Modeling motor task activation from resting-state fMRI using machine learning in individual subjects

• Published in: Brain imaging and behavior Vol. 15; no. 1; pp. 122 - 132
• Main Authors: Niu, Chen, Cohen, Alexander D., Wen, Xin, Chen, Ziyi, Lin, Pan, Liu, Xin, Menze, Bjoern H., Wiestler, Benedikt, Wang, Yang, Zhang, Ming
• Format: Journal Article
• Language: English
• Published: New York Springer US 01.02.2021; Springer Nature B.V
• Subjects: Biomedical and Life Sciences; Biomedicine; Brain; Brain Mapping; Functional magnetic resonance imaging; Hand; Humans; Independent component analysis; Learning algorithms; Machine Learning; Magnetic Resonance Imaging; Model matching; Neuropsychology; Neuroradiology; Neurosciences; Original Research; Psychiatry; Rest; Sensorimotor system; Functional MRI; Resting state; General linear model; Motor function; Machine learning; Independent component analysis

Resting-state functional MRI (rs-fMRI) has provided important insights into brain physiology. It has become an increasingly popular method for presurgical mapping, as an alternative to task-based functional MRI wherein the subject performs a task while being scanned. However, there is no commonly ac...