |
| 第 5 週 | Content: Student presentation (20-30 min) of selected paper Homework for the next week: Do seed-based analysis and calculate FC for selected seed point Prepare presentation of seed analysis |
| 第 6 週 | Content: Student presentation of selected seed point analysis (compare with paper) More about SPM • What is the meaning of the files generated by SPM? What is the GLM? Homework for the next week: Read paper about MATLAB toolbox (Zhou et al., 2009) |
| 第 7 週 | Children's Day and Qingming Festival Holiday |
| 第 8 週 | Content: Other types of functional connectivity • MATLAB toolbox • Time lag • Coherence • Mutual information Show how to extract time series in DPARSF Other programs for visualization and atlases • MNI coordinates • XJVIEW • MRIcron • WFU pickatlas AAL3 Homework for the next week: Extract time series for multiple ROIs and do further analysis Prepare presentation for next week |
| 第 9 週 | Content: Students present their findings of time-series analysis Homework for the next week: Read GSR papers |
| 第 10 週 | Content: Issues with global signal regression • What is global signal regression? Why is it a problem? The multiple comparisons issue • What is it? • Different approaches (FDR, FWE, cluster vs voxel, TFCE) Homework for the next week: Recalculate FC with GSR and compare with old results Prepare presentation of GSR results |
| 第 11 週 | Content: Student presentations of results and feedback • With vs. without GSR Homework for the next week: Calculate global signal as a seed and do FC, SPM, time-lag etc. |
| 第 12 週 | Content: Student presentations of results and feedback • Seed-to-seed FC and the relationship with FC from whole-brain mask (global signal) Homework for the next week: Install GIFT toolbox Read ICA papers |
| 第 13 週 | Content: Introduction to ICA • What is ICA? • Noise removal • Identification of functional networks • Introduction to GIFT toolbox Homework for the next week: Do ICA on smoothed data Prepare presentation of ICA results |
| 第 14 週 | Content: Student presentation of ICA results • Discussion of issues with data processing for the report Homework for the next week: Calculate SPM regression with GS STD or RMS for seed points (positive/ negative contrasts) |
| 第 15 週 | Content: • Student presentation regression results #1 Homework for the next week: Write final report |
| 第 16 週 | Content: • Student presentation regression results #2 Homework for the next week: Write final report |
教科書
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