IMR Press / JIN / Volume 20 / Issue 3 / DOI: 10.31083/j.jin2003074
Open Access Brief Report
Human locomotion-control brain networks detected with independent component analysis
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1 Key Laboratory of Biomechanics and Mechanobiology (Beihang University), Ministry of Education, Beijing Advanced Innovation Center for Biomedical Engineering, School of Biological Science and Medical Engineering, Beihang University, 100083 Beijing, China
2 Beijing Key Laboratory of Rehabilitation Technical Aids for Old-Age Disability, Key Laboratory of Neuro-functional Information and Rehabilitation Engineering of the Ministry of Civil Affairs, National Research Center for Rehabilitation Technical Aids, 100176 Beijing, China
*Correspondence: (Yubo Fan)
J. Integr. Neurosci. 2021, 20(3), 695–701;
Submitted: 4 July 2021 | Revised: 10 August 2021 | Accepted: 24 August 2021 | Published: 30 September 2021
Copyright: © 2021 The Author(s). Published by IMR Press.
This is an open access article under the CC BY 4.0 license (

Walking is a fundamental movement skill in humans. However, how the brain controls walking is not fully understood. In this functional magnetic resonance imaging study, the rhythmic, bilaterally alternating ankle movements were used as paradigm to simulate walking. In addition to the resting state, several motor tasks with different speeds were tested. Independent component analysis was performed to detect four components shared by all task conditions and the resting state. According to the distributed brain regions, these independent components were the cerebellum, primary auditory cortex–secondary somatosensory cortex–inferior parietal cortex–presupplementary motor area, medial primary sensorimotor cortex–supplementary area–premotor cortex–superior parietal lobule, and lateral primary somatosensory cortex–superior parietal lobule–dorsal premotor cortex networks, which coordinated limb movements, controlled the rhythm, differentiated speed, and performed a function as a basic actor network, respectively. These brain networks may be used as biomarkers of the neural control of normal human walking and as targets for neural modulation to improve different aspects of walking, such as rhythm and speed.

Human walking
Motor control
Brain network
Independent component analysis
Fig. 1.
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