Spatial Filtering Methods in MEG. Part 3: Template Normalization and Group Analysis"

Transcription

1 Spatial Filtering Methods in MEG Part 3: Template Normalization and Group Analysis" Douglas Cheyne, PhD" Program in Neurosciences and Mental Health" Hospital for Sick Children Research Institute " &" Department of Medical Imaging " University of Toronto"

2 BrainWave: Data Organization and Preprocessing Steps Classify and epoch MEG datasets Raw datasets Import CTF data epoch data by condition ~/motor_experiment/s001_motor_cond1.ds ~/motor_experiment/s001_motor_cond2.ds ~/motor_experiment/s002_motor_cond1.ds ~/motor_experiment/s002_motor_cond2.ds mark data events using DataEditor or custom scripts 2. epoch continuous datasets into one dataset per condition, should be same length (e.g., for comparing time courses) 3. each dataset name must begin with <subjectid> code followed by underscore 4. options for pre-filtering to remove filter artifacts, rejecting noisy trials or eye-blinks

3 BrainWave: Data Organization and Preprocessing Steps Importing MRI and creating head models MRI data (DICOM) Import MRI ~/motor_experiment/s001_mri/s001.nii ~/motor_experiment/s002_mri/s001.nii import MRI data (from DICOM or existing.mri file) 2. mark fiducial locations (will import from.mri if they are already defined) 3. extract MRI surfaces using FSL* 4. compute single sphere or multisphere head models for each dataset * can also load polhemus or other shapes in CTF format (i.e., in MEG coordinates / cm)

4 MRI import and Head Models z x y Dewar coordinate system (origin at reference array origin) ( 27 cm above head) (rotated 45 deg to head direction) Head coordinate system (based on head coils) (origin is mid-point between ears)

5 The spherical model y z + For MRI based head model: Need best fit sphere origin in Head Coordinate System Default origin: (x=0, y=0, z=5 cm) Sarvas (1987) Single sphere forward model: only need to know location of sphere relative to point of measurement

6 MRI surface extraction (FSL) FSL uses extract triangulated inner and outer skull and scalp surfaces Surfaces saved in voxel relative coordinates in mesh file (*.off) requires knowledge of head center (fiducials) inner skull surface + Best-fit sphere to inner skull surface

7 The Multisphere head model compromise between realistic model and single-sphere model provides small correction for non-spherical portions of head does not provide globally optimum solution for all sources frontal sensor occipital sensor Best-fit sphere to surface patch closest to sensor

8 BrainWave: MRI import and Head Models BrainWave MRIViewer module: surfaces are in voxel coordinates (independent of fiducials) shapes are in head coordinates (relative to fiducials) Head model (*.hdm) files: stores head model, i.e., sphere origin (s) in head coordinates

9 BrainWave: MRI import and Head Models Head model (*.hdm) file

10 BrainWave: Template Normalization and Group Analysis SPM and Template Normalization of Source Images: MEG coordinates MNI coordinates

11 Template normalization using SPM Co-registered MRI " BG.nii" Beamformer Source Image" image_xxx_.svl" Normalized Source Image" wimage_xxx_.nii" bounding box" in MEG coordinates" [ ]" trilinear " interpolation" SPM Linear and non-linear " normalization parameters" S001_resl_-10_10_-8_8_-2_14_sn3d.mat" " resampled MRI " S001_resl_-10_10_-8_8_-2_14.nii" MNI template brain" Overlay on Template Brain " (MRIcron)"

12 BrainWave: Template Normalization and Group Analysis Talairach vs MNI coordinates default template is MNI152 (ICBM152) template (can use others) peak locations can be listed in MNI or Talairach coordinates conversion between MNI to Talairach coords uses Matthew Brett s algorithm (mni2tal.m, tal2mni.m) Brodmann areas (BA) and atlas labels are provided using talairach.org database (closest gray matter within 5 mm search) MNI coordinates are RAS relative to origin at anterior commissure Talairach atlas MNI template

13 BrainWave: Template Normalization and Group Analysis What if I don t have an MRI? Step 1. Load a template MRI w/ fiducials The Colin-27 (CH2.nii) template is provided as default A high resolution MRI images from 27 T1 scans of Collin Holmes normalized to MNI template Step 2. Load digitized surface points (e.g., from Polhemus digitizer) Step 3. Warp template to surface points (uses SPM8 iterative closest point (ICP) algorithm) Step 4. Save warped template as surrogate MRI for analysis

14 BrainWave: MRI import and Head Models Plotting virtual sensors fortalairach coordinates: virtual sensors must be computed using MEG coordinates ( real sensor space ) requires unwarping from template coord. back to subject s MEG coord. option for exact unwarping or searching for original peak activation in image

15 Statistical Thresholding Omnibus Permutation Nichols and Holmes (2001) Nonparameteric permutation tests for functional neuroimaging: a primer with examples. Hum Brain Mapp. 15:1-25 based on principle of exchangeability null hypothesis: no effect of subtraction order (A-B) or (B-A) permute (randomize) all possible orders (A-B, B-A) across subjects For N subjects, max. # of permutations 2 N, min. p value = 1/permutations for > 11 subjects # perms set to 2048, randomly selected (Monte Carlo) uses maximal statistic or omnibus test to control for multiple comparisons Permutation distribution Threshold (p<0.05) = 95% percentile

16 Statistical Thresholding Omnibus Permutation Normalized " Subject Images (N=8)" 1" -1" 1" Randomly flip images, then average" Select largest value in average" Repeat for k " permutations (= 2 8 = 256)" Add value to distribution" Permutation Distribution" 1" Select Threshold* (p < 0.5)" -1" 1" 1" -1" *Smallest p-value = 0.004

17 Statistical Thresholding Omnibus Permutation Effect of # of subjects (permutations on null distribution) Permutation includes activation (biased by largest value in image) excludes activation (less conservative) Chau W. McIntosh R., Robinson S., M. Schultz, Pantev C. (2004) Improving permutation test power for group analysis of spatially filtered MEG data. NeuroImage 23:

18 Organization of BrainWave output files: S001_motor_cond1.ds/ CTF data structures.ave and.cov files saved in text files to speed up processing.hdm head model files (one for each.ds folder) S001_motor_cond1.ds/ANALYSIS all generated image files for this subject (.svl, *.nii, *w.nii) list files for individual subject images and data S001_MRI/ S001.nii - co-registered MRI for subject S001 (NIfTI) S001.mat -.mat file containing co-registration information S001_resl_<BB*>_.nii - resliced MRI file used in template normalization S001_resl_<BB*>_sn3d.mat - normalization parameters (used by SPM) extracted surface files (*.off) - surface meshes created by FSL *BB = bounding box (e.g., _-10_10_-8_8_2_14)

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