腦功能連結分析

Course orientation

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: Install Matlab and SPM Import data into SPM Preprocess data of single subject

228 Peace Memorial Day

Introduction to fMRI data preprocessing using SPM (II) ‧ Student discussion of data preprocessing Homework for the next week: Preprocess data of 10 subjects

Conceptual introduction to functional brain connectivity Check preprocessed data ‧ How to quality check your data Homework for the next week: Hand out resting state papers about DMN (Buckner et al. 2019) and SAL (Menon et al., 2015).

Resting-state functional connectivity networks ‧ What is the default mode network? ‧ What is the salience network Homework for the next week: Hand out DPARSF and REST papers to read

Functional connectivity using DPARSF ‧ How to preprocess data in DPARSF (linear detrend, regression, filter) ‧ Define seed points ‧ Run FC analysis ‧ Consultation for papers and preprocessing Homework for the next week: Install DPARSF and preprocess data for next week Preprocess data of 10 subjects for seed-based analysis and calculate FC Choose a paper using DPARSF and seed analysis

Tomb Sweeping Day

Student presentation of papers Functional connectivity using DPARSF ‧ How to setup a contrast ‧ How to do 1-sample t-test in SPM Homework for the next week: Setup contrast and do 1-sample t-test on data with seed-point from chosen paper Prepare presentation of results

Present seed-point analysis and compare with paper Homework for the next week: Read paper about MATLAB toolbox (Zhou et al., 2009)

Other types of functional connectivity ‧ MATLAB toolbox ‧ Time lag ‧ Coherence ‧ Mutual information ‧ Show how to extract time series in DPARSF Homework for the next week: Extract time series for multiple ROIs and do further analysis Prepare presentation for next week

Students present their findings of time-series analysis The multiple comparisons issue ‧ What is it? ‧ Different approaches (FDR, FWE, cluster vs voxel, TFCE, AlphaSIm) Homework for the next week: Read GSR papers

Issues with global signal regression ‧ What is global signal regression? ‧ Why is it a problem? Homework for the next week: Recalculate FC with GSR and compare with old results

Break ‧ Do calculations with GSR ‧ Prepare presentation of GSR results ‧ Start writing your report

Student presentations of results and feedback ‧ With vs. without GSR Homework for the next week: Install GIFT toolbox Read ICA papers

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

Student presentation of ICA results ‧ Discussion of issues with data processing for the report Homework for the next week: Prepare report for ICA and seed-point analysis

(1) Hand in final report (2) Extra topics chosen by students