An fMRI normative database for connectivity networks using one-class support vector machines.
The application of functional magnetic resonance imaging (fMRI) in neuroscience studies has increased enormously in the last decade. Although primarily used to map brain regions activated by specific stimuli, many studies have shown that fMRI can also be useful in identifying interactions between brain regions (functional and effective connectivity). Despite the widespread use of fMRI as a research tool, clinical applications of brain connectivity as studied by fMRI are not well established. One possible explanation is the lack of normal patterns and intersubject variability-two variables that are still largely uncharacterized in most patient populations of interest. In the current study, we combine the identification of functional connectivity networks extracted by using Spearman partial correlation with the use of a one-class support vector machine in order construct a normative database. An application of this approach is illustrated using an fMRI dataset of 43 healthy subjects performing a visual working memory task. In addition, the relationships between the results obtained and behavioral data are explored.
Sato
João Ricardo
JR
Department of Statistics, Institute of Mathematics and Statistics, University of São Paulo, Brazil. jrsatobr@gmail.com
da Graça Morais Martin
Maria
M
Fujita
André
A
Mourão-Miranda
Janaina
J
Brammer
Michael John
MJ
Amaro
Edson
E
D001185:Artificial Intelligence; D001921:Brain / Q000033:anatomy & histology / Q000098:blood supply*; D001931:Brain Mapping; D016206:Databases, Bibliographic / Q000706:statistics & numerical data*; D005260:Female; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods; D008279:Magnetic Resonance Imaging / Q000379:methods*; D008297:Male; D008568:Memory / Q000502:physiology; D008959:Models, Neurological; D009434:Neural Pathways / Q000098:blood supply / Q000502:physiology; D009483:Neuropsychological Tests; D010100:Oxygen / Q000097:blood; D010364:Pattern Recognition, Visual; D010775:Photic Stimulation; D018709:Statistics, Nonparametric
D010100:Oxygen