Aging effect on head motion: A Machine Learning study on resting state fMRI data
- 1 March 2021
- journal article
- research article
- Published by Elsevier in Journal of Neuroscience Methods
- Vol. 352, 109084
Abstract
No abstract availableKeywords
This publication has 43 references indexed in Scilit:
- Spurious but systematic correlations in functional connectivity MRI networks arise from subject motionNeuroImage, 2012
- The influence of head motion on intrinsic functional connectivity MRINeuroImage, 2012
- Correspondence of the brain's functional architecture during activation and restProceedings of the National Academy of Sciences, 2009
- The Global Signal and Observed Anticorrelated Resting State Brain NetworksJournal of Neurophysiology, 2009
- Effects of age and sex on brain glutamate and other metabolitesMagnetic Resonance Imaging, 2009
- The respiration response function: The temporal dynamics of fMRI signal fluctuations related to changes in respirationNeuroImage, 2008
- Aging influence on functional connectivity of the motor network in the resting stateNeuroscience Letters, 2007
- Consistent resting-state networks across healthy subjectsProceedings of the National Academy of Sciences, 2006
- Age-related decline of dopamine synthesis in the living human brain measured by positron emission tomography with l-[β-11C]DOPALife Sciences, 2006
- Support-vector networksMachine Learning, 1995