Linked Life Data

19166946

Source:http://linkedlifedata.com/resource/pubmed/id/19166946

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
4
pubmed:dateCreated
2009-3-20
pubmed:abstractText
A visual task for semantic access involves a number of brain regions. However, previous studies either examined the role of each region separately using univariate approach, or analyzed a single brain network using covariance connectivity analysis. We hypothesize that these brain regions construct several functional networks underpinning a word semantic access task, these networks being engaged in different cognitive components with distinct temporal characters. In this paper, multivariate independent component analysis (ICA) was used to reveal these networks based on functional magnetic resonance imaging (fMRI) data acquired during a visual and an auditory word semantic judgment task. Our results demonstrated that there were three task-related independent components (ICs), corresponding to various cognitive components involved in the visual task. Furthermore, ICA separation on the auditory task showed consistency of the results with our hypothesis, regardless of the input modalities.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:month
May
pubmed:issn
1095-9572
pubmed:author
pubmed:issnType
Electronic
pubmed:day
1
pubmed:volume
45
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
1347-58
pubmed:meshHeading
pubmed:year
2009
pubmed:articleTitle
Multiple neural networks supporting a semantic task: an fMRI study using independent component analysis.
pubmed:affiliation
School of Information Science and Technology, Beijing Normal University, Beijing, China.
pubmed:publicationType
Journal Article, Research Support, Non-U.S. Gov't