1
|
Sta. Maria MT, Hasegawa Y, Khaing AMM, Salazar S, Ono T. The relationships between mastication and cognitive function: A systematic review and meta-analysis. JAPANESE DENTAL SCIENCE REVIEW 2023; 59:375-388. [PMID: 38022390 PMCID: PMC10630119 DOI: 10.1016/j.jdsr.2023.10.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2022] [Revised: 09/13/2023] [Accepted: 10/02/2023] [Indexed: 12/01/2023] Open
Abstract
Masticatory function such as chewing is expected to modify human cognitive function, and/or the possibility of improving cognitive function is also predicted. This systematic review investigated whether masticatory function affects cognitive function for older/young adults. Full articles written in English from January 2000 to April 2022 were collected using PubMed and Cochrane Library. Target outcomes were cognitive function test scores, cognitive processing speed (reaction time), and masticatory function. For each research question, two independent reviewers conducted the search and screening, data extraction, quality assessment, and risk of bias assessment. The reviewers resolved any disagreements by discussion. From 226 articles retrieved, 20 were included in this review. Older adults with lower scores on the cognitive function test had lower masticatory performance, lower chewing ability, chewing difficulty, and decreased number of teeth. An increased risk of cognitive impairment was found in older adults with masticatory dysfunction. For young adults, gum chewing significantly reduced the processing speed of cognitive tasks compared to no gum chewing. Although most of the evidence included had a low level of evidence and a high risk of bias because of the research designs, the results still suggest that mastication may be a factor in improving cognitive function.
Collapse
Affiliation(s)
- Ma. Therese Sta. Maria
- Division of Comprehensive Prosthodontics, Faculty of Dentistry, Niigata University Graduate School of Medical and Dental Sciences, Niigata, Japan
- Department of Prosthodontics, College of Dentistry, Manila Central University, Caloocan, Philippines
| | - Yoko Hasegawa
- Division of Comprehensive Prosthodontics, Faculty of Dentistry, Niigata University Graduate School of Medical and Dental Sciences, Niigata, Japan
| | - Aye Mya Mya Khaing
- Division of Comprehensive Prosthodontics, Faculty of Dentistry, Niigata University Graduate School of Medical and Dental Sciences, Niigata, Japan
| | - Simonne Salazar
- Department of Prosthodontics, Faculty of Dentistry, Centro Escolar University, Makati, Philippines
| | - Takahiro Ono
- Division of Comprehensive Prosthodontics, Faculty of Dentistry, Niigata University Graduate School of Medical and Dental Sciences, Niigata, Japan
- Department of Geriatric Dentistry, Osaka Dental University, Osaka, Japan
| |
Collapse
|
2
|
Zhang Y, Jiang J, Ling R, Wang L, Jiang J, Wang M. Early Diagnosis and Biomarkers of Alzheimer's Disease Based on Spatio-temporal Graph Convolution Network. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2023; 2023:1-4. [PMID: 38083072 DOI: 10.1109/embc40787.2023.10341155] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/18/2023]
Abstract
Functional magnetic resonance imaging (fMRI) could detect the dynamic activity of brain function and communication. Previous studies have found reduced brain functional connectivity in Alzheimer's disease (AD) patients. In this study, we proposed to process fMRI data by spatio-temporal graph convolution network (ST-GCN) to achieve an early differential diagnosis of AD and to extract image markers using gradient-weighted class activation mapping (Grad-CAM). The data used in this study were from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database, Xuanwu Hospital, and Tongji Hospital. The study included 1105 normal controls and 790 patients with mild cognitive impairment (MCI). The grid search method of K-fold cross-validation was used to train the model. In addition, we used Grad-CAM to extract image markers and carried out visualization analysis. This model obtains better AD diagnosis power: accuracy = 0.92, sensitivity = 0.97, specificity = 0.89, and area under the curve=0.96. Salient brain regions extracted by Grad-CAM include the paracentral lobule, inferior occipital gyrus, middle frontal gyrus, superior temporal gyrus, cuneus, posterior cingulate gyrus, and superior parietal gyrus. Our proposed ST-GAN model will help to explore objective markers that can be used for the early diagnosis of AD.Clinical relevance- Our proposed model shows great potential for enhancing the understanding of the pathology of AD by detecting functional connectivity interruptions.
Collapse
|
3
|
Blair DS, Soriano-Mas C, Cabral J, Moreira P, Morgado P, Deco G. Complexity changes in functional state dynamics suggest focal connectivity reductions. Front Hum Neurosci 2022; 16:958706. [PMID: 36211126 PMCID: PMC9540393 DOI: 10.3389/fnhum.2022.958706] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2022] [Accepted: 08/03/2022] [Indexed: 11/13/2022] Open
Abstract
The past two decades have seen an explosion in the methods and directions of neuroscience research. Along with many others, complexity research has rapidly gained traction as both an independent research field and a valuable subdiscipline in computational neuroscience. In the past decade alone, several studies have suggested that psychiatric disorders affect the spatiotemporal complexity of both global and region-specific brain activity (Liu et al., 2013; Adhikari et al., 2017; Li et al., 2018). However, many of these studies have not accounted for the distributed nature of cognition in either the global or regional complexity estimates, which may lead to erroneous interpretations of both global and region-specific entropy estimates. To alleviate this concern, we propose a novel method for estimating complexity. This method relies upon projecting dynamic functional connectivity into a low-dimensional space which captures the distributed nature of brain activity. Dimension-specific entropy may be estimated within this space, which in turn allows for a rapid estimate of global signal complexity. Testing this method on a recently acquired obsessive-compulsive disorder dataset reveals substantial increases in the complexity of both global and dimension-specific activity versus healthy controls, suggesting that obsessive-compulsive patients may experience increased disorder in cognition. To probe the potential causes of this alteration, we estimate subject-level effective connectivity via a Hopf oscillator-based model dynamic model, the results of which suggest that obsessive-compulsive patients may experience abnormally high connectivity across a broad network in the cortex. These findings are broadly in line with results from previous studies, suggesting that this method is both robust and sensitive to group-level complexity alterations.
Collapse
Affiliation(s)
| | - Carles Soriano-Mas
- Psychiatry and Mental Health Group, Neuroscience Program, Institut d’Investigació Biomèdica de Bellvitge, Barcelona, Spain
- Network Center for Biomedical Research on Mental Health, Carlos III Health Institute, Madrid, Spain
- Department of Social Psychology and Quantitative Psychology, Universitat de Barcelona, Barcelona, Spain
| | - Joana Cabral
- Life and Health Sciences Research Institute, School of Medicine, University of Minho, Braga, Portugal
| | - Pedro Moreira
- Life and Health Sciences Research Institute, School of Medicine, University of Minho, Braga, Portugal
- ICVS/3B’s, PT Government Associate Laboratory, Braga, Portugal
- Psychological Neuroscience Lab, CIPsi, School of Psychology, University of Minho, Braga, Portugal
| | - Pedro Morgado
- Life and Health Sciences Research Institute, School of Medicine, University of Minho, Braga, Portugal
- ICVS/3B’s, PT Government Associate Laboratory, Braga, Portugal
- Clinical Academic Center—Braga, Braga, Portugal
| | - Gustavo Deco
- Facultad de Comunicación, Universitat Pompeu Fabra, Barcelona, Spain
- Institució Catalana de Recerca i Estudis Avançats, Barcelona, Spain
- Department of Neuropsychology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
- School of Psychological Sciences, Monash University, Clayton, VIC, Australia
| |
Collapse
|
4
|
Zhang K, Ma X, Zhang R, Liu Z, Jiang L, Qin Y, Zhang D, Tian P, Gao Z, Zhang N, Shi Z, Xu S. Crosstalk Between Gut Microflora and Vitamin D Receptor SNPs Are Associated with the Risk of Amnestic Mild Cognitive Impairment in a Chinese Elderly Population. J Alzheimers Dis 2022; 88:357-373. [PMID: 35599486 DOI: 10.3233/jad-220101] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
Background: The interactions between environmental factors and genetic variants have been implicated in the pathogenesis of Alzheimer’s disease (AD). The altered gut microbiota (GM) and vitamin D deficiency are closely associated with the higher risk of AD. Objective: This study was performed to evaluate whether the crosstalk between GM and single nucleotide polymorphisms (SNPs) of vitamin D receptor (VDR) or vitamin D binding protein (VDBP) have a link with the risk of amnestic mild cognitive impairment (aMCI) in the Chinese elderly population. Methods: A total of 171 aMCI patients and 261 cognitive normal controls (NC) were enrolled in this study. Six tag SNPs of VDR and VDBP were genotyped by PCR-RFLP. The serum levels of vitamin D, Aβ1-42, and p-tau (181P) were determined by using of ELISA kits. The alterations in the GM were analyzed by full-length 16S ribosomal RNA (rRNA) gene sequencing. Results: The frequencies of AG genotype and A allele of VDR rs1544410 in aMCI group were significantly higher than that in NC group (genotype: p = 0.002, allele: p = 0.003). Patients with aMCI showed an abnormal GM composition compared with NC group. Interestingly, significant differences in GM composition were found between aMCI and NC group among individuals with AG genotype, as well as between individuals with AG and GG genotype of VDR rs1544410 among patients with aMCI. Conclusion: These results implicated that the crosstalk between gut microflora and vitamin D receptor variants are associated with the risk of aMCI in Chinese elderly population.
Collapse
Affiliation(s)
- Kaixia Zhang
- Central Laboratory, The First Hospital of HebeiMedical University, Shijiazhuang, P. R. China
| | - Xiaoying Ma
- Central Laboratory, The First Hospital of HebeiMedical University, Shijiazhuang, P. R. China
| | - Rui Zhang
- Central Laboratory, The First Hospital of HebeiMedical University, Shijiazhuang, P. R. China
- Hebei International Joint Research Center forBrain Science, Shijiazhuang, P. R. China
- HebeiKey Laboratory of Brain Science and Psychiatric-Psychologic Disease, Shijiazhuang, P. R. China
| | - Zanchao Liu
- Department ofEndocrinology, The Second Hospital of Shijiazhuang City, Shijiazhuang, P. R. China
| | - Lei Jiang
- Central Laboratory, The First Hospital of HebeiMedical University, Shijiazhuang, P. R. China
- Hebei International Joint Research Center forBrain Science, Shijiazhuang, P. R. China
- HebeiKey Laboratory of Brain Science and Psychiatric-Psychologic Disease, Shijiazhuang, P. R. China
| | - Yushi Qin
- Central Laboratory, The First Hospital of HebeiMedical University, Shijiazhuang, P. R. China
| | - Di Zhang
- Central Laboratory, The First Hospital of HebeiMedical University, Shijiazhuang, P. R. China
| | - Pei Tian
- Central Laboratory, The First Hospital of HebeiMedical University, Shijiazhuang, P. R. China
| | - ZhaoYu Gao
- Central Laboratory, The First Hospital of HebeiMedical University, Shijiazhuang, P. R. China
- Hebei International Joint Research Center forBrain Science, Shijiazhuang, P. R. China
- HebeiKey Laboratory of Brain Science and Psychiatric-Psychologic Disease, Shijiazhuang, P. R. China
| | - Nan Zhang
- Central Laboratory, The First Hospital of HebeiMedical University, Shijiazhuang, P. R. China
- Hebei International Joint Research Center forBrain Science, Shijiazhuang, P. R. China
- HebeiKey Laboratory of Brain Science and Psychiatric-Psychologic Disease, Shijiazhuang, P. R. China
| | - Zhongli Shi
- Central Laboratory, The First Hospital of HebeiMedical University, Shijiazhuang, P. R. China
- Hebei International Joint Research Center forBrain Science, Shijiazhuang, P. R. China
- HebeiKey Laboratory of Brain Science and Psychiatric-Psychologic Disease, Shijiazhuang, P. R. China
| | - Shunjiang Xu
- Central Laboratory, The First Hospital of HebeiMedical University, Shijiazhuang, P. R. China
- Hebei International Joint Research Center forBrain Science, Shijiazhuang, P. R. China
- HebeiKey Laboratory of Brain Science and Psychiatric-Psychologic Disease, Shijiazhuang, P. R. China
- Research Unit of Digestive Tract Microecosystem Pharmacology and Toxicology, ChineseAcademy of Medical Sciences, Beijing, P. R. China
| |
Collapse
|
5
|
Yan H, Wu H, Chen Y, Yang Y, Xu M, Zeng W, Zhang J, Chang C, Wang N. Dynamical Complexity Fingerprints of Occupation-Dependent Brain Functional Networks in Professional Seafarers. Front Neurosci 2022; 16:830808. [PMID: 35368265 PMCID: PMC8973415 DOI: 10.3389/fnins.2022.830808] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2021] [Accepted: 01/24/2022] [Indexed: 12/24/2022] Open
Abstract
The complexity derived from resting-state functional magnetic resonance imaging (rs-fMRI) data has been applied for exploring cognitive states and occupational neuroplasticity. However, there is little information about the influence of occupational factors on dynamic complexity and topological properties of the connectivity networks. In this paper, we proposed a novel dynamical brain complexity analysis (DBCA) framework to explore the changes in dynamical complexity of brain activity at the voxel level and complexity topology for professional seafarers caused by long-term working experience. The proposed DBCA is made up of dynamical brain entropy mapping analysis and complex network analysis based on brain entropy sequences, which generate the dynamical complexity of local brain areas and the topological complexity across brain areas, respectively. First, the transient complexity of voxel-wise brain map was calculated; compared with non-seafarers, seafarers showed decreased dynamic entropy values in the cerebellum and increased values in the left fusiform gyrus (BA20). Further, the complex network analysis based on brain entropy sequences revealed small-worldness in terms of topological complexity in both seafarers and non-seafarers, indicating that it is an inherent attribute of human the brain. In addition, seafarers showed a higher average path length and lower average clustering coefficient than non-seafarers, suggesting that the information processing ability is reduced in seafarers. Moreover, the reduction in efficiency of seafarers suggests that they have a less efficient processing network. To sum up, the proposed DBCA is effective for exploring the dynamic complexity changes in voxel-wise activity and region-wise connectivity, showing that occupational experience can reshape seafarers’ dynamic brain complexity fingerprints.
Collapse
Affiliation(s)
- Hongjie Yan
- Department of Neurology, Affiliated Lianyungang Hospital of Xuzhou Medical University, Lianyungang, China
| | - Huijun Wu
- School of Biomedical Engineering, Health Science Center, Shenzhen University, Shenzhen, China
| | - Yanyan Chen
- School of Biomedical Engineering, Health Science Center, Shenzhen University, Shenzhen, China
| | - Yang Yang
- Key Laboratory of Behavioral Science, Center for Brain Science and Learning Difficulties, Institute of Psychology, Chinese Academy of Sciences, Beijing, China
| | - Min Xu
- Center for Brain Disorders and Cognitive Science, Shenzhen University, Shenzhen, China
| | - Weiming Zeng
- Lab of Digital Image and Intelligent Computation, Shanghai Maritime University, Shanghai, China
| | - Jian Zhang
- School of Pharmacy, Health Science Center, Shenzhen University, Shenzhen, China
| | - Chunqi Chang
- School of Biomedical Engineering, Health Science Center, Shenzhen University, Shenzhen, China
- Peng Cheng Laboratory, Shenzhen, China
- *Correspondence: Nizhuan Wang,
| | - Nizhuan Wang
- School of Biomedical Engineering, ShanghaiTech University, Shanghai, China
- *Correspondence: Nizhuan Wang,
| |
Collapse
|
6
|
Chao YP, Liu PTB, Wang PN, Cheng CH. Reduced Inter-Voxel Whiter Matter Integrity in Subjective Cognitive Decline: Diffusion Tensor Imaging With Tract-Based Spatial Statistics Analysis. Front Aging Neurosci 2022; 14:810998. [PMID: 35309886 PMCID: PMC8924936 DOI: 10.3389/fnagi.2022.810998] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2021] [Accepted: 01/24/2022] [Indexed: 11/24/2022] Open
Abstract
Subjective cognitive decline (SCD), a self-reported worsening in cognition concurrent with normal performance on standardized neuropsychological tests, has gained much attention due to its high risks in the development of mild cognitive impairments or Alzheimer’s disease. The existing cross-sectional diffusion tensor imaging (DTI) studies in SCD have shown extremely controversial findings. Furthermore, all of these studies investigated diffusion properties within the voxel, such as fractional anisotropy, mean diffusivity, or axial diffusivity (DA). However, it remains unclear whether individuals with SCD demonstrate alterations of diffusion profile between voxels and their neighbors, as indexed by local diffusion homogeneity (LDH). We selected 30 healthy controls (HCs) and 23 SCD subjects to acquire their whole-brain DTI. Diffusion images were compared using the tract-based spatial statistics method. Diffusion indices with significant between-group tract clusters were extracted from each individual for further region-of-interest (ROI)-based comparisons. Our results showed that subjects with SCD demonstrated reduced LDH in the left superior frontal gyrus (SFG) and DA in the right anterior cingulate cortex compared with the HC group. In contrast, the SCD group showed higher LDH values in the left lingual gyrus (LG) compared with the HC group. Notably, LDH in the left SFG was significantly and negatively correlated with LDH in the left LG. In conclusion, white matter (WM) integrity in the left SFG, right ACC, and left LG is altered in SCD, suggesting that individuals with SCD exhibit detectable changes in WM tracts before they demonstrate objective cognitive deficits.
Collapse
Affiliation(s)
- Yi-Ping Chao
- Department of Computer Science and Information Engineering, Chang Gung University, Taoyuan City, Taiwan
- Department of Neurology, Chang Gung Memorial Hospital, Taoyuan City, Taiwan
| | - Po-Ting Bertram Liu
- Department of Occupational Therapy and Graduate Institute of Behavioral Sciences, Chang Gung University, Taoyuan City, Taiwan
- Laboratory of Brain Imaging and Neural Dynamics (BIND Lab), Chang Gung University, Taoyuan City, Taiwan
| | - Pei-Ning Wang
- Division of General Neurology, Department of Neurological Institute, Taipei Veterans General Hospital, Taipei City, Taiwan
- Department of Neurology, National Yang Ming Chiao Tung University, Taipei City, Taiwan
| | - Chia-Hsiung Cheng
- Department of Occupational Therapy and Graduate Institute of Behavioral Sciences, Chang Gung University, Taoyuan City, Taiwan
- Laboratory of Brain Imaging and Neural Dynamics (BIND Lab), Chang Gung University, Taoyuan City, Taiwan
- Healthy Aging Research Center, Chang Gung University, Taoyuan City, Taiwan
- Department of Psychiatry, Chang Gung Memorial Hospital, Taoyuan City, Taiwan
- *Correspondence: Chia-Hsiung Cheng, ;
| |
Collapse
|
7
|
Xin X, Long S, Sun M, Gao X. The Application of Complexity Analysis in Brain Blood-Oxygen Signal. Brain Sci 2021; 11:brainsci11111415. [PMID: 34827414 PMCID: PMC8615802 DOI: 10.3390/brainsci11111415] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2021] [Revised: 10/22/2021] [Accepted: 10/25/2021] [Indexed: 11/17/2022] Open
Abstract
One of the daunting features of the brain is its physiology complexity, which arises from the interaction of numerous neuronal circuits that operate over a wide range of temporal and spatial scales, enabling the brain to adapt to the constantly changing environment and to perform various cognitive functions. As a reflection of the complexity of brain physiology, the complexity of brain blood-oxygen signal has been frequently studied in recent years. This paper reviews previous literature regarding the following three aspects: (1) whether the complexity of the brain blood-oxygen signal can serve as a reliable biomarker for distinguishing different patient populations; (2) which is the best algorithm for complexity measure? And (3) how to select the optimal parameters for complexity measures. We then discuss future directions for blood-oxygen signal complexity analysis, including improving complexity measurement based on the characteristics of both spatial patterns of brain blood-oxygen signal and latency of complexity itself. In conclusion, the current review helps to better understand complexity analysis in brain blood-oxygen signal analysis and provide useful information for future studies.
Collapse
|
8
|
Khan NC, Pandey V, Gajos KZ, Gupta AS. Free-Living Motor Activity Monitoring in Ataxia-Telangiectasia. THE CEREBELLUM 2021; 21:368-379. [PMID: 34302287 PMCID: PMC8302464 DOI: 10.1007/s12311-021-01306-y] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Accepted: 07/08/2021] [Indexed: 11/12/2022]
Abstract
With disease-modifying approaches under evaluation in ataxia-telangiectasia and other ataxias, there is a need for objective and reliable biomarkers of free-living motor function. In this study, we test the hypothesis that metrics derived from a single wrist sensor worn at home provide accurate, reliable, and interpretable information about neurological disease severity in children with A-T. A total of 15 children with A-T and 15 age- and sex-matched controls wore a sensor with a triaxial accelerometer on their dominant wrist for 1 week at home. Activity intensity measures, derived from the sensor data, were compared with in-person neurological evaluation on the Brief Ataxia Rating Scale (BARS) and performance on a validated computer mouse task. Children with A-T were inactive the same proportion of each day as controls but produced more low intensity movements (p < 0.01; Cohen’s d = 1.48) and fewer high intensity movements (p < 0.001; Cohen’s d = 1.71). The range of activity intensities was markedly reduced in A-T compared to controls (p < 0.0001; Cohen’s d = 2.72). The activity metrics correlated strongly with arm, gait, and total clinical severity (r: 0.71–0.87; p < 0.0001), correlated with specific computer task motor features (r: 0.67–0.92; p < 0.01), demonstrated high reliability (r: 0.86–0.93; p < 0.00001), and were not significantly influenced by age in the healthy control group. Motor activity metrics from a single, inexpensive wrist sensor during free-living behavior provide accurate and reliable information about diagnosis, neurological disease severity, and motor performance. These low-burden measurements are applicable independent of ambulatory status and are potential digital behavioral biomarkers in A-T.
Collapse
Affiliation(s)
- Nergis C Khan
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.,School of Medicine, Stanford University, Stanford, CA, USA
| | - Vineet Pandey
- Harvard John A. Paulson School of Engineering and Applied Sciences, Cambridge, MA, USA
| | - Krzysztof Z Gajos
- Harvard John A. Paulson School of Engineering and Applied Sciences, Cambridge, MA, USA
| | - Anoopum S Gupta
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.
| |
Collapse
|
9
|
Ren P, Ma M, Xie G, Wu Z, Wu D. Altered complexity of resting-state BOLD activity in Alzheimer's disease-related neurodegeneration: a multiscale entropy analysis. Aging (Albany NY) 2020; 12:13571-13582. [PMID: 32649309 PMCID: PMC7377896 DOI: 10.18632/aging.103463] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2020] [Accepted: 05/27/2020] [Indexed: 11/25/2022]
Abstract
Brain complexity, which reflects the ability of the brain to adapt to a changing environment, has been found to be significantly changed with age. However, there is less evidence on the alterations of brain complexity in neurodegenerative disorders such as Alzheimer's disease (AD). Here we investigated the altered complexity of resting-state blood oxygen level-dependent signals in AD-related neurodegeneration using multiscale entropy (MSE) analysis. All participants were recruited from the Alzheimer's Disease Neuroimaging Initiative, including healthy controls (HC, n=62), amnestic mild cognitive impairment (aMCI, n =81) patients, and Alzheimer's disease (AD, n=25) patients. Our results showed time scale-dependent MSE differences across the three groups. In scale=1, significantly changed MSE patterns (HC>aMCI>AD) were found in four brain regions, including the hippocampus, middle frontal gyrus, intraparietal lobe, and superior frontal gyrus. In scale=4, reversed MSE patterns (HC<aMCI<AD) were found in the middle frontal gyrus and middle occipital gyrus. Furthermore, the values of regional entropy were significantly associated with cognitive functions positively on the short time scale, while negatively on the longer time scale. Our findings suggest that MSE could be a reliable measure for characterizing brain deterioration in AD, and may provide insights into the neural mechanism of AD-related neurodegeneration.
Collapse
Affiliation(s)
- Ping Ren
- Shenzhen Mental Health Center, Shenzhen, Guangdong, China.,Shenzhen Kangning Hospital, Shenzhen, Guangdong, China
| | - Manxiu Ma
- Center for Neurobiology Research, Fralin Biomedical Research Institute at VTC, Virginia Tech, Roanoke, VA 24016, USA
| | - Guohua Xie
- Shenzhen Mental Health Center, Shenzhen, Guangdong, China.,Shenzhen Kangning Hospital, Shenzhen, Guangdong, China
| | - Zhiwei Wu
- Shenzhen Mental Health Center, Shenzhen, Guangdong, China.,Shenzhen Kangning Hospital, Shenzhen, Guangdong, China
| | - Donghui Wu
- Shenzhen Mental Health Center, Shenzhen, Guangdong, China.,Shenzhen Kangning Hospital, Shenzhen, Guangdong, China
| | | |
Collapse
|