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AbuRahma AF, Avgerinos ED, Chang RW, Darling RC, Duncan AA, Forbes TL, Malas MB, Perler BA, Powell RJ, Rockman CB, Zhou W. The Society for Vascular Surgery implementation document for management of extracranial cerebrovascular disease. J Vasc Surg 2021; 75:26S-98S. [PMID: 34153349 DOI: 10.1016/j.jvs.2021.04.074] [Citation(s) in RCA: 64] [Impact Index Per Article: 21.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2021] [Accepted: 04/28/2021] [Indexed: 12/24/2022]
Affiliation(s)
- Ali F AbuRahma
- Department of Surgery, West Virginia University-Charleston Division, Charleston, WV.
| | - Efthymios D Avgerinos
- Division of Vascular Surgery, University of Pittsburgh School of Medicine, UPMC Hearrt & Vascular Institute, Pittsburgh, Pa
| | - Robert W Chang
- Vascular Surgery, Permanente Medical Group, San Francisco, Calif
| | | | - Audra A Duncan
- Division of Vascular & Endovascular Surgery, University of Western Ontario, London, Ontario, Canada
| | - Thomas L Forbes
- Division of Vascular & Endovascular Surgery, University of Western Ontario, London, Ontario, Canada
| | - Mahmoud B Malas
- Vascular & Endovascular Surgery, University of California San Diego, La Jolla, Calif
| | - Bruce Alan Perler
- Division of Vascular Surgery & Endovascular Therapy, Johns Hopkins, Baltimore, Md
| | | | - Caron B Rockman
- Division of Vascular Surgery, New York University Langone, New York, NY
| | - Wei Zhou
- Division of Vascular Surgery, University of Arizona, Tucson, Ariz
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Zhang X, Su J, Gao C, Ni W, Gao X, Li Y, Zhang J, Lei Y, Gu Y. Progression in Vascular Cognitive Impairment: Pathogenesis, Neuroimaging Evaluation, and Treatment. Cell Transplant 2019; 28:18-25. [PMID: 30488737 PMCID: PMC6322135 DOI: 10.1177/0963689718815820] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/25/2022] Open
Abstract
Vascular cognitive impairment (VCI) defines an entire spectrum of neurologic disorders from mild cognitive impairment to dementia caused by cerebral vascular disease. The pathogenesis of VCI includes ischemic factors (e.g., large vessel occlusion and small vessel dysfunction); hemorrhagic factors (e.g., intracerebral hemorrhage and subarachnoid hemorrhage); and other factors (combined with Alzheimer's disease). Clinical evaluations of VCI mainly refer to neuropsychological testing and imaging assessments, including structural and functional neuroimaging, with different advantages. At present, the main treatment for VCI focuses on neurological protection, cerebral blood flow reconstruction, and neurological rehabilitation, such as pharmacological treatment, revascularization, and cognitive training. In this review, we discuss the pathogenesis, neuroimaging evaluation, and treatment of VCI.
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Affiliation(s)
- Xin Zhang
- Department of Neurosurgery, Huashan Hospital, Fudan University, Shanghai, China
| | - Jiabin Su
- Department of Neurosurgery, Huashan Hospital, Fudan University, Shanghai, China
| | - Chao Gao
- Department of Neurosurgery, Huashan Hospital, Fudan University, Shanghai, China
| | - Wei Ni
- Department of Neurosurgery, Huashan Hospital, Fudan University, Shanghai, China
| | - Xinjie Gao
- Department of Neurosurgery, Huashan Hospital, Fudan University, Shanghai, China
| | - Yuxin Li
- Department of Radiology, Huashan Hospital, Fudan University, Shanghai, China
| | - Jun Zhang
- Department of Radiology, Huashan Hospital, Fudan University, Shanghai, China
| | - Yu Lei
- Department of Neurosurgery, Huashan Hospital, Fudan University, Shanghai, China
- Yu Lei and Yuxiang Gu, Department of Neurosurgery, Huashan Hospital, Fudan University, Shanghai, No. 12 Middle Wulumuqi Road, Shanghai 200040, China. Emails: ;
| | - Yuxiang Gu
- Department of Neurosurgery, Huashan Hospital, Fudan University, Shanghai, China
- Yu Lei and Yuxiang Gu, Department of Neurosurgery, Huashan Hospital, Fudan University, Shanghai, No. 12 Middle Wulumuqi Road, Shanghai 200040, China. Emails: ;
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Hou F, Liu C, Yu Z, Xu X, Zhang J, Peng CK, Wu C, Yang A. Age-Related Alterations in Electroencephalography Connectivity and Network Topology During n-Back Working Memory Task. Front Hum Neurosci 2018; 12:484. [PMID: 30574079 PMCID: PMC6291464 DOI: 10.3389/fnhum.2018.00484] [Citation(s) in RCA: 22] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2018] [Accepted: 11/19/2018] [Indexed: 12/14/2022] Open
Abstract
The study of the healthy brain in elders, especially age-associated alterations in cognition, is important to understand the deficits created by Alzheimer's disease (AD), which imposes a tremendous burden on individuals, families, and society. Although, the changes in synaptic connectivity and reorganization of brain networks that accompany aging are gradually becoming understood, little is known about how normal aging affects brain inter-regional synchronization and functional networks when items are held in working memory (WM). According to the classic Sternberg WM paradigm, we recorded multichannel electroencephalography (EEG) from healthy adults (young and senior) in three different conditions, i.e., the resting state, 0-back (control) task, and 2-back task. The phase lag index (PLI) between EEG channels was computed and then weighted and undirected network was constructed based on the PLI matrix. The effects of aging on network topology were examined using a brain connectivity toolbox. The results showed that age-related alteration was more prominent when the 2-back task was engaged, especially in the theta band. For the younger adults, the WM task evoked a significant increase in the clustering coefficient of the beta-band functional connectivity network, which was absent in the older adults. Furthermore, significant correlations were observed between the behavioral performance of WM and EEG metrics in the theta and gamma bands, suggesting the potential use of those measures as biomarkers for the evaluation of cognitive training, for instance. Taken together, our findings shed further light on the underlying mechanism of WM in physiological aging and suggest that different EEG frequencies appear to have distinct functional correlates in cognitive aging. Analysis of inter-regional synchronization and topological characteristics based on graph theory is thus an appropriate way to explore natural age-related changes in the human brain.
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Affiliation(s)
- Fengzhen Hou
- Key Laboratory of Biomedical Functional Materials, School of Science, China Pharmaceutical University, Nanjing, China
| | - Cong Liu
- Key Laboratory of Biomedical Functional Materials, School of Science, China Pharmaceutical University, Nanjing, China
| | - Zhinan Yu
- Key Laboratory of Biomedical Functional Materials, School of Science, China Pharmaceutical University, Nanjing, China
| | - Xiaodong Xu
- School of Foreign Languages and Cultures, Nanjing Normal University, Nanjing, China
| | - Junying Zhang
- Department of TCMs Pharmaceuticals, School of Traditional Chinese Pharmacy, China Pharmaceutical University, Nanjing, China
| | - Chung-Kang Peng
- Division of Interdisciplinary Medicine and Biotechnology, Department of Medicine, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, United States
| | - Chunyong Wu
- Key Laboratory of Drug Quality Control and Pharmacovigilance, Ministry of Education, China Pharmaceutical University, Nanjing, China.,Department of Pharmaceutical Analysis, China Pharmaceutical University, Nanjing, China
| | - Albert Yang
- Division of Interdisciplinary Medicine and Biotechnology, Department of Medicine, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, United States
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Baniqued PL, Gallen CL, Voss MW, Burzynska AZ, Wong CN, Cooke GE, Duffy K, Fanning J, Ehlers DK, Salerno EA, Aguiñaga S, McAuley E, Kramer AF, D'Esposito M. Brain Network Modularity Predicts Exercise-Related Executive Function Gains in Older Adults. Front Aging Neurosci 2018; 9:426. [PMID: 29354050 PMCID: PMC5758542 DOI: 10.3389/fnagi.2017.00426] [Citation(s) in RCA: 65] [Impact Index Per Article: 10.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2017] [Accepted: 12/11/2017] [Indexed: 01/01/2023] Open
Abstract
Recent work suggests that the brain can be conceptualized as a network comprised of groups of sub-networks or modules. The extent of segregation between modules can be quantified with a modularity metric, where networks with high modularity have dense connections within modules and sparser connections between modules. Previous work has shown that higher modularity predicts greater improvements after cognitive training in patients with traumatic brain injury and in healthy older and young adults. It is not known, however, whether modularity can also predict cognitive gains after a physical exercise intervention. Here, we quantified modularity in older adults (N = 128, mean age = 64.74) who underwent one of the following interventions for 6 months (NCT01472744 on ClinicalTrials.gov): (1) aerobic exercise in the form of brisk walking (Walk), (2) aerobic exercise in the form of brisk walking plus nutritional supplement (Walk+), (3) stretching, strengthening and stability (SSS), or (4) dance instruction. After the intervention, the Walk, Walk+ and SSS groups showed gains in cardiorespiratory fitness (CRF), with larger effects in both walking groups compared to the SSS and Dance groups. The Walk, Walk+ and SSS groups also improved in executive function (EF) as measured by reasoning, working memory, and task-switching tests. In the Walk, Walk+, and SSS groups that improved in EF, higher baseline modularity was positively related to EF gains, even after controlling for age, in-scanner motion and baseline EF. No relationship between modularity and EF gains was observed in the Dance group, which did not show training-related gains in CRF or EF control. These results are consistent with previous studies demonstrating that individuals with a more modular brain network organization are more responsive to cognitive training. These findings suggest that the predictive power of modularity may be generalizable across interventions aimed to enhance aspects of cognition and that, especially in low-performing individuals, global network properties can capture individual differences in neuroplasticity.
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Affiliation(s)
- Pauline L. Baniqued
- Helen Wills Neuroscience Institute, University of California, Berkeley, Berkeley, CA, United States
- Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, IL, United States
| | - Courtney L. Gallen
- Helen Wills Neuroscience Institute, University of California, Berkeley, Berkeley, CA, United States
| | - Michelle W. Voss
- Department of Psychological and Brain Sciences, University of Iowa, Iowa City, IA, United States
| | - Agnieszka Z. Burzynska
- Department of Human Development and Family Studies, Colorado State University, Fort Collins, CO, United States
| | - Chelsea N. Wong
- Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, IL, United States
| | - Gillian E. Cooke
- Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, IL, United States
- Interdisciplinary Health Sciences Institute, University of Illinois at Urbana-Champaign, Urbana, IL, United States
| | - Kristin Duffy
- Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, IL, United States
| | - Jason Fanning
- Department of Kinesiology and Community Health, University of Illinois at Urbana-Champaign, Urbana, IL, United States
- Department of Internal Medicine-Gerontology, Wake Forest School of Medicine, Winston-Salem, NC, United States
| | - Diane K. Ehlers
- Department of Kinesiology and Community Health, University of Illinois at Urbana-Champaign, Urbana, IL, United States
| | - Elizabeth A. Salerno
- Department of Kinesiology and Community Health, University of Illinois at Urbana-Champaign, Urbana, IL, United States
| | - Susan Aguiñaga
- Department of Kinesiology and Community Health, University of Illinois at Urbana-Champaign, Urbana, IL, United States
| | - Edward McAuley
- Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, IL, United States
- Department of Kinesiology and Community Health, University of Illinois at Urbana-Champaign, Urbana, IL, United States
| | - Arthur F. Kramer
- Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, IL, United States
- Psychology Department and Mechanical and Industrial Engineering Department, Northeastern University, Boston, MA, United States
| | - Mark D'Esposito
- Helen Wills Neuroscience Institute, University of California, Berkeley, Berkeley, CA, United States
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Duncan ES, Small SL. Increased Modularity of Resting State Networks Supports Improved Narrative Production in Aphasia Recovery. Brain Connect 2016; 6:524-9. [PMID: 27345466 PMCID: PMC5084363 DOI: 10.1089/brain.2016.0437] [Citation(s) in RCA: 45] [Impact Index Per Article: 5.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022] Open
Abstract
The networks that emerge in the analysis of resting state functional magnetic resonance imaging (rsfMRI) data are believed to reflect the intrinsic organization of the brain. One key property of such complex biological networks is modularity, a measure of community structure. This topological characteristic changes in neurological disease and recovery. Nineteen subjects with language disorders after stroke (aphasia) underwent neuroimaging and behavioral assessment at multiple time points before (baseline) and after an imitation-based therapy. Language was assessed with a narrative production task. Group independent component analysis was performed on the rsfMRI data to identify resting state networks (RSNs). For each participant and each rsfMRI acquisition, we constructed a graph comprising all RSNs. We assigned nodal community based on a region's RSN membership, calculated the modularity score, and then correlated changes in modularity and therapeutic gains on the narrative task. We repeated this comparison controlling for pretherapy performance and using a community structure not based on RSN membership. Increased RSN modularity was positively correlated with improvement on the narrative task immediately post-therapy. This finding remained significant when controlling for pretherapy performance. There were no significant findings for network modularity and behavior when nodal community was assigned without consideration of RSN membership. We interpret these findings as support for the adaptive role of network segregation in behavioral improvement in aphasia therapy. This has important clinical implications for the targeting of noninvasive brain stimulation in poststroke remediation and suggests potential for further insight into the processes underlying such changes through computational modeling.
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Affiliation(s)
- E. Susan Duncan
- Department of Cognitive Sciences & Neurology, University of California, Irvine, Irvine, California
| | - Steven L. Small
- Department of Neurology, Neurobiology & Behavior, Cognitive Sciences, University of California, Irvine, Irvine, California
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