X Ding1, C-Y Li1, Q-S Wang2, F-Z Du3, Z-W Ke3, F Peng1, J Wang1, L Chen1. 1. Department of Neurology, Chengdu Military General Hospital, No. 270 Rongdu Avenue, Jinniu District, Chengdu, Sichuan 610083, China. 2. Department of Neurology, Chengdu Military General Hospital, No. 270 Rongdu Avenue, Jinniu District, Chengdu, Sichuan 610083, China. Electronic address: happy174236@sina.com. 3. Department of Radiology, Chengdu Military General Hospital, No. 270 Rongdu Avenue, Jinniu District, Chengdu, Sichuan 610083, China.
Abstract
OBJECT: To investigate whether resting-state functional connectivity (FC) differed in the default mode network (DMN) in stroke patients with and without post-stroke cognitive impairment (PSCI vs. Non-PSCI) and to explore the relationship between DMN connectivity and the cognitive performance in stroke patients. METHODS: We totally enrolled twenty healthy controls and 18 stroke patients. The stroke patients were divided into two subgroups on the basis of the cognitive assays. Montreal Cognitive Assessment (MoCA) and Mini-Mental State Examination (MMSE) scores were recorded 10 days and 3 months after the stroke. Independent component analysis was used to isolate the DMN. One-way analysis of variance was performed to detect different FC among groups. Pearson correlation analyses were conducted to determine the relationships between FC strength and the MoCA and MMSE scores. RESULTS: Compared to healthy controls, both Non-PSCI patients and PSCI patients showed significantly decreased FC in the posterior cingulate cortex/precuneus (PCC/PCu), as well as increased FC in the medial prefrontal cortex (MPFC) and left hippocampus. However, Non-PSCI patients showed more significantly increased FC in the MPFC and hippocampus than PSCI patients did. The FC in the PCC/PCu was related to the MoCA score measured at a 10-day follow-up, and the FC in the left hippocampus predicted the MoCA score measured at 3 months follow-up. CONCLUSIONS: Our findings may be helpful for facilitating further understanding of the potential mechanism underlying PSCI, and suggests that resting-state DMN connectivity could serve as neuroimaging biomarkers for future interventional studies.
OBJECT: To investigate whether resting-state functional connectivity (FC) differed in the default mode network (DMN) in strokepatients with and without post-stroke cognitive impairment (PSCI vs. Non-PSCI) and to explore the relationship between DMN connectivity and the cognitive performance in strokepatients. METHODS: We totally enrolled twenty healthy controls and 18 strokepatients. The strokepatients were divided into two subgroups on the basis of the cognitive assays. Montreal Cognitive Assessment (MoCA) and Mini-Mental State Examination (MMSE) scores were recorded 10 days and 3 months after the stroke. Independent component analysis was used to isolate the DMN. One-way analysis of variance was performed to detect different FC among groups. Pearson correlation analyses were conducted to determine the relationships between FC strength and the MoCA and MMSE scores. RESULTS: Compared to healthy controls, both Non-PSCIpatients and PSCI patients showed significantly decreased FC in the posterior cingulate cortex/precuneus (PCC/PCu), as well as increased FC in the medial prefrontal cortex (MPFC) and left hippocampus. However, Non-PSCIpatients showed more significantly increased FC in the MPFC and hippocampus than PSCI patients did. The FC in the PCC/PCu was related to the MoCA score measured at a 10-day follow-up, and the FC in the left hippocampus predicted the MoCA score measured at 3 months follow-up. CONCLUSIONS: Our findings may be helpful for facilitating further understanding of the potential mechanism underlying PSCI, and suggests that resting-state DMN connectivity could serve as neuroimaging biomarkers for future interventional studies.
Authors: Lara A Boyd; Kathryn S Hayward; Nick S Ward; Cathy M Stinear; Charlotte Rosso; Rebecca J Fisher; Alexandre R Carter; Alex P Leff; David A Copland; Leeanne M Carey; Leonardo G Cohen; D Michele Basso; Jane M Maguire; Steven C Cramer Journal: Int J Stroke Date: 2017-07 Impact factor: 5.266
Authors: Joshua S Siegel; Abraham Z Snyder; Lenny Ramsey; Gordon L Shulman; Maurizio Corbetta Journal: J Cereb Blood Flow Metab Date: 2015-11-04 Impact factor: 6.200