Inference by permutation of multi-subject neuroimaging
studies
Inference by permutation of multi-subject neuroimaging
studies
John SucklingBrain Mapping UnitDepartment of PsychiatryUniversity of Cambridge
Acknowledgements: Funded by the Human Brain Project/Neuroinformatics, National Institute of Biomedical Imaging and Bioengineering and the National Instititute of Mental Health. Experimental work supported by GlaxoSmithKline plc. Data collection at the MRI Unit, Maudsley Hospital, London (1.5T) and Wolfson Brain Imaging Centre, Cambridge (3T).
M BrammerE BullmoreJ FadiliC Long
V MaximC OoiL SendurD Welchew
OverviewOverview
Part I: Preliminaries • Software overview• fMRI processing pipeline
Part II: multi-subject experiments• Within-group activation mapping• Categorically designed experiments• Factorally designed experiments
Brain Activation and Morphological Mapping (BAMM)
Brain Activation and Morphological Mapping (BAMM)
http://www-bmu.psychiatry.cam.ac.uk/software/
fMRI analysis
Structural analysis
Standard space mapping
Other analysis(SPM, DTI, MT…)
group mapping
categoricaldesign
factorialdesign
Statistical inference
fMRI processingfMRI processing
fMRI analysis
Rigid body mapping onto mean time-series image
Regress quadratic function of displacements and lag=1 onto time-series
Mean zero and linear trend removal
Threshold from histogram
global trendremoval
temporal motioncorrection
geometric motioncorrection
parenchymalmasking
fMRI processingfMRI processing
standard spacemapping
permutation inwavelet domain
response estimationY=X+
R
Estimation via the general linear model (with auto-regressive pre-whitening)
Surrogate time-series with comparable auto-covariance
Affine transformation of observed and surrogate responses
between- and within-group inference
fMRI processingfMRI processing
Processing controlled by scripts and parameter files. Studywide are set via options in the control script (fbamm.csh): # User configurable optionssetenv DUMMIES 0 # No. of dummy scanssetenv SMTHKERNEL 0.0 # Amount of spatial pre-smoothingsetenv PHASE off # Phase: on/offsetenv UNSTD off # Test statistic standardised: on/offsetenv NRANDOM 10 # Number of randomisations
…
and individual parameter files:
/home/user/study/images/subject1/AB012345.12jun04 # subject ID/home/user/study/designmatrix # paradigm design1 # cluster level E(FP)
fMRI processingfMRI processing
Individual & group mapping run from a command script: #!/bin/csh
fbamm.csh < /home/user/study/subject1.paramfbamm.csh < /home/user/study/subject2.paramfbamm.csh < /home/user/study/subject3.paramfbamm.csh < /home/user/study/subject7.paramfbamm.csh < /home/user/study/subject10.paramfbamm.csh < /home/user/study/subject23.param…gbamm.csh < gbamm.param
Group map parameter files:
/home/user/study/subject.list # list of subjects/app/BAMM/templates/MNI/EPI # template/home/user/study/groupmap # output directory1 # cluster level E(FP)
Inference by permutationInference by permutationParametric
• Random sampling: from the population• Random assignment: to treatments • Homogeneity of variance (sphericity)
Permutation
Follows from random assignment (Fisher, 1929): Identify the independent (exchangable) quantity, such that its reordering has no effect on the distribution of test statistic under H0
Within-group activation mappingWithin-group activation mapping
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original
permuted
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1/f–like noise decorrelated coefficientsColored Noise and Computational Inference in Neurophysiological (fMRI) Time Series Analysis: Resampling Methods in Time and Wavelet Domain. E Bullmore et al. 12: 61-78,
Within-group activation mappingWithin-group activation mapping
median observed & permuted responses
aggregate permuted responses
Obtain cluster CVscontrolling FWER
X R
observed
CV+CV-
Bullmore E et al (2003) Practice and difficulty evoke anatomically and pharmacologically dissociable brain activation dynamics. Cerebral Cortex 13: 144-154.
Cluster statisticsCluster statisticsProcedure1. Threshold voxel F (or t ) map @ p<0.052. Aggregate contiguous voxels into 3D clusters3. Calculate sum of supra-threshold F for each
cluster4. Repeat for permuted F maps5. Obtain CV and threshold observed clusters
Activation is both focal and diffuse
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p<0.005
p<0.05
Cluster statisticsCluster statistics
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1.5T 3T
Exp FPExp FP
Obs FP
Obs FP
Null experiment: Estimated type I errors
Between-subject categorically designed experiments
Between-subject categorically designed experiments
Test statistic: slopeof linear model
Permute observations
Obtain cluster CVscontrolling FWER
DATAYi = 0 + 1G + … +nXn
Yi - observation at voxel iG - independent variableXn - confounds
1/SE(1) - test statistic
cases
controls
Ob
serv
ed v
alu
e
Neural response to pleasant stimuli in anhedonia: Mitterschiffthaler et al Neuroreport 12: 177-182
Between-subject categorically designed experiments
Between-subject categorically designed experiments
Ob
serv
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alu
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Continuous measure
Attenuation of the Neural Response to Sad Faces in Major Depression by Antidepressant Treatment Fu et al. Archives of General Psychiatry (in press)
Between-subject categorically designed experiments
Between-subject categorically designed experiments
Null experiment: Estimated type I errors
voxel cluster area cluster massGlobal, Voxel, and Cluster Tests, by Theory and Permutation, for a Difference Between Two Groups of Structural MR Images of the Brain. E T Bullmore et al IEEE Trans Med Imag 18: 32-42
Between-subject factorially designed experiments
Between-subject factorially designed experiments
Calculate F: maineffects and interaction
Permute observations
Obtain cluster CVscontrolling FWER
DATA
11n 21n 31n
12n 22n 32n
Factor ALevel 1 Level 2 Level 3
Fact
or
BLe
vel 1
Level 2
n=1…N for a balanced design
A1 A2 A3
B1
B2
main effect A
A1 A2 A3
B1
B2
main effect B
exact tests: N =p.V
A1 A2 A3
B1
B2
interaction
Rijn = ijn- i.. - .j. - … approx test: NI p.V
Attenuation of the Neural Response to Sad Faces in Major Depression by Antidepressant Treatment Fu et al. Archives of General Psychiatry (in press)
Between-subject factorially designed experiments
Between-subject factorially designed experiments
Simulation effect (.SNR2.5db ), smoothed Gaussian noise
parametricpermutationcluster
Independent or repeated measures
1.0
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J Suckling and E Bullmore. Permutation Tests for Factorially Designed Neuroimaging Experiments. HBM 22: 193-205
ProcessingProcessing
/home/user/study/subject1/prefix 1 1/home/user/study/subject2/prefix 1 1/home/user/study/subject3/prefix 1 1…
/home/user/study/subject7/prefix 1 2/home/user/study/subject10/prefix 1 2/home/user/study/subject23/prefix 1 2…
/home/user/study/subject45/prefix 2 1/home/user/study/subject46/prefix 2 2/home/user/study/subject48/prefix 2 2
usage: exbamm [-i|r|m] -d FILE -t FILE -o DIR –p VALUE-i|r|m independent, mixed or repeated observations-p eppi/ecpi (default=1)-d design matrix filename-t template image filename-o output directory
Balanced design
FutureFuture
• GUI improvements for modular program linking
• BLU estimation of response in wavelet domain
• Permutation testing of spectral measures
• Inference of spatial statistics in wavelet domain
End