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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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

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alu

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Neural response to pleasant stimuli in anhedonia: Mitterschiffthaler et al Neuroreport 12: 177-182

Between-subject categorically designed experiments

Between-subject categorically designed experiments

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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

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vel 1

Level 2

n=1…N for a balanced design

A1 A2 A3

B1

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main effect A

A1 A2 A3

B1

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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

0.0

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