Dissociating functional brain networks by decoding the between-subject variability

In this study we illustrate how the functional networks involved in a single task (e.g. the sensory, cognitive and motor components) can be segregated without cognitive subtractions at the second-level. The method used is based on meaningful variability in the patterns of activation between subjects...

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Bibliographic Details
Published in:	NeuroImage (Orlando, Fla.) Vol. 45; no. 2; pp. 349 - 359
Main Authors:	Seghier, Mohamed L., Price, Cathy J.
Format:	Journal Article
Language:	English
Published:	United States Elsevier Inc 01.04.2009 Elsevier Limited Academic Press
Subjects:	Across-subject variability Adolescent Adult Aged Between-subject variance Brain Brain - physiology Cognition - physiology Cognitive subtractions Computer Simulation Decision making Default network Female Functional MRI Fuzzy clustering Humans Image Interpretation, Computer-Assisted - methods Inter-individual variability Language Magnetic Resonance Imaging - methods Male Middle Aged Models, Neurological Nerve Net - physiology Networks Reproducibility of Results Second-level analysis Semantic decision Semantics Sensitivity and Specificity Studies Young Adult Cognitive subtractions Networks Fuzzy clustering Language Between-subject variance Inter-individual variability Default network Second-level analysis Functional MRI Across-subject variability Semantic decision
ISSN:	1053-8119, 1095-9572, 1095-9572
Online Access:	Get full text
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