Linked Life Data

19166942

Source:http://linkedlifedata.com/resource/pubmed/id/19166942

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
3
pubmed:dateCreated
2009-3-9
pubmed:abstractText
The intra-class class correlation coefficient (ICC) is a prominent statistic to measure test-retest reliability of fMRI data. It can be used to address the question of whether regions of high group activation in a first scan session will show preserved subject differentiability in a second session. With this purpose, we present a method that extends voxel-wise ICC analysis. We show that voxels with high group activation have more probability of being reliable, if a subsequent session is performed, than typical voxels across the brain or across white matter. We also find that the existence of some voxels with high ICC but low group activation can be explained by stable signals across sessions that poorly fit the HRF model. At a region of interest level, we show that our voxel-wise ICC calculation is more robust than previous implementations under variations of smoothing and cluster size. The method also allows formal comparisons between the reliabilities of given brain regions; aimed at establishing which ROIs discriminate best between individuals. The method is applied to an auditory and a verbal working memory task. A reliability toolbox for SPM5 is provided at http://brainmap.co.uk.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:month
Apr
pubmed:issn
1095-9572
pubmed:author
pubmed:issnType
Electronic
pubmed:day
15
pubmed:volume
45
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
758-68
pubmed:meshHeading
pubmed:year
2009
pubmed:articleTitle
Measuring fMRI reliability with the intra-class correlation coefficient.
pubmed:affiliation
Centre for Neuroimaging Sciences, Institute of Psychiatry, King's College London, London, UK. alejandro.caceres@iop.kcl.ac.uk
pubmed:publicationType
Journal Article, Research Support, Non-U.S. Gov't