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Hum Brain Mapp. 2019 Nov 1;40(16):4686-4702. doi: 10.1002/hbm.24730. Epub 2019 Jul 22.

Graph theory analysis of resting-state functional magnetic resonance imaging in essential tremor.

Author information

1
Department of Neurology, University Hospital 12 de Octubre, Madrid, Spain.
2
Center of Biomedical Network Research on Neurodegenerative Diseases (CIBERNED), Madrid, Spain.
3
Department of Medicine, Faculty of Medicine, Complutense University, Madrid, Spain.
4
Medical Image Analysis Laboratory (LAIMBIO), Rey Juan Carlos University, Madrid, Spain.
5
Department of Neurology, Yale School of Medicine, Yale University, New Haven, Connecticut.
6
Department of Chronic Disease Epidemiology, Yale School of Public Health, Yale University, New Haven, Connecticut.
7
Center for Neuroepidemiology and Clinical Neurological Research, Yale School of Medicine, Yale University, New Haven, Connecticut.
8
Faculty of Biosanitary Sciences, Francisco de Vitoria University, Madrid, Spain.
9
Brain Damage Unit, Hospital Beata Maria Ana, Madrid, Spain.
10
Neural and Cognitive Engineering group, Center for Automation and Robotics (CAR) CSIC-UPM, Arganda del Rey, Spain.

Abstract

Essential tremor (ET) is a neurological disease with both motor and nonmotor manifestations; however, little is known about its underlying brain basis. Furthermore, the overall organization of the brain network in ET remains largely unexplored. We investigated the topological properties of brain functional network, derived from resting-state functional magnetic resonance imaging (MRI) data, in 23 ET patients versus 23 healthy controls. Graph theory analysis was used to assess the functional network organization. At the global level, the functional network of ET patients was characterized by lower small-worldness values than healthy controls-less clustered functionality of the brain. At the regional level, compared with the healthy controls, ET patients showed significantly higher values of global efficiency, cost and degree, and a shorter average path length in the left inferior frontal gyrus (pars opercularis), right inferior temporal gyrus (posterior division and temporo-occipital part), right inferior lateral occipital cortex, left paracingulate, bilateral precuneus bilaterally, left lingual gyrus, right hippocampus, left amygdala, nucleus accumbens bilaterally, and left middle temporal gyrus (posterior part). In addition, ET patients showed significant higher local efficiency and clustering coefficient values in frontal medial cortex bilaterally, subcallosal cortex, posterior cingulate cortex, parahippocampal gyri bilaterally (posterior division), right lingual gyrus, right cerebellar flocculus, right postcentral gyrus, right inferior semilunar lobule of cerebellum and culmen of vermis. Finally, the right intracalcarine cortex and the left orbitofrontal cortex showed a shorter average path length in ET patients, while the left frontal operculum and the right planum polare showed a higher betweenness centrality in ET patients. In conclusion, the efficiency of the overall brain functional network in ET is disrupted. Further, our results support the concept that ET is a disorder that disrupts widespread brain regions, including those outside of the brain regions responsible for tremor.

KEYWORDS:

MRI; biomarker; essential tremor; functional connectivity; graph theory; resting state

PMID:
31332912
DOI:
10.1002/hbm.24730

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