An fMRI normative database for connectivity networks using one-class support vector machines.

Human Brain Mapping
João Ricardo SatoEdson Amaro

Abstract

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.

References

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Citations

May 19, 2011·Social Neuroscience·João R SatoJorge Moll
Oct 11, 2012·PloS One·João Ricardo SatoLuis A Rohde
Mar 1, 2016·NeuroImage·Erdem VarolUNKNOWN Alzheimer's Disease Neuroimaging Initiative
Feb 24, 2017·Scientific Reports·Andrea Cristina de Lima-PardiniEdson Amaro
Jun 22, 2017·The World Journal of Biological Psychiatry : the Official Journal of the World Federation of Societies of Biological Psychiatry·João Ricardo SatoRodrigo Affonseca Bressan

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