Group Modeling for fMRI. Thomas Nichols, Ph.D. Assistant Professor Department of Biostatistics http://www.sph.umich.edu/~nichols IPAM MBI July 21, 2004. Overview. Mixed effects motivation Evaluating mixed effects methods Case Studies Summary statistic approach (HF) SPM2 FSL3
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Thomas Nichols, Ph.D.
Department of Biostatistics
July 21, 2004
... all the same
... all alluding to multiple sources of variation
(in contrast to fixed effects)
Consider this RT data
Here, two sources
Within subject var.
Between subject var.
Causes dependence in
3 Ss, 5 replicated RT’sRandom Effects Illustration
Distribution of population effect
A: Active, flashing checkerboard B: Baseline, fixation
6 blocks, ABABAB Just consider block averages...
Item recognition task
1-sample t test on diff. imgs
uRF = 9.87uBonf = 9.805 sig. vox.
uPerm = 7.67 58 sig. vox.
378 sig. vox.
Smoothed Variance t Statistic,Nonparametric Threshold
t11Statistic, Nonparametric Threshold
t11Statistic, RF & Bonf. Threshold
Permutation Distn Maximum t11Small GroupfMRI Example
Working memory data: Marshuetz et al (2000)
First-level, combines sessions
Second-level, combines subjects
Third-level, combines/compares groups
Beckman et al., 2003