Linked Life Data

10642733

Source:http://linkedlifedata.com/resource/pubmed/id/10642733

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
1
pubmed:dateCreated
2000-3-14
pubmed:abstractText
Most statistical methods for assessing activated voxels in fMRI experiments are based on correlation or regression analysis. In this context, the main assumptions are that the baseline can be described by a few known basis functions or variables and that the effect of the stimulus, i.e., the activation, stays constant over time. As these assumptions are in many cases neither necessary nor correct, a new dynamic approach that does not depend on those assumptions will be presented. This allows for simultaneous nonparametric estimation of the baseline and, as an important feature, of time-varying effects of stimulation. This method of estimating the stimulus related areas of the brain furthermore provides the possibility to analyze the temporal and spatial evolution of the activation within an fMRI experiment.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:month
Jan
pubmed:issn
0740-3194
pubmed:author
pubmed:issnType
Print
pubmed:volume
43
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
72-81
pubmed:dateRevised
2006-11-15
pubmed:meshHeading
pubmed:year
2000
pubmed:articleTitle
Dynamic models in fMRI.
pubmed:affiliation
Max-Planck-Institute of Psychiatry, Munich, Germany. goessl@mpipsykl.mpg.de
pubmed:publicationType
Journal Article, Research Support, Non-U.S. Gov't