Abstract
We aimed to investigate the activity within and the connectivity between resting state networks (RSNs) in healthy subjects and patients with Alzheimer’s disease (AD) or mild cognitive impairment (MCI). Magnetic resonance imaging (MRI) and resting-state MRI were performed on patients diagnosed with AD (n=18) or MCI (n=16) and on healthy subjects (n=18) with matching demographic characteristics (age, sex, and education level). Independent component analysis and Granger causality analysis (GCA) were used during image postprocessing. We calculated ‘In + Out degree’ for each RSN. Then, we investigated the relationships between “In + Out degree” of each brain network and the cognitive behavioural data. RSNs were obtained using the optimal matching method. The core areas of the five RSNs were similar between the AD, MCI, and healthy control groups, but the activity within these five RSNs was significantly lower in the AD and MCI groups than in the healthy control group (P<0.01, false discovery rate corrected). The GCA results showed that the connectivity between the five RSNs, particularly the connectivity from the default mode network (DMN) to the other RSNs, was slightly lower in MCI patients and was significantly lower in AD patients than in healthy subjects. In contrast, increased connectivity was evident between the memory network and the executive control network in the AD and MCI patients. The “In + Out degree” of the DMN negatively correlated with the Montreal Cognitive Assessment score in AD patients (R=-0.43, P<0.05). In conclusion, the activity within RSNs and the connectivity between RSNs differed between AD patients, MCI patients, and normal individuals; these results provide an imaging reference for the diagnosis of AD and the measurement of disease progression and reveal insight into the pathogenesis of AD.
Keywords: Alzheimer’s disease (AD), mild cognitive impairment (MCI), dementia, resting-state networks (RSNs), resting state functional magnetic resonance imaging (rs-fMRI), independent component analysis (ICA), granger causality analysis (GCA).
Current Alzheimer Research
Title:Functional Activity and Connectivity Differences of Five Resting-State Networks in Patients with Alzheimer’s Disease or Mild Cognitive Impairment
Volume: 13 Issue: 3
Author(s): Yu Chen, Hao Yan, Zaizhu Han, Yanchao Bi, Hongyan Chen, Jia Liu, Meiru Wu, Yongjun Wang and Yumei Zhang
Affiliation:
Keywords: Alzheimer’s disease (AD), mild cognitive impairment (MCI), dementia, resting-state networks (RSNs), resting state functional magnetic resonance imaging (rs-fMRI), independent component analysis (ICA), granger causality analysis (GCA).
Abstract: We aimed to investigate the activity within and the connectivity between resting state networks (RSNs) in healthy subjects and patients with Alzheimer’s disease (AD) or mild cognitive impairment (MCI). Magnetic resonance imaging (MRI) and resting-state MRI were performed on patients diagnosed with AD (n=18) or MCI (n=16) and on healthy subjects (n=18) with matching demographic characteristics (age, sex, and education level). Independent component analysis and Granger causality analysis (GCA) were used during image postprocessing. We calculated ‘In + Out degree’ for each RSN. Then, we investigated the relationships between “In + Out degree” of each brain network and the cognitive behavioural data. RSNs were obtained using the optimal matching method. The core areas of the five RSNs were similar between the AD, MCI, and healthy control groups, but the activity within these five RSNs was significantly lower in the AD and MCI groups than in the healthy control group (P<0.01, false discovery rate corrected). The GCA results showed that the connectivity between the five RSNs, particularly the connectivity from the default mode network (DMN) to the other RSNs, was slightly lower in MCI patients and was significantly lower in AD patients than in healthy subjects. In contrast, increased connectivity was evident between the memory network and the executive control network in the AD and MCI patients. The “In + Out degree” of the DMN negatively correlated with the Montreal Cognitive Assessment score in AD patients (R=-0.43, P<0.05). In conclusion, the activity within RSNs and the connectivity between RSNs differed between AD patients, MCI patients, and normal individuals; these results provide an imaging reference for the diagnosis of AD and the measurement of disease progression and reveal insight into the pathogenesis of AD.
Export Options
About this article
Cite this article as:
Chen Yu, Yan Hao, Han Zaizhu, Bi Yanchao, Chen Hongyan, Liu Jia, Wu Meiru, Wang Yongjun and Zhang Yumei, Functional Activity and Connectivity Differences of Five Resting-State Networks in Patients with Alzheimer’s Disease or Mild Cognitive Impairment, Current Alzheimer Research 2016; 13 (3) . https://dx.doi.org/10.2174/156720501303160217113858
DOI https://dx.doi.org/10.2174/156720501303160217113858 |
Print ISSN 1567-2050 |
Publisher Name Bentham Science Publisher |
Online ISSN 1875-5828 |
Call for Papers in Thematic Issues
New Advances in the Prevention, Diagnosis, Treatment, and Rehabilitation of Alzheimer's Disease
Aims and Scope: Introduction: Alzheimer's disease (AD) poses a significant global health challenge, with an increasing prevalence that demands concerted efforts to advance our understanding and strategies for prevention, diagnosis, treatment, and rehabilitation. This thematic issue aims to bring together cutting-edge research and innovative approaches from multidisciplinary perspectives to address ...read more
Current updates on the Role of Neuroinflammation in Neurodegenerative Disorders
Neuroinflammation is an invariable hallmark of chronic and acute neurodegenerative disorders and has long been considered a potential drug target for Alzheimer?s disease (AD) and dementia. Significant evidence of inflammatory processes as a feature of AD is provided by the presence of inflammatory markers in plasma, CSF and postmortem brain ...read more
Deep Learning for Advancing Alzheimer's Disease Research
Alzheimer's disease (AD) poses a significant global health challenge, with an increasing number of individuals affected yearly. Deep learning, a subfield of artificial intelligence, has shown immense potential in various domains, including healthcare. This thematic issue of Current Alzheimer Research explores the application of deep learning techniques in advancing our ...read more
Diagnostic and therapeutic biomarkers of dementia
Dementia affects 18 million people worldwide. Dementia is a syndrome of symptoms caused by brain disease, usually chronic or progressive, clinically characterized by multiple impairments of higher cortical functions such as memory, thinking, orientation, and learning. In addition, in the course of dementia, cognitive deficits are observed, which often hinder ...read more
- Author Guidelines
- Graphical Abstracts
- Fabricating and Stating False Information
- Research Misconduct
- Post Publication Discussions and Corrections
- Publishing Ethics and Rectitude
- Increase Visibility of Your Article
- Archiving Policies
- Peer Review Workflow
- Order Your Article Before Print
- Promote Your Article
- Manuscript Transfer Facility
- Editorial Policies
- Allegations from Whistleblowers
- Announcements
Related Articles
-
The Role of miR-129-5p in Cancer: A Novel Therapeutic Target
Current Molecular Pharmacology Cdc25A Protein Phosphatase: A Therapeutic Target for Liver Cancer Therapies
Anti-Cancer Agents in Medicinal Chemistry Cyclin-Dependent Kinase 4/6 (Cdk4/6) Inhibitors: Perspectives in Cancer Therapy and Imaging
Mini-Reviews in Medicinal Chemistry Colorectal Cancer Classification and Survival Analysis Based on an Integrated RNA and DNA Molecular Signature
Current Bioinformatics Smart Synthetic Polymer Nanocarriers for Controlled and Site-Specific Drug Delivery
Current Topics in Medicinal Chemistry Personalizing Stem Cell Research and Therapy: The Arduous Road Ahead or Missed Opportunity?
Current Pharmacogenomics and Personalized Medicine Cognitive, Psychological and Psychiatric Effects of Ionizing Radiation Exposure
Current Medicinal Chemistry Phenylbutyric Acid: Simple Structure - Multiple Effects
Current Pharmaceutical Design Ethanol Metabolism and Effects: Nitric Oxide and its Interaction
Current Clinical Pharmacology Stem Cells: Their Role in Breast Cancer Development and Resistance to Treatment
Current Pharmaceutical Biotechnology The Inhibitor of Growth (ING) Gene Family: Potential Role in Cancer Therapy
Current Cancer Drug Targets Oligonucleotides and G-quadruplex Stabilizers: Targeting Telomeres and Telomerase in Cancer Therapy
Current Pharmaceutical Design Activatable Molecular Probes for Cancer Imaging
Current Topics in Medicinal Chemistry Inhibitors of Cyclin Dependent Kinases: Useful Targets for Cancer Treatment
Current Cancer Drug Targets Computational Evaluation and In Vitro Validation of New Epidermal Growth Factor Receptor Inhibitors
Current Topics in Medicinal Chemistry Peptidyl Prolyl Isomerase, Pin1 is a Potential Target for Enhancing the Therapeutic Efficacy of Etoposide
Current Cancer Drug Targets Solving the Blood-Brain Barrier Challenge for the Effective Treatment of HIV Replication in the Central Nervous System
Current Pharmaceutical Design Impact of Drug Metabolism/Pharmacokinetics and their Relevance Upon Taxus-based Drug Development
Current Drug Metabolism Editorial (Thematic Issue: Emerging Concepts and Therapeutics Strategies for the Treatment of Brain Tumors)
Anti-Cancer Agents in Medicinal Chemistry The MCM Complex: Its Role in DNA Replication and Implications for Cancer Therapy
Current Cancer Drug Targets