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Determining significance in neuroimaging studies using covariate-modulated false discovery rate
Published on May 23, 20075356 Views
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Chapter list
Advances in False Discovery Rate control applied in Neuroimaging00:02
Outline00:29
Outline01:23
Voxel-based morphometry01:31
Voxel-based morphometry02:09
Vertex-based morphometry02:18
Pial (outside) surface02:54
White matter surface03:03
Wireframe03:11
Multiple comparisons03:57
Multiple comparisons04:04
Searching for interesting results04:27
Outline05:06
Definition05:58
Markov Random Fields06:06
Markov Random Fields06:29
Permutation tests.06:57
Weakness with blob-based methods07:25
The original concept08:03
The method08:07
Graphical08:11
FDR in practice09:03
Outline09:25
Local FDR09:34
The model09:44
The model, cont.10:38
Definition11:02
Definition11:11
Why local?11:30
Histogram of Z-scores11:59
Requirements13:09
Calculating the local FDR13:34
The mixture f (z)14:06
The mixture f (z)14:12
The mixture f (z)14:24
The numerator p0f0(z)14:58
The numerator p0f0(z)15:24
The numerator p0f0(z)15:52
Outline16:49
Covariate Modulated FDR17:03
Microarray example17:38
The model18:48
The model19:00
Definition19:08
Definition19:22
Definition19:35
Compare to Local FDR20:17
The model, II20:42
Calculating cmFDR21:39
Observation21:46
Bin the covariates22:39
Hyperpriors23:40
posterior density24:01
posterior density, cont.24:36
Approximate24:45
Approximate25:11
cmFDR with one bin25:35
Outline26:54
Genetic variation and cortical thickness27:00
BDNF -66328:32
cmFDR reasoning30:55
Comparison31:19
Comparison31:53
Bibliography35:18