Functional neuroimaging of human postural control: A systematic review with meta-analysis

• Published in: Neuroscience and biobehavioral reviews Vol. 115; pp. 351 - 362
• Main Authors: Dijkstra, Bauke W., Bekkers, Esther M.J., Gilat, Moran, de Rond, Veerle, Hardwick, Robert M., Nieuwboer, Alice
• Format: Journal Article
• Language: English
• Published: United States Elsevier Ltd 01.08.2020
• Subjects: Aging; Balance; Basal Ganglia; Functional Neuroimaging; Humans; Meta-Analysis; MRI; PET; Postural Balance; Postural control; Posture; Meta-Analysis; Postural control; MRI; Functional neuroimaging; Balance; PET; Posture
• ISSN: 0149-7634; 1873-7528; 1873-7528
• DOI: 10.1016/j.neubiorev.2020.04.028

•Functional brain images of postural control were investigated in a meta-analysis.•Widespread cortical and subcortical brain regions are involved in postural control.•The cerebellum is activated consistently across postural control studies. Postural instability is a strong risk factor for falls that becomes more prominent with aging. To facilitate treatment and prevention of falls in an aging society, a thorough understanding of the neural networks underlying postural control is warranted. Here, we present a systematic review of the functional neuroimaging literature of studies measuring posture-related neural activity in healthy subjects. Study methods were overall heterogeneous. Eleven out of the 14 studies relied on postural simulation in a supine position (e.g. motor imagery). The key nodes of human postural control involved the brainstem, cerebellum, basal ganglia, thalamus and several cortical regions. An activation likelihood estimation meta-analysis revealed that the anterior cerebellum was consistently activated across the wide range of postural tasks. The cerebellum is known to modulate the brainstem nuclei involved in the control of posture. Hence, this systematic review with meta-analysis provides insight into the neural correlates which underpin human postural control and which may serve as a reference for future neural network and region of interest analyses.