title: Altered functional and structural connectivity networks in psychogenic non-epileptic seizures.
abstract: Psychogenic non-epileptic seizures (PNES) are paroxysmal behaviors that resemble epileptic seizures but lack abnormal electrical activity. Recent studies suggest aberrant functional connectivity involving specific brain regions in PNES. Little is known, however, about alterations of topological organization of whole-brain functional and structural connectivity networks in PNES. We constructed functional connectivity networks from resting-state functional MRI signal correlations and structural connectivity networks from diffusion tensor imaging tractography in 17 PNES patients and 20 healthy controls. Graph theoretical analysis was employed to compute network properties. Moreover, we investigated the relationship between functional and structural connectivity networks. We found that PNES patients exhibited altered small-worldness in both functional and structural networks and shifted towards a more regular (lattice-like) organization, which could serve as a potential imaging biomarker for PNES. In addition, many regional characteristics were altered in structural connectivity network, involving attention, sensorimotor, subcortical and default-mode networks. These regions with altered nodal characteristics likely reflect disease-specific pathophysiology in PNES. Importantly, the coupling strength of functional-structural connectivity was decreased and exhibited high sensitivity and specificity to differentiate PNES patients from healthy controls, suggesting that the decoupling strength of functional-structural connectivity might be an important characteristic reflecting the mechanisms of PNES. This is the first study to explore the altered topological organization in PNES combining functional and structural connectivity networks, providing a new way to understand the pathophysiological mechanisms of PNES.
authors.affiliation: Key Laboratory for Neuroinformation of Ministry of Education, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, PR China.
authors.forename: Ju-Rong
authors.initials: JR
authors.lastname: Ding
authors.forename: Dongmei
authors.initials: D
authors.lastname: An
authors.forename: Wei
authors.initials: W
authors.lastname: Liao
authors.forename: Jinmei
authors.initials: J
authors.lastname: Li
authors.forename: Guo-Rong
authors.initials: GR
authors.lastname: Wu
authors.forename: Qiang
authors.initials: Q
authors.lastname: Xu
authors.forename: Zhiliang
authors.initials: Z
authors.lastname: Long
authors.forename: Qiyong
authors.initials: Q
authors.lastname: Gong
authors.forename: Dong
authors.initials: D
authors.lastname: Zhou
authors.forename: Olaf
authors.initials: O
authors.lastname: Sporns
authors.forename: Huafu
authors.initials: H
authors.lastname: Chen
mesh_terms: D000328:Adult; D015415:Biomarkers / Q000378:metabolism; D001921:Brain / Q000378:metabolism / Q000503:physiopathology*; D001931:Brain Mapping / Q000379:methods; D004827:Epilepsy / Q000378:metabolism / Q000503:physiopathology*; D005260:Female; D006801:Humans; D008279:Magnetic Resonance Imaging / Q000379:methods; D008297:Male; D009415:Nerve Net / Q000378:metabolism / Q000503:physiopathology*; D009434:Neural Pathways / Q000378:metabolism / Q000503:physiopathology*; D055815:Young Adult
chemical_list: D015415:Biomarkers