restplus - resting state fmri v1.21 manual.pdf · 90 roi 1 roi 2 roi 3 roi 4 roi 1 1 roi2 and roi1...
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RESTplus
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1. Download RESTplushttp://www.restfmri.net/forum/RESTplusV1.2
2. Install RESTplusMATLAB 2014a
SPM12(https://www.fil.ion.ucl.ac.uk/spm/software/spm12/)
3. NoticeDo not include any Chinese characters or specific symbol.
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Install RESTplus
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Install RESTplus
Data arrangement
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Data arrangement
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IMADCMnone
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Data arrangement
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…… ……control_001 patient_001
Work directory
(work_dir)
Functional data folder
(REST)
Structure data folder
(STRUC)
control_001 patient_001
DICOM files
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Example data
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Example data
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DICOM or NIFTI
Example data
01.Pipeline
ALFF calculation
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Pipeline
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Slice timing
(Poldrack, Mumford et al. 2011)
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Slice order could be Matlab formula : [1:2:33 2:2:32]
Motion correction
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Normalization
Individual brains are highly variable in their size and
shape
Data be integrated across individuals (group analyses)
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Transform the brain images to reduce the variability between individuals and
allow meaningful group analyses.
Normalization
The Talairach atlasThe best-known brain atlas is the one created by Talairach (1967) and subsequently
updated by Talairach & Tournoux (1988).
The MNI templatesWithin the fMRI literature, the most common templates used for spatial normalization are those
developed at the Montreal Neurological Institute, known as the MNI templates.
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Spatial smoothing
The most common means of spatial smoothing is the
convolution of the three-dimensional image with a
three-dimensional Gaussian kernel.
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Filter (low-frequency)
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Before filter
After filter
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01b_Pipeline_Results
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02. Statistical analysis
Two sample t-test
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Head motion
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03. Viewer
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04. Summary
RESTplus
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05. pipeline
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06. Other metrics
Fractional ALFF (fALFF)
70Zou Q H, Zhu C Z, Yang Y, et al. An improved approach to detection of amplitude of low-frequency fluctuation (ALFF) for
resting-state fMRI: fractional ALFF[J]. Journal of neuroscience methods, 2008, 172(1): 137-141.
1 DICOM to NIFTI
2 Remove first n time points
3 Slice timing
4 Realign
5 Reorient
6 Normalize
7 Smooth
8 Detrend
9 fALFF
fALFF
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Functional connectivity
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Voxel wise functional connectivity
(Fox et al., PNAS, 2005)
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ROI wise functional connectivity
(Liao & Zhang et al., HBM, 2011)
Functional connectivity
1 DICOM to NIFTI
2 Remove first n time points
3 Slice timing
4 Realign
5 Reorient
6 Normalize
7 Smooth
8 Detrend
9 Nuisance covariates regression
10 Filter
11 Functional connectivity76
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ROI 1 ROI 2 ROI 3 ROI 4
ROI 1 1 ROI2 and ROI1 ROI3 and ROI1 ROI4 and ROI1
ROI 2 ROI1 and ROI2 1 ROI3 and ROI2 ROI4 and ROI2
ROI 3 ROI1 and ROI3 ROI2 and ROI3 1 ROI4 and ROI3
ROI 4 ROI1 and ROI4 ROI2 and ROI4 ROI3 and ROI4 1
ROI1 ROI2 ROI3 ROI4
Degree centrality (DC)
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(Salomon et al., JN, 2011)
√ Identify hubs in the human brain
√ Data-diven
√ Voxelwise
Degree centrality
1 DICOM to NIFTI
2 Remove first n time points
3 Slice timing
4 Realign
5 Reorient
6 Normalize
7 Detrend
8 Nuisance covariates regression
9 Filter
10 Degree centrality
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