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Lu Y, Liu T, Sheng Q, Zhang Y, Shi H, Jiao Z. Predicting the cognitive function status in end-stage renal disease patients at a functional subnetwork scale. MATHEMATICAL BIOSCIENCES AND ENGINEERING : MBE 2024; 21:3838-3859. [PMID: 38549310 DOI: 10.3934/mbe.2024171] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/02/2024]
Abstract
Brain functional networks derived from functional magnetic resonance imaging (fMRI) provide a promising approach to understanding cognitive processes and predicting cognitive abilities. The topological attribute parameters of global networks are taken as the features from the overall perspective. It is constrained to comprehend the subtleties and variances of brain functional networks, which fell short of thoroughly examining the complex relationships and information transfer mechanisms among various regions. To address this issue, we proposed a framework to predict the cognitive function status in the patients with end-stage renal disease (ESRD) at a functional subnetwork scale (CFSFSS). The nodes from different network indicators were combined to form the functional subnetworks. The area under the curve (AUC) of the topological attribute parameters of functional subnetworks were extracted as features, which were selected by the minimal Redundancy Maximum Relevance (mRMR). The parameter combination with improved fitness was searched by the enhanced whale optimization algorithm (E-WOA), so as to optimize the parameters of support vector regression (SVR) and solve the global optimization problem of the predictive model. Experimental results indicated that CFSFSS achieved superior predictive performance compared to other methods, by which the mean absolute error (MAE), mean absolute percentage error (MAPE), and root mean square error (RMSE) were up to 0.5951, 0.0281 and 0.9994, respectively. The functional subnetwork effectively identified the active brain regions associated with the cognitive function status, which offered more precise features. It not only helps to more accurately predict the cognitive function status, but also provides more references for clinical decision-making and intervention of cognitive impairment in ESRD patients.
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Affiliation(s)
- Yu Lu
- School of Microelectronics and Control Engineering, Changzhou University, Changzhou 213164, China
| | - Tongqiang Liu
- Department of Nephrology, The Affiliated Changzhou No.2 People's Hospital of Nanjing Medical University, Changzhou 213003, China
| | - Quan Sheng
- School of Microelectronics and Control Engineering, Changzhou University, Changzhou 213164, China
| | - Yutao Zhang
- School of Microelectronics and Control Engineering, Changzhou University, Changzhou 213164, China
| | - Haifeng Shi
- Department of Radiology, The Affiliated Changzhou No.2 People's Hospital of Nanjing Medical University, Changzhou 213003, China
| | - Zhuqing Jiao
- School of Microelectronics and Control Engineering, Changzhou University, Changzhou 213164, China
- School of Computer Science and Artificial Intelligence, Changzhou University, Changzhou 213164, China
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Drenth N, van Dijk SE, Foster-Dingley JC, Bertens AS, Rius Ottenheim N, van der Mast RC, Rombouts SARB, van Rooden S, van der Grond J. Distinct functional subnetworks of cognitive domains in older adults with minor cognitive deficits. Brain Commun 2024; 6:fcae048. [PMID: 38419735 PMCID: PMC10901264 DOI: 10.1093/braincomms/fcae048] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2023] [Revised: 12/18/2023] [Accepted: 02/14/2024] [Indexed: 03/02/2024] Open
Abstract
Although past research has established a relationship between functional connectivity and cognitive function, less is known about which cognitive domains are associated with which specific functional networks. This study investigated associations between functional connectivity and global cognitive function and performance in the domains of memory, executive function and psychomotor speed in 166 older adults aged 75-91 years (mean = 80.3 ± 3.8) with minor cognitive deficits (Mini-Mental State Examination scores between 21 and 27). Functional connectivity was assessed within 10 standard large-scale resting-state networks and on a finer spatial resolution between 300 nodes in a functional connectivity matrix. No domain-specific associations with mean functional connectivity within large-scale resting-state networks were found. Node-level analysis revealed that associations between functional connectivity and cognitive performance differed across cognitive functions in strength, location and direction. Specific subnetworks of functional connections were found for each cognitive domain in which higher connectivity between some nodes but lower connectivity between other nodes were related to better cognitive performance. Our findings add to a growing body of literature showing differential sensitivity of functional connections to specific cognitive functions and may be a valuable resource for hypothesis generation of future studies aiming to investigate specific cognitive dysfunction with resting-state functional connectivity in people with beginning cognitive deficits.
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Affiliation(s)
- Nadieh Drenth
- Department of Radiology, Leiden University Medical Center, P.O. Box 9600, 2300 RC Leiden, The Netherlands
| | - Suzanne E van Dijk
- Department of Radiology, Leiden University Medical Center, P.O. Box 9600, 2300 RC Leiden, The Netherlands
| | - Jessica C Foster-Dingley
- Department of Radiology, Leiden University Medical Center, P.O. Box 9600, 2300 RC Leiden, The Netherlands
- Department of Psychiatry, Leiden University Medical Center, P.O. Box 9600, 2300 RC Leiden, The Netherlands
| | - Anne Suzanne Bertens
- Department of Radiology, Leiden University Medical Center, P.O. Box 9600, 2300 RC Leiden, The Netherlands
- Department of Psychiatry, Leiden University Medical Center, P.O. Box 9600, 2300 RC Leiden, The Netherlands
| | - Nathaly Rius Ottenheim
- Department of Psychiatry, Leiden University Medical Center, P.O. Box 9600, 2300 RC Leiden, The Netherlands
| | - Roos C van der Mast
- Department of Psychiatry, Leiden University Medical Center, P.O. Box 9600, 2300 RC Leiden, The Netherlands
- Department of Psychiatry, Collaborative Antwerp Psychiatric Research Institute (CAPRI)-University of Antwerp, Antwerp, Belgium
| | - Serge A R B Rombouts
- Department of Radiology, Leiden University Medical Center, P.O. Box 9600, 2300 RC Leiden, The Netherlands
- Institute of Psychology, Leiden University, P.O. Box 9555, 2300 RB Leiden, The Netherlands
- Leiden Institute for Brain and Cognition, P.O. Box 9600, 2300 RC Leiden, The Netherlands
| | - Sanneke van Rooden
- Department of Radiology, Leiden University Medical Center, P.O. Box 9600, 2300 RC Leiden, The Netherlands
| | - Jeroen van der Grond
- Department of Radiology, Leiden University Medical Center, P.O. Box 9600, 2300 RC Leiden, The Netherlands
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Ross FC, Mayer DE, Horn J, Cryan JF, Del Rio D, Randolph E, Gill CIR, Gupta A, Ross RP, Stanton C, Mayer EA. Potential of dietary polyphenols for protection from age-related decline and neurodegeneration: a role for gut microbiota? Nutr Neurosci 2024:1-19. [PMID: 38287652 DOI: 10.1080/1028415x.2023.2298098] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/31/2024]
Abstract
Many epidemiological studies have shown the beneficial effects of a largely plant-based diet, and the strong association between the consumption of a Mediterranean-type diet with healthy aging including a lower risk of cognitive decline. The Mediterranean diet is characterized by a high intake of olive oil, fruits and vegetables and is rich in dietary fiber and polyphenols - both of which have been postulated to act as important mediators of these benefits. Polyphenols are large molecules produced by plants to protect them from environmental threats and injury. When ingested by humans, as little as 5% of these molecules are absorbed in the small intestine with the majority metabolized by the gut microbiota into absorbable simple phenolic compounds. Flavan-3-ols, a type of flavonoid, contained in grapes, berries, pome fruits, tea, and cocoa have been associated with many beneficial effects on several risk factors for cardiovascular disease, cognitive function and brain regions involved in memory formation. Both preclinical and clinical studies suggest that these brain and heart benefits can be attributed to endothelial vascular effects and anti-inflammatory properties among others. More recently the gut microbiota has emerged as a potential modulator of the aging brain and intriguingly polyphenols have been shown to alter microbiota composition and be metabolized by different microbial species. However, there is a need for well controlled studies in large populations to identify predictors of response, particularly given the vast inter-individual variation of human gut microbiota.
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Affiliation(s)
- F C Ross
- APC Microbiome Ireland, University College Cork, Co. Cork, Ireland
| | - D E Mayer
- Institute of Human Nutrition, Columbia University, New York, USA
| | - J Horn
- Oppenheimer Centre for Neurobiology of Stress and Resilience, Vatche and Tamar Manoukian Division of Digestive Diseases, David Geffen School of Medicine, UCLA, Los Angeles, USA
| | - J F Cryan
- APC Microbiome Ireland, University College Cork, Co. Cork, Ireland
- Department Anatomy & Neuroscience, University College Cork, Co. Cork, Ireland
| | - D Del Rio
- Department of Food and Drugs, University of Parma, Parma, Italy
| | - E Randolph
- Oppenheimer Centre for Neurobiology of Stress and Resilience, Vatche and Tamar Manoukian Division of Digestive Diseases, David Geffen School of Medicine, UCLA, Los Angeles, USA
| | - C I R Gill
- Nutrition Innovation Centre for Food and Health, Northern Ireland, UK
| | - A Gupta
- Division of Digestive Diseases, UCLA, Los Angeles, USA
- Goodman Luskin Microbiome Center at UCLA, Los Angeles, CA, USA
| | - R P Ross
- APC Microbiome Ireland, University College Cork, Co. Cork, Ireland
| | - C Stanton
- Teagasc Food Research Centre, Moorepark, Fermoy, Co. Cork, Ireland
| | - E A Mayer
- Oppenheimer Centre for Neurobiology of Stress and Resilience, Vatche and Tamar Manoukian Division of Digestive Diseases, David Geffen School of Medicine, UCLA, Los Angeles, USA
- Goodman Luskin Microbiome Center at UCLA, Los Angeles, CA, USA
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Liu M, Huang Q, Huang L, Ren S, Cui L, Zhang H, Guan Y, Guo Q, Xie F, Shen D. Dysfunctions of multiscale dynamic brain functional networks in subjective cognitive decline. Brain Commun 2024; 6:fcae010. [PMID: 38304005 PMCID: PMC10833653 DOI: 10.1093/braincomms/fcae010] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2023] [Revised: 11/22/2023] [Accepted: 01/15/2024] [Indexed: 02/03/2024] Open
Abstract
Subjective cognitive decline is potentially the earliest symptom of Alzheimer's disease, whose objective neurological basis remains elusive. To explore the potential biomarkers for subjective cognitive decline, we developed a novel deep learning method based on multiscale dynamical brain functional networks to identify subjective cognitive declines. We retrospectively constructed an internal data set (with 112 subjective cognitive decline and 64 healthy control subjects) to develop and internally validate the deep learning model. Conventional deep learning methods based on static and dynamic brain functional networks are compared. After the model is established, we prospectively collect an external data set (26 subjective cognitive decline and 12 healthy control subjects) for testing. Meanwhile, our method provides monitoring of the transitions between normal and abnormal (subjective cognitive decline-related) dynamical functional network states. The features of abnormal dynamical functional network states are quantified by network and variability metrics and associated with individual cognitions. Our method achieves an area under the receiver operating characteristic curve of 0.807 ± 0.046 in the internal validation data set and of 0.707 (P = 0.007) in the external testing data set, which shows improvements compared to conventional methods. The method further suggests that, at the local level, the abnormal dynamical functional network states are characterized by decreased connectivity strength and increased connectivity variability at different spatial scales. At the network level, the abnormal states are featured by scale-specifically altered modularity and all-scale decreased efficiency. Low tendencies to stay in abnormal states and high state transition variabilities are significantly associated with high general, language and executive functions. Overall, our work supports the deficits in multiscale brain dynamical functional networks detected by the deep learning method as reliable and meaningful neural alternation underpinning subjective cognitive decline.
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Affiliation(s)
- Mianxin Liu
- Shanghai Artificial Intelligence Laboratory, Shanghai 200232, China
- School of Biomedical Engineering, State Key Laboratory of Advanced Medical Materials and Devices, ShanghaiTech University, Shanghai 201210, China
| | - Qi Huang
- Department of Nuclear Medicine & PET Center, Huashan Hospital, Fudan University, Shanghai 200040, China
| | - Lin Huang
- Department of Gerontology, Shanghai Jiao Tong University Affiliated Sixth People’s Hospital, Shanghai 200233, China
| | - Shuhua Ren
- Department of Nuclear Medicine & PET Center, Huashan Hospital, Fudan University, Shanghai 200040, China
| | - Liang Cui
- Department of Gerontology, Shanghai Jiao Tong University Affiliated Sixth People’s Hospital, Shanghai 200233, China
| | - Han Zhang
- School of Biomedical Engineering, State Key Laboratory of Advanced Medical Materials and Devices, ShanghaiTech University, Shanghai 201210, China
| | - Yihui Guan
- Department of Nuclear Medicine & PET Center, Huashan Hospital, Fudan University, Shanghai 200040, China
| | - Qihao Guo
- Department of Gerontology, Shanghai Jiao Tong University Affiliated Sixth People’s Hospital, Shanghai 200233, China
| | - Fang Xie
- Department of Nuclear Medicine & PET Center, Huashan Hospital, Fudan University, Shanghai 200040, China
| | - Dinggang Shen
- School of Biomedical Engineering, State Key Laboratory of Advanced Medical Materials and Devices, ShanghaiTech University, Shanghai 201210, China
- Shanghai United Imaging Intelligence Co., Ltd., Shanghai 200230, China
- Shanghai Clinical Research and Trial Center, Shanghai, 201210, China
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Paban V, Mheich A, Spieser L, Sacher M. A multidimensional model of memory complaints in older individuals and the associated hub regions. Front Aging Neurosci 2023; 15:1324309. [PMID: 38187362 PMCID: PMC10771290 DOI: 10.3389/fnagi.2023.1324309] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2023] [Accepted: 11/27/2023] [Indexed: 01/09/2024] Open
Abstract
Memory complaints are highly prevalent among middle-aged and older adults, and they are frequently reported in individuals experiencing subjective cognitive decline (SCD). SCD has received increasing attention due to its implications for the early detection of dementia. This study aims to advance our comprehension of individuals with SCD by elucidating potential cognitive/psychologic-contributing factors and characterizing cerebral hubs within the brain network. To identify these potential contributing factors, a structural equation modeling approach was employed to investigate the relationships between various factors, such as metacognitive beliefs, personality, anxiety, depression, self-esteem, and resilience, and memory complaints. Our findings revealed that self-esteem and conscientiousness significantly influenced memory complaints. At the cerebral level, analysis of delta and theta electroencephalographic frequency bands recorded during rest was conducted to identify hub regions using a local centrality metric known as betweenness centrality. Notably, our study demonstrated that certain brain regions undergo changes in their hub roles in response to the pathology of SCD. Specifically, the inferior temporal gyrus and the left orbitofrontal area transition into hubs, while the dorsolateral prefrontal cortex and the middle temporal gyrus lose their hub function in the presence of SCD. This rewiring of the neural network may be interpreted as a compensatory response employed by the brain in response to SCD, wherein functional connectivity is maintained or restored by reallocating resources to other regions.
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Affiliation(s)
- Véronique Paban
- Aix-Marseille Université, CNRS, LNC (Laboratoire de Neurosciences Cognitives–UMR 7291), Marseille, France
| | - A. Mheich
- CHUV-Centre Hospitalier Universitaire Vaudois, Service des Troubles du Spectre de l’Autisme et Apparentés, Lausanne University Hospital, Lausanne, Switzerland
| | - L. Spieser
- Aix-Marseille Université, CNRS, LNC (Laboratoire de Neurosciences Cognitives–UMR 7291), Marseille, France
| | - M. Sacher
- University of Toulouse Jean-Jaurès, CNRS, LCLLE (Laboratoire Cognition, Langues, Langage, Ergonomie–UMR 5263), Toulouse, France
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Lazarou I, Oikonomou VP, Mpaltadoros L, Grammatikopoulou M, Alepopoulos V, Stavropoulos TG, Bezerianos A, Nikolopoulos S, Kompatsiaris I, Tsolaki M. Eliciting brain waves of people with cognitive impairment during meditation exercises using portable electroencephalography in a smart-home environment: a pilot study. Front Aging Neurosci 2023; 15:1167410. [PMID: 37388185 PMCID: PMC10306118 DOI: 10.3389/fnagi.2023.1167410] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2023] [Accepted: 05/03/2023] [Indexed: 07/01/2023] Open
Abstract
Objectives Meditation imparts relaxation and constitutes an important non-pharmacological intervention for people with cognitive impairment. Moreover, EEG has been widely used as a tool for detecting brain changes even at the early stages of Alzheimer's Disease (AD). The current study investigates the effect of meditation practices on the human brain across the AD spectrum by using a novel portable EEG headband in a smart-home environment. Methods Forty (40) people (13 Healthy Controls-HC, 14 with Subjective Cognitive Decline-SCD and 13 with Mild Cognitive Impairment-MCI) participated practicing Mindfulness Based Stress Reduction (Session 2-MBSR) and a novel adaptation of the Kirtan Kriya meditation to the Greek culture setting (Session 3-KK), while a Resting State (RS) condition was undertaken at baseline and follow-up (Session 1-RS Baseline and Session 4-RS Follow-Up). The signals were recorded by using the Muse EEG device and brain waves were computed (alpha, theta, gamma, and beta). Results Analysis was conducted on four-electrodes (AF7, AF8, TP9, and TP10). Statistical analysis included the Kruskal-Wallis (KW) nonparametric analysis of variance. The results revealed that both states of MBSR and KK lead to a marked difference in the brain's activation patterns across people at different cognitive states. Wilcoxon Signed-ranks test indicated for HC that theta waves at TP9, TP10 and AF7, AF8 in Session 3-KK were statistically significantly reduced compared to Session 1-RS Z = -2.271, p = 0.023, Z = -3.110, p = 0.002 and Z = -2.341, p = 0.019, Z = -2.132, p = 0.033, respectively. Conclusion The results showed the potential of the parameters used between the various groups (HC, SCD, and MCI) as well as between the two meditation sessions (MBSR and KK) in discriminating early cognitive decline and brain alterations in a smart-home environment without medical support.
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Affiliation(s)
- Ioulietta Lazarou
- Centre for Research and Technology Hellas (CERTH), Information Technologies Institute (ITI), Thessaloniki, Greece
| | - Vangelis P. Oikonomou
- Centre for Research and Technology Hellas (CERTH), Information Technologies Institute (ITI), Thessaloniki, Greece
| | - Lampros Mpaltadoros
- Centre for Research and Technology Hellas (CERTH), Information Technologies Institute (ITI), Thessaloniki, Greece
| | - Margarita Grammatikopoulou
- Centre for Research and Technology Hellas (CERTH), Information Technologies Institute (ITI), Thessaloniki, Greece
| | - Vasilis Alepopoulos
- Centre for Research and Technology Hellas (CERTH), Information Technologies Institute (ITI), Thessaloniki, Greece
| | - Thanos G. Stavropoulos
- Centre for Research and Technology Hellas (CERTH), Information Technologies Institute (ITI), Thessaloniki, Greece
| | - Anastasios Bezerianos
- Centre for Research and Technology Hellas (CERTH), Information Technologies Institute (ITI), Thessaloniki, Greece
| | - Spiros Nikolopoulos
- Centre for Research and Technology Hellas (CERTH), Information Technologies Institute (ITI), Thessaloniki, Greece
| | - Ioannis Kompatsiaris
- Centre for Research and Technology Hellas (CERTH), Information Technologies Institute (ITI), Thessaloniki, Greece
| | - Magda Tsolaki
- Centre for Research and Technology Hellas (CERTH), Information Technologies Institute (ITI), Thessaloniki, Greece
- 1st Department of Neurology, Faculty of Health Sciences, G.H. “AHEPA”, School of Medicine, Aristotle University of Thessaloniki (AUTH), Thessaloniki, Greece
- Greek Association of Alzheimer’s Disease and Related Disorders (GAADRD), Thessaloniki, Greece
- Laboratory of Neurodegenerative Diseases, Center for Interdisciplinary Research and Innovation (CIRI–AUTh), Aristotle University of Thessaloniki, Thessaloniki, Greece
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Lassi M, Fabbiani C, Mazzeo S, Burali R, Vergani AA, Giacomucci G, Moschini V, Morinelli C, Emiliani F, Scarpino M, Bagnoli S, Ingannato A, Nacmias B, Padiglioni S, Micera S, Sorbi S, Grippo A, Bessi V, Mazzoni A. Degradation of EEG microstates patterns in subjective cognitive decline and mild cognitive impairment: Early biomarkers along the Alzheimer's Disease continuum? Neuroimage Clin 2023; 38:103407. [PMID: 37094437 PMCID: PMC10149415 DOI: 10.1016/j.nicl.2023.103407] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2022] [Revised: 03/29/2023] [Accepted: 04/14/2023] [Indexed: 04/26/2023]
Abstract
Alzheimer's disease (AD) pathological changes may begin up to decades earlier than the appearance of the first symptoms of cognitive decline. Subjective cognitive decline (SCD) could be the first pre-clinical sign of possible AD, which might be followed by mild cognitive impairment (MCI), the initial stage of clinical cognitive decline. However, the neural correlates of these prodromic stages are not completely clear yet. Recent studies suggest that EEG analysis tools characterizing the cortical activity as a whole, such as microstates and cortical regions connectivity, might support a characterization of SCD and MCI conditions. Here we test this approach by performing a broad set of analyses to identify the prominent EEG markers differentiating SCD (n = 57), MCI (n = 46) and healthy control subjects (HC, n = 19). We found that the salient differences were in the temporal structure of the microstates patterns, with MCI being associated with less complex sequences due to the altered transition probability, frequency and duration of canonic microstate C. Spectral content of EEG, network connectivity, and spatial arrangement of microstates were instead largely similar in the three groups. Interestingly, comparing properties of EEG microstates in different cerebrospinal fluid (CSF) biomarkers profiles, we found that canonic microstate C displayed significant differences in topography in AD-like profile. These results show that the progression of dementia might be associated with a degradation of the cortical organization captured by microstates analysis, and that this leads to altered transitions between cortical states. Overall, our approach paves the way for the use of non-invasive EEG recordings in the identification of possible biomarkers of progression to AD from its prodromal states.
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Affiliation(s)
- Michael Lassi
- The BioRobotics Institute and Department of Excellence in Robotics and AI, Sant'Anna School of Advanced Studies, viale Rinaldo Piaggio 34, 56025 Pisa, Italy
| | - Carlo Fabbiani
- IRCCS Fondazione Don Carlo Gnocchi, via di Scandicci, 269, 50143 Florence, Italy
| | - Salvatore Mazzeo
- IRCCS Fondazione Don Carlo Gnocchi, via di Scandicci, 269, 50143 Florence, Italy; Department of Neuroscience, Psychology, Drug Research and Child Health, University of Florence, Careggi University Hospital, viale Gaetano Pieraccini, 6, 50139 Florence, Italy
| | - Rachele Burali
- IRCCS Fondazione Don Carlo Gnocchi, via di Scandicci, 269, 50143 Florence, Italy
| | - Alberto Arturo Vergani
- The BioRobotics Institute and Department of Excellence in Robotics and AI, Sant'Anna School of Advanced Studies, viale Rinaldo Piaggio 34, 56025 Pisa, Italy
| | - Giulia Giacomucci
- Department of Neuroscience, Psychology, Drug Research and Child Health, University of Florence, Careggi University Hospital, viale Gaetano Pieraccini, 6, 50139 Florence, Italy
| | - Valentina Moschini
- Department of Neuroscience, Psychology, Drug Research and Child Health, University of Florence, Careggi University Hospital, viale Gaetano Pieraccini, 6, 50139 Florence, Italy
| | - Carmen Morinelli
- Dipartimento Neuromuscolo-scheletrico e degli organi di senso, Careggi University Hospital, 50134 Florence, Italy
| | - Filippo Emiliani
- Department of Neuroscience, Psychology, Drug Research and Child Health, University of Florence, Careggi University Hospital, viale Gaetano Pieraccini, 6, 50139 Florence, Italy
| | - Maenia Scarpino
- IRCCS Fondazione Don Carlo Gnocchi, via di Scandicci, 269, 50143 Florence, Italy
| | - Silvia Bagnoli
- Department of Neuroscience, Psychology, Drug Research and Child Health, University of Florence, Careggi University Hospital, viale Gaetano Pieraccini, 6, 50139 Florence, Italy
| | - Assunta Ingannato
- Department of Neuroscience, Psychology, Drug Research and Child Health, University of Florence, Careggi University Hospital, viale Gaetano Pieraccini, 6, 50139 Florence, Italy
| | - Benedetta Nacmias
- IRCCS Fondazione Don Carlo Gnocchi, via di Scandicci, 269, 50143 Florence, Italy; Department of Neuroscience, Psychology, Drug Research and Child Health, University of Florence, Careggi University Hospital, viale Gaetano Pieraccini, 6, 50139 Florence, Italy
| | - Sonia Padiglioni
- Regional Referral Centre for Relational Criticalities - Tuscany Region, 50139 Florence, Italy
| | - Silvestro Micera
- The BioRobotics Institute and Department of Excellence in Robotics and AI, Sant'Anna School of Advanced Studies, viale Rinaldo Piaggio 34, 56025 Pisa, Italy; Bertarelli Foundation Chair in Translational Neuroengineering, Centre for Neuroprosthetics and Institute of Bioengineering, School of Engineering, École Polytechnique Fédérale de Lausanne (EPFL), 1015 Lausanne, Switzerland
| | - Sandro Sorbi
- IRCCS Fondazione Don Carlo Gnocchi, via di Scandicci, 269, 50143 Florence, Italy; Department of Neuroscience, Psychology, Drug Research and Child Health, University of Florence, Careggi University Hospital, viale Gaetano Pieraccini, 6, 50139 Florence, Italy
| | - Antonello Grippo
- IRCCS Fondazione Don Carlo Gnocchi, via di Scandicci, 269, 50143 Florence, Italy
| | - Valentina Bessi
- Department of Neuroscience, Psychology, Drug Research and Child Health, University of Florence, Careggi University Hospital, viale Gaetano Pieraccini, 6, 50139 Florence, Italy
| | - Alberto Mazzoni
- The BioRobotics Institute and Department of Excellence in Robotics and AI, Sant'Anna School of Advanced Studies, viale Rinaldo Piaggio 34, 56025 Pisa, Italy.
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Ren S, Hu J, Huang L, Li J, Jiang D, Hua F, Guan Y, Guo Q, Xie F, Huang Q. Graph Analysis of Functional Brain Topology Using Minimum Spanning Tree in Subjective Cognitive Decline. J Alzheimers Dis 2022; 90:1749-1759. [PMID: 36336928 DOI: 10.3233/jad-220527] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
BACKGROUND Subjects with subjective cognitive decline (SCD) are proposed as a potential population to screen for Alzheimer's disease (AD). OBJECTIVE Investigating brain topologies would help to mine the neuromechanisms of SCD and provide new insights into the pathogenesis of AD. METHODS Objectively cognitively unimpaired subjects from communities who underwent resting-state BOLD-fMRI and clinical assessments were included. The subjects were categorized into SCD and normal control (NC) groups according to whether they exhibited self-perceived cognitive decline and were worried about it. The minimum spanning tree (MST) of the functional brain network was calculated for each subject, based on which the efficiency and centrality of the brain network organization were explored. Hippocampal/parahippocampal volumes were also detected to reveal whether the early neurodegeneration of AD could be seen in SCD. RESULTS A total of 49 subjects in NC and 95 subjects in SCD group were included in this study. We found the efficiency and centrality of brain network organization, as well as the hippocampal/parahippocampal volume were preserved in SCD. Besides, SCD exhibited normal cognitions, including memory, language, and execution, but increased depressive and anxious levels. Interestingly, language and execution, instead of memory, showed a significant positive correlation with the maximum betweenness centrality of the functional brain organization and hippocampal/parahippocampal volume. Neither depressive nor anxious scales exhibited correlations with the brain functional topologies or hippocampal/parahippocampal volume. CONCLUSION SCD exhibited preserved efficiency and centrality of brain organization. In clinical practice, language and execution as well as depression and anxiety should be paid attention in SCD.
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Affiliation(s)
- Shuhua Ren
- PET Center, Huashan Hospital, Fudan University, Shanghai, China
| | - Jingchao Hu
- Department of Gerontology, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai, China.,School of Nursing, Shanghai Jiao Tong University, Shanghai, China
| | - Lin Huang
- Department of Gerontology, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai, China
| | - Junpeng Li
- PET Center, Huashan Hospital, Fudan University, Shanghai, China
| | - Donglang Jiang
- PET Center, Huashan Hospital, Fudan University, Shanghai, China
| | - Fengchun Hua
- Department of Nuclear Medicine, Longhua Hospital, Shanghai University of Traditional Chinese Medicine, Shanghai, China
| | - Yihui Guan
- PET Center, Huashan Hospital, Fudan University, Shanghai, China
| | - Qihao Guo
- Department of Gerontology, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai, China
| | - Fang Xie
- PET Center, Huashan Hospital, Fudan University, Shanghai, China
| | - Qi Huang
- PET Center, Huashan Hospital, Fudan University, Shanghai, China
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9
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Guo Y, Liu S, Yan F, Yin N, Ni J, Li C, Pan X, Ma R, Wu J, Li S, Li X. Associations between disrupted functional brain network topology and cognitive impairment in patients with rectal cancer during chemotherapy. Front Oncol 2022; 12:927771. [PMID: 36505777 PMCID: PMC9731768 DOI: 10.3389/fonc.2022.927771] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2022] [Accepted: 11/10/2022] [Indexed: 11/25/2022] Open
Abstract
Introduction Cognitive impairment has been identified in patients with non-central nervous system cancer received chemotherapy. Chemotherapy-induced changes in the brain are considered as the possible causes of the cognitive deficits of patients. This study aimed to explore chemotherapy-related functional brain changes and cognitive impairment in rectal cancer (RC) patients who had just finished chemotherapy treatment. Methods In this study, RC patients after chemotherapy (on the day patients received the last dose of chemotherapy) (n=30) and matched healthy controls (HCs) (n=30) underwent cognitive assessments, structural magnetic resonance imaging (MRI) and resting-state functional MRI. The functional brain networks were constructed by thresholding the partial correlation matrices of 90 brain regions in the Anatomical Automatic Labeling template and the topologic properties were evaluated by graph theory analysis. Moreover, correlations between altered topological measures and scores of cognitive scales were explored in the patient group. Results Compared with HCs, RC patients had lower scores of cognitive scales. The functional brain network had preserved small-world topological features but with a tendency towards higher path length in the whole network. In addition, patients had decreased nodal global efficiency (Eglo(i)) in the left superior frontal gyrus (dorsolateral), superior frontal gyrus (orbital part), inferior frontal gyrus (opercular part), inferior frontal gyrus (triangular part) and right inferior frontal gyrus (triangular part). Moreover, values of Eglo(i) in the superior and inferior frontal gyrus were positively associated with cognitive function in the patient group. Conclusion These results suggested that cognitive impairment was associated with disruptions of the topological organization in functional brain networks of RC patients who had just finished chemotherapy, which provided new insights into the pathophysiology underlying acute effects of chemotherapy on cognitive function.
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Affiliation(s)
- Yesong Guo
- Department of Radiotherapy, Jiangsu Cancer Hospital & Jiangsu Institute of Cancer Research & The Affiliated Cancer Hospital of Nanjing Medical University, Nanjing, China
| | - Siwen Liu
- Research Center for Clinical Oncology, Jiangsu Cancer Hospital & Jiangsu Institute of Cancer Research & The Affiliated Cancer Hospital of Nanjing Medical University, Nanjing, China
| | - Fei Yan
- Department of Oncology, Jiangsu Cancer Hospital & Jiangsu Institute of Cancer Research & The Affiliated Cancer Hospital of Nanjing Medical University, Nanjing, China
| | - Na Yin
- Department of Radiology, Jiangsu Cancer Hospital & Jiangsu Institute of Cancer Research & The Affiliated Cancer Hospital of Nanjing Medical University, Nanjing, China
| | - Jie Ni
- Department of Oncology, Jiangsu Cancer Hospital & Jiangsu Institute of Cancer Research & The Affiliated Cancer Hospital of Nanjing Medical University, Nanjing, China
| | - Chenchen Li
- Department of Oncology, Jiangsu Cancer Hospital & Jiangsu Institute of Cancer Research & The Affiliated Cancer Hospital of Nanjing Medical University, Nanjing, China
| | - Xuan Pan
- Department of Oncology, Jiangsu Cancer Hospital & Jiangsu Institute of Cancer Research & The Affiliated Cancer Hospital of Nanjing Medical University, Nanjing, China
| | - Rong Ma
- Research Center for Clinical Oncology, Jiangsu Cancer Hospital & Jiangsu Institute of Cancer Research & The Affiliated Cancer Hospital of Nanjing Medical University, Nanjing, China
| | - Jianzhong Wu
- Research Center for Clinical Oncology, Jiangsu Cancer Hospital & Jiangsu Institute of Cancer Research & The Affiliated Cancer Hospital of Nanjing Medical University, Nanjing, China
| | - Shengwei Li
- Department of Anorectal, Yangzhou Traditional Chinese Medicine Hospital Affiliated to Nanjing University of Chinese Medicine, Yangzhou, China,*Correspondence: Xiaoyou Li, ; Shengwei Li,
| | - Xiaoyou Li
- Department of Oncology, Jiangsu Cancer Hospital & Jiangsu Institute of Cancer Research & The Affiliated Cancer Hospital of Nanjing Medical University, Nanjing, China,*Correspondence: Xiaoyou Li, ; Shengwei Li,
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10
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Lazarou I, Georgiadis K, Nikolopoulos S, Oikonomou VP, Stavropoulos TG, Tsolaki A, Kompatsiaris I, Tsolaki M. Exploring Network Properties Across Preclinical Stages of Alzheimer’s Disease Using a Visual Short-Term Memory and Attention Task with High-Density Electroencephalography: A Brain-Connectome Neurophysiological Study. J Alzheimers Dis 2022; 87:643-664. [DOI: 10.3233/jad-215421] [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: Visual short-term memory (VSTMT) and visual attention (VAT) exhibit decline in the Alzheimer’s disease (AD) continuum; however, network disruption in preclinical stages is scarcely explored. Objective: To advance our knowledge about brain networks in AD and discover connectivity alterations during VSTMT and VAT. Methods: Twelve participants with AD, 23 with mild cognitive impairment (MCI), 17 with subjective cognitive decline (SCD), and 21 healthy controls (HC) were examined using a neuropsychological battery at baseline and follow-up (three years). At baseline, the subjects were examined using high density electroencephalography while performing a VSTMT and VAT. For exploring network organization, we constructed weighted undirected networks and examined clustering coefficient, strength, and betweenness centrality from occipito-parietal regions. Results: One-way ANOVA and pair-wise t-test comparisons showed statistically significant differences in HC compared to SCD (t (36) = 2.43, p = 0.026), MCI (t (42) = 2.34, p = 0.024), and AD group (t (31) = 3.58, p = 0.001) in Clustering Coefficient. Also with regards to Strength, higher values for HC compared to SCD (t (36) = 2.45, p = 0.019), MCI (t (42) = 2.41, p = 0.020), and AD group (t (31) = 3.58, p = 0.001) were found. Follow-up neuropsychological assessment revealed converge of 65% of the SCD group to MCI. Moreover, SCD who were converted to MCI showed significant lower values in all network metrics compared to the SCD that remained stable. Conclusion: The present findings reveal that SCD exhibits network disorganization during visual encoding and retrieval with intermediate values between MCI and HC.
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Affiliation(s)
- Ioulietta Lazarou
- Information Technologies Institute, Centre for Research and Technology Hellas (CERTH-ITI), Thessaloniki, Makedonia, Greece
- 1 Department of Neurology, G.H. “AHEPA”, School of Medicine, Faculty of Health Sciences, Aristotle University of Thessaloniki, Makedonia, Greece
| | - Kostas Georgiadis
- Information Technologies Institute, Centre for Research and Technology Hellas (CERTH-ITI), Thessaloniki, Makedonia, Greece
- Informatics Department, Aristotle University of Thessaloniki, Makedonia, Greece
| | - Spiros Nikolopoulos
- Information Technologies Institute, Centre for Research and Technology Hellas (CERTH-ITI), Thessaloniki, Makedonia, Greece
| | - Vangelis P. Oikonomou
- Information Technologies Institute, Centre for Research and Technology Hellas (CERTH-ITI), Thessaloniki, Makedonia, Greece
| | - Thanos G. Stavropoulos
- Information Technologies Institute, Centre for Research and Technology Hellas (CERTH-ITI), Thessaloniki, Makedonia, Greece
| | - Anthoula Tsolaki
- Information Technologies Institute, Centre for Research and Technology Hellas (CERTH-ITI), Thessaloniki, Makedonia, Greece
- Greek Association of Alzheimer’s Disease and Related Disorders, Thessaloniki, Makedonia, Greece
| | - Ioannis Kompatsiaris
- Information Technologies Institute, Centre for Research and Technology Hellas (CERTH-ITI), Thessaloniki, Makedonia, Greece
| | - Magda Tsolaki
- Information Technologies Institute, Centre for Research and Technology Hellas (CERTH-ITI), Thessaloniki, Makedonia, Greece
- 1 Department of Neurology, G.H. “AHEPA”, School of Medicine, Faculty of Health Sciences, Aristotle University of Thessaloniki, Makedonia, Greece
- Greek Association of Alzheimer’s Disease and Related Disorders, Thessaloniki, Makedonia, Greece
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11
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Yang F, Jiang X, Yue F, Wang L, Boecker H, Han Y, Jiang J. Exploring dynamic functional connectivity alterations in the preclinical stage of Alzheimer's disease: an exploratory study from SILCODE. J Neural Eng 2022; 19. [PMID: 35147522 DOI: 10.1088/1741-2552/ac542d] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2021] [Accepted: 02/08/2022] [Indexed: 11/11/2022]
Abstract
INTRODUCTION Exploring functional connectivity (FC) alterations is important for the understanding of underlying neuronal network alterations in subjective cognitive decline (SCD). The objective of this study was to prove that dynamic FC can better reflect the changes of brain function in individuals with SCD compared to static FC, and further to explore the association between FC alterations and amyloid pathology in the preclinical stage of Alzheimer's disease (AD). METHODS 101 normal control (NC) subjects, 97 SCDs, and 55 cognitive impairment (CI) subjects constituted the whole-cohort. Of these, 29 NCs and 52 SCDs with amyloid images were selected as the sub-cohort. First, independent components (ICs) were identified by independent component analysis and static and dynamic FC were calculated by pairwise correlation coefficient between ICs. Second, FC alterations were identified through group comparison, and seed-based dynamic FC analysis was done. Analysis of variance (ANOVA) was used to compare the seed-based dynamic FC maps and measure the group or amyloid effects. Finally, correlation analysis was conducted between the altered dynamic FC and amyloid burden. RESULTS The results showed that 42 ICs were revealed. Significantly altered dynamic FC included those between the salience/ventral attention network, the default mode network, and the visual network. Specifically, the thalamus/caudate (IC 25) drove the hub role in the group differences. In the seed-based dynamic FC analysis, the dynamic FC between the thalamus/caudate and the middle temporal/frontal gyrus was observed to be higher in the SCD and CI groups. Moreover, a higher dynamic FC between the thalamus/caudate and visual cortex was observed in the amyloid positive group. Finally, the altered dynamic FC was associated with the amyloid global standardized uptake value ratio (SUVr). CONCLUSION Our findings suggest SCD-related alterations could be more reflected by dynamic FC than static FC, and the alterations are associated with global SUVr.
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Affiliation(s)
- Fan Yang
- Shanghai University, Shangda Road, Baoshan district, Shanghai, Shanghai, 200444, CHINA
| | - Xueyan Jiang
- Hainan University, Meilan District, Haikou City, Hainan Province, Haikou, 570288, CHINA
| | - Feng Yue
- Hainan University, Meilan District, Haikou City, Hainan Province, Haikou, 570288, CHINA
| | - Luyao Wang
- Shanghai University, Shangda road, Baoshan district, shanghai, Shanghai, 200444, CHINA
| | - Henning Boecker
- University Hospital Bonn, Positron Emission Tomography (PET) Group, Bonn, Germany, Bonn, Nordrhein-Westfalen, 53127, GERMANY
| | - Ying Han
- Hainan University, Meilan District, Haikou City, Hainan Province, Haikou, 570288, CHINA
| | - Jiehui Jiang
- Shanghai University, Shangda road, Baoshan district, Shanghai, Shanghai, 200444, CHINA
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12
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Ota M, Numata Y, Kitabatake A, Tsukada E, Kaneta T, Asada T, Meno K, Uchida K, Suzuki H, Korenaga T, Arai T. Structural brain network correlations with amyloid burden in elderly individuals at risk of Alzheimer's disease. Psychiatry Res Neuroimaging 2022; 319:111415. [PMID: 34839208 DOI: 10.1016/j.pscychresns.2021.111415] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/17/2021] [Revised: 08/10/2021] [Accepted: 11/10/2021] [Indexed: 11/29/2022]
Abstract
Alzheimer's disease (AD) has a long preclinical phase during which beta-amyloid accumulates in the brain without cognitive impairment. However, the pattern of brain network alterations in this early stage of the disease remains to be clarified. In this study we examined the relationships between regional brain network indices and beta-amyloid deposits. Twenty-four elderly subjects with the APOE4 allele underwent both a 1.5-Tesla magnetic resonance imaging (MRI) scan and a positron emission tomography (PET) scan using [18F]Florbetapir. We computed network metrics such as the degree, betweenness centrality, and clustering coefficient, and examined the relationships between the beta-amyloid accumulation and these regional brain network connectivity metrics. We found a significant positive correlation between the global standardized uptake value ratio (SUVR) of [18F]Florbetapir and the betweenness centrality in the left parietal region. However, there were no significant correlations between the SUVR score and other network indices or the regional gray matter volume. Our data suggest a relationship between the beta-amyloid accumulation and the regional brain network connectivity in subjects at risk of AD. The brain connectome may provide an adjunct biomarker for the early detection of AD.
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Affiliation(s)
- Miho Ota
- Department of Psychiatry, Division of Clinical Medicine, Faculty of Medicine, University of Tsukuba, 1-1-1 Tennoudai, Tsukuba, Ibaraki, 305-8576, Japan.
| | - Yuriko Numata
- Department of Psychiatry, Division of Clinical Medicine, Faculty of Medicine, University of Tsukuba, 1-1-1 Tennoudai, Tsukuba, Ibaraki, 305-8576, Japan
| | - Ayako Kitabatake
- Department of Psychiatry, Division of Clinical Medicine, Faculty of Medicine, University of Tsukuba, 1-1-1 Tennoudai, Tsukuba, Ibaraki, 305-8576, Japan
| | - Eriko Tsukada
- Department of Psychiatry, Division of Clinical Medicine, Faculty of Medicine, University of Tsukuba, 1-1-1 Tennoudai, Tsukuba, Ibaraki, 305-8576, Japan
| | - Tomohiro Kaneta
- Department of Advanced Molecular Imaging, Faculty of Medicine, University of Tsukuba, Tsukuba, 1-1-1 Tennoudai, Tsukuba, Ibaraki, 305-8576, Japan
| | - Takashi Asada
- Department of Neuropsychiatry, Tokyo Medical And Dental University, Bunkyo-ku, Tokyo, 113-8549, Japan
| | - Kohji Meno
- Tsukuba Industrial Liaison and Cooperative Research Center, University of Tsukuba, Tsukuba, 1-1-1 Tennoudai, Tsukuba, Ibaraki, 305-8576, Japan
| | - Kazuhiko Uchida
- Tsukuba Industrial Liaison and Cooperative Research Center, University of Tsukuba, Tsukuba, 1-1-1 Tennoudai, Tsukuba, Ibaraki, 305-8576, Japan
| | - Hideaki Suzuki
- Tsukuba Industrial Liaison and Cooperative Research Center, University of Tsukuba, Tsukuba, 1-1-1 Tennoudai, Tsukuba, Ibaraki, 305-8576, Japan
| | - Tatsumi Korenaga
- Tsukuba Industrial Liaison and Cooperative Research Center, University of Tsukuba, Tsukuba, 1-1-1 Tennoudai, Tsukuba, Ibaraki, 305-8576, Japan
| | - Tetsuaki Arai
- Department of Psychiatry, Division of Clinical Medicine, Faculty of Medicine, University of Tsukuba, 1-1-1 Tennoudai, Tsukuba, Ibaraki, 305-8576, Japan
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13
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Liang L, Chen Z, Wei Y, Tang F, Nong X, Li C, Yu B, Duan G, Su J, Mai W, Zhao L, Zhang Z, Deng D. Fusion analysis of gray matter and white matter in subjective cognitive decline and mild cognitive impairment by multimodal CCA-joint ICA. Neuroimage Clin 2021; 32:102874. [PMID: 34911186 PMCID: PMC8605254 DOI: 10.1016/j.nicl.2021.102874] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2021] [Revised: 10/30/2021] [Accepted: 11/01/2021] [Indexed: 11/25/2022]
Abstract
BACKGROUND Previous multimodal neuroimaging studies analyzed each dataset independently in subjective cognitive decline (SCD) and mild cognitive impairment (MCI), missing the cross-information. Multi-modal fusion analysis can provide more integral and comprehensive information regarding the brain. There has been a paucity of research on fusion analysis of sMRI and DTI in SCD and MCI. MATERIALS AND METHODS In the present study, we conducted fusion analysis of structural MRI and DTI by applying multimodal canonical correlation analysis with joint independent component analysis (mCCA-jICA) to capture the cross-information of gray matter (GM) and white matter (WM) in 62 SCD patients, 99 MCI patients, and 70 healthy controls (HCs). We further analyzed correlations between the mixing coefficients of mCCA-jICA and neuropsychological scores among the three groups. RESULTS A set of joint-discriminative independent components of GM and fractional anisotropy (FA) exhibited significant links between SCD and HCs, as well as between MCI and HCs. The covariant abnormalities primarily involved the frontal lobe/middle temporal gyrus/calcarine sulcus-anterior thalamic radiation/superior longitudinal fasciculus in SCD, and middle temporal gyrus/ fusiform gyrus/caudate necleus-forceps minor/anterior thalamic radiation in MCI. There was no significant difference between SCD and MCI groups. CONCLUSIONS The covariant GM-WM abnormalities in SCD and MCI were found in specific brain regions involved in cognitive processing, which confirms the simultaneous GM and WM changes underlying cognitive decline. These findings suggest that multimodal fusion analysis allows for a more comprehensive understanding of the association among different types of brain tissues and its crucial role in the neuropathological mechanism of SCD and MCI.
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Affiliation(s)
- Lingyan Liang
- The People's Hospital of Guangxi Zhuang Autonomous Region, Nanning 530021, Guangxi, China
| | - Zaili Chen
- School of Biomedical Engineering, Health Science Center, Shenzhen University, Shenzhen 518060, China; Department of Medical Instrument Measurement, Shenzhen Academy of Metrology and Quality Inspection, Shenzhen 518055, China.
| | - Yichen Wei
- Department of Radiology, First Affiliated Hospital, Guangxi University of Chinese Medicine, Nanning 530023, Guangxi, China
| | - Fei Tang
- School of Biomedical Engineering, Health Science Center, Shenzhen University, Shenzhen 518060, China; Department of Medical Instrument Measurement, Shenzhen Academy of Metrology and Quality Inspection, Shenzhen 518055, China.
| | - Xiucheng Nong
- Department of Acupuncture, First Affiliated Hospital, Guangxi University of Chinese Medicine, Nanning 530023, Guangxi, China
| | - Chong Li
- Department of Acupuncture, First Affiliated Hospital, Guangxi University of Chinese Medicine, Nanning 530023, Guangxi, China
| | - Bihan Yu
- Department of Acupuncture, First Affiliated Hospital, Guangxi University of Chinese Medicine, Nanning 530023, Guangxi, China
| | - Gaoxiong Duan
- The People's Hospital of Guangxi Zhuang Autonomous Region, Nanning 530021, Guangxi, China
| | - Jiahui Su
- Department of Acupuncture, First Affiliated Hospital, Guangxi University of Chinese Medicine, Nanning 530023, Guangxi, China
| | - Wei Mai
- Department of Acupuncture, First Affiliated Hospital, Guangxi University of Chinese Medicine, Nanning 530023, Guangxi, China
| | - Lihua Zhao
- Department of Acupuncture, First Affiliated Hospital, Guangxi University of Chinese Medicine, Nanning 530023, Guangxi, China
| | - Zhiguo Zhang
- School of Biomedical Engineering, Health Science Center, Shenzhen University, Shenzhen 518060, China; Guangdong Provincial Key Laboratory of Biomedical Measurements and Ultrasound Imaging, Shenzhen 518060, China; Peng Cheng Laboratory, Shenzhen 518055, China.
| | - Demao Deng
- The People's Hospital of Guangxi Zhuang Autonomous Region, Nanning 530021, Guangxi, China.
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14
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Lazarou I, Moraitou D, Papatheodorou M, Vavouras I, Lokantidou C, Agogiatou C, Gialaoutzis M, Nikolopoulos S, Stavropoulos TG, Kompatsiaris I, Tsolaki M. Adaptation and Validation of the Memory Alteration Test (M@T) in Greek Middle-Aged, Older, and Older-Old Population with Subjective Cognitive Decline and Mild Cognitive Impairment. J Alzheimers Dis 2021; 84:1219-1232. [PMID: 34657882 DOI: 10.3233/jad-210558] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
BACKGROUND The Memory Alteration Test (M@T) is a verbal episodic and semantic memory screening test able to detect subjective cognitive decline (SCD) and Mild Cognitive Impairment (MCI). OBJECTIVE To adapt M@T, creating a Greek version of the Memory Alteration Test (M@T-GR), and to validate M@T-GR compared to the Mini-Mental State Examination (MMSE), and Subjective Cognitive Decline- Questionnaire (SCD-Q) MyCog and TheirCog. METHODS 232 people over 55 years old participated in the study and they were classified as healthy controls (HC, n = 65), SCD (n = 78), or MCI (n = 89). RESULTS The ANCOVA showed that the M@T-GR's total score was significantly different in HC and SCD (I-J = 2.26, p = 0.032), HC and MCI (I-J = 6.16, p < 0.0001), and SCD compared to MCI (I-J = 3.90, p < 0.0001). In particular, a cut-off score of 46.50 points had an 81%sensitivity and 61%specificity for discriminating HC from SCD (AUC = 0.76, p < 0.0001), while a cut-off score of 45.50 had a sensitivity of 92%and a specificity of 73%for discriminating MCI (AUC = 0.88, p < 0.0001), and a cut-off score of 45.50 points had a sensitivity of 63%and a specificity of 73%for discriminating SCD from those with MCI (AUC = 0.69, p < 0.0021). Exploratory factor analysis indicated that there was one factor explaining 38.46%of the total variance. Internal consistency was adequate (α= 0.75), while convergent validity was found between M@T-GR and MMSE (r = 0.37, p < 0.0001) and SCD-Q TheirCog (r = -0.32, p < 0.0001). CONCLUSION The M@T-GR is a good to fair screening tool with adequate discriminant validity for administration in people with SCD and MCI in Greece.
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Affiliation(s)
- Ioulietta Lazarou
- Information Technologies Institute, Centre for Research and Technology Hellas, Thessaloniki, Greece.,1st Department of Neurology, G.H. "AHEPA", School of Medicine, Faculty of Health Sciences, Aristotle University of Thessaloniki, Thessaloniki, Greece
| | - Despina Moraitou
- Laboratory of Psychology, School of Psychology, Aristotle University of Thessaloniki, Thessaloniki, Greece
| | - Marianna Papatheodorou
- Greek Association of Alzheimer's Disease and Related Disorders (GAADRD), Thessaloniki, Greece
| | - Isaak Vavouras
- Greek Association of Alzheimer's Disease and Related Disorders (GAADRD), Thessaloniki, Greece
| | - Chrysanthi Lokantidou
- Greek Association of Alzheimer's Disease and Related Disorders (GAADRD), Thessaloniki, Greece
| | - Christina Agogiatou
- Greek Association of Alzheimer's Disease and Related Disorders (GAADRD), Thessaloniki, Greece
| | - Moses Gialaoutzis
- Greek Association of Alzheimer's Disease and Related Disorders (GAADRD), Thessaloniki, Greece
| | - Spiros Nikolopoulos
- Information Technologies Institute, Centre for Research and Technology Hellas, Thessaloniki, Greece
| | - Thanos G Stavropoulos
- Information Technologies Institute, Centre for Research and Technology Hellas, Thessaloniki, Greece
| | - Ioannis Kompatsiaris
- Information Technologies Institute, Centre for Research and Technology Hellas, Thessaloniki, Greece
| | - Magda Tsolaki
- Information Technologies Institute, Centre for Research and Technology Hellas, Thessaloniki, Greece.,1st Department of Neurology, G.H. "AHEPA", School of Medicine, Faculty of Health Sciences, Aristotle University of Thessaloniki, Thessaloniki, Greece.,Greek Association of Alzheimer's Disease and Related Disorders (GAADRD), Thessaloniki, Greece
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15
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Portillo-Lara R, Tahirbegi B, Chapman CAR, Goding JA, Green RA. Mind the gap: State-of-the-art technologies and applications for EEG-based brain-computer interfaces. APL Bioeng 2021; 5:031507. [PMID: 34327294 PMCID: PMC8294859 DOI: 10.1063/5.0047237] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/11/2021] [Accepted: 05/19/2021] [Indexed: 11/14/2022] Open
Abstract
Brain-computer interfaces (BCIs) provide bidirectional communication between the brain and output devices that translate user intent into function. Among the different brain imaging techniques used to operate BCIs, electroencephalography (EEG) constitutes the preferred method of choice, owing to its relative low cost, ease of use, high temporal resolution, and noninvasiveness. In recent years, significant progress in wearable technologies and computational intelligence has greatly enhanced the performance and capabilities of EEG-based BCIs (eBCIs) and propelled their migration out of the laboratory and into real-world environments. This rapid translation constitutes a paradigm shift in human-machine interaction that will deeply transform different industries in the near future, including healthcare and wellbeing, entertainment, security, education, and marketing. In this contribution, the state-of-the-art in wearable biosensing is reviewed, focusing on the development of novel electrode interfaces for long term and noninvasive EEG monitoring. Commercially available EEG platforms are surveyed, and a comparative analysis is presented based on the benefits and limitations they provide for eBCI development. Emerging applications in neuroscientific research and future trends related to the widespread implementation of eBCIs for medical and nonmedical uses are discussed. Finally, a commentary on the ethical, social, and legal concerns associated with this increasingly ubiquitous technology is provided, as well as general recommendations to address key issues related to mainstream consumer adoption.
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Affiliation(s)
- Roberto Portillo-Lara
- Department of Bioengineering, Imperial College London, Royal School of Mines, London SW7 2AZ, United Kingdom
| | - Bogachan Tahirbegi
- Department of Bioengineering, Imperial College London, Royal School of Mines, London SW7 2AZ, United Kingdom
| | - Christopher A. R. Chapman
- Department of Bioengineering, Imperial College London, Royal School of Mines, London SW7 2AZ, United Kingdom
| | - Josef A. Goding
- Department of Bioengineering, Imperial College London, Royal School of Mines, London SW7 2AZ, United Kingdom
| | - Rylie A. Green
- Department of Bioengineering, Imperial College London, Royal School of Mines, London SW7 2AZ, United Kingdom
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16
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Tao W, Li H, Li X, Huang R, Shao W, Guan Q, Zhang Z. Progressive Brain Degeneration From Subjective Cognitive Decline to Amnestic Mild Cognitive Impairment: Evidence From Large-Scale Anatomical Connection Classification Analysis. Front Aging Neurosci 2021; 13:687530. [PMID: 34322011 PMCID: PMC8312851 DOI: 10.3389/fnagi.2021.687530] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2021] [Accepted: 06/07/2021] [Indexed: 11/13/2022] Open
Abstract
People with subjective cognitive decline (SCD) and amnestic mild cognitive impairment (aMCI) are both at high risk for Alzheimer’s disease (AD). Behaviorally, both SCD and aMCI have subjective reports of cognitive decline, but the latter suffers a more severe objective cognitive impairment than the former. However, it remains unclear how the brain develops from SCD to aMCI. In the current study, we aimed to investigate the topological characteristics of the white matter (WM) network that can successfully identify individuals with SCD or aMCI from healthy control (HC) and to describe the relationship of pathological changes between these two stages. To this end, three groups were recruited, including 22 SCD, 22 aMCI, and 22 healthy control (HC) subjects. We constructed WM network for each subject and compared large-scale topological organization between groups at both network and nodal levels. At the network level, the combined network indexes had the best performance in discriminating aMCI from HC. However, no indexes at the network level can significantly identify SCD from HC. These results suggested that aMCI but not SCD was associated with anatomical impairments at the network level. At the nodal level, we found that the short-path length can best differentiate between aMCI and HC subjects, whereas the global efficiency has the best performance in differentiating between SCD and HC subjects, suggesting that both SCD and aMCI had significant functional integration alteration compared to HC subjects. These results converged on the idea that the neural degeneration from SCD to aMCI follows a gradual process, from abnormalities at the nodal level to those at both nodal and network levels.
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Affiliation(s)
- Wuhai Tao
- Center for Brain Disorders and Cognitive Science, Shenzhen University, Shenzhen, China.,Shenzhen-Hong Kong Institute of Brain Science-Shenzhen Fundamental Research Institutions, Shenzhen, China
| | - Hehui Li
- Center for Brain Disorders and Cognitive Science, Shenzhen University, Shenzhen, China
| | - Xin Li
- State Key Laboratory of Cognitive Neuroscience and Learning and IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Rong Huang
- Center for Brain Disorders and Cognitive Science, Shenzhen University, Shenzhen, China
| | - Wen Shao
- Department of Neurology, China-Japan Friendship Hospital, Beijing, China
| | - Qing Guan
- Center for Brain Disorders and Cognitive Science, Shenzhen University, Shenzhen, China.,Shenzhen-Hong Kong Institute of Brain Science-Shenzhen Fundamental Research Institutions, Shenzhen, China
| | - Zhanjun Zhang
- State Key Laboratory of Cognitive Neuroscience and Learning and IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
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Sharma N, Murari G, Vandermorris S, Verhoeff NPLG, Herrmann N, Chen JJ, Mah L. Functional Connectivity Between the Posterior Default Mode Network and Parahippocampal Gyrus Is Disrupted in Older Adults with Subjective Cognitive Decline and Correlates with Subjective Memory Ability. J Alzheimers Dis 2021; 82:435-445. [PMID: 34024823 DOI: 10.3233/jad-201579] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
BACKGROUND Subjective cognitive decline (SCD) is associated with increased risk of developing Alzheimer's disease (AD). However, the underlying mechanisms for this association remain unclear. Neuroimaging studies suggest the earliest AD-related changes are large-scale network disruptions, beginning in the posterior default mode (pDMN) network. OBJECTIVE To examine the association between SCD and pDMN network connectivity with medial temporal lobe (MTL) regions using resting-state functional magnetic resonance imaging. METHODS Forty-nine participants with either SCD (n = 23, 12 females; mean age: 70.7 (5.5)) or who were cognitively unimpaired (CU; n = 26, 16 females, mean age: 71.42 (7.3)) completed the Memory Functioning Questionnaire, a measure of subjective memory, and underwent resting state functional MRI at 3 Tesla. Functional connectivity between the posterior cingulate cortex (PCC), as the key pDMN node, and MTL regions were compared between SCD and CU groups. Further, the association between pDMN-MTL connectivity and the Frequency of Forgetting subscale of the Memory Functioning Questionnaire was examined. RESULTS Connectivity between the PCC-MTL was observed in the CU group but was absent in SCD (t(47) = 2.69, p = 0.01). Across all participants, self-perception of frequency of forgetting, but not objective memory, was strongly correlated with connectivity between the PCC-left parahippocampal gyrus (r = 0.43, p = 0.002). CONCLUSION These findings support the hypothesis that increased AD risk in SCD may be mediated by disrupted pDMN-parahippocampal connectivity. In addition, these findings suggest that frequency of forgetting may serve as a potential biomarker of SCD due to incipient AD.
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Affiliation(s)
- Namita Sharma
- Rotman Research Institute, Baycrest Health Sciences, Toronto, Ontario, Canada
| | - Geetanjali Murari
- Rotman Research Institute, Baycrest Health Sciences, Toronto, Ontario, Canada
| | | | - Nicolaas Paul L G Verhoeff
- Baycrest Health Sciences, Toronto, Ontario, Canada.,Department of Psychiatry, Geriatric Psychiatry Division, University of Toronto, Toronto, ON, Canada
| | - Nathan Herrmann
- Sunnybrook Research Institute, Sunnybrook Health Sciences Centre, Toronto, Ontario, Canada.,Department of Psychiatry, Geriatric Psychiatry Division, University of Toronto, Toronto, ON, Canada
| | - J Jean Chen
- Rotman Research Institute, Baycrest Health Sciences, Toronto, Ontario, Canada.,Department of Medical Biophysics, University of Toronto, Toronto, ON, Canada
| | - Linda Mah
- Rotman Research Institute, Baycrest Health Sciences, Toronto, Ontario, Canada.,Department of Psychiatry, Geriatric Psychiatry Division, University of Toronto, Toronto, ON, Canada
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Effects of Combined Physical Activity and Cognitive Training on Cognitive Function in Older Adults with Subjective Cognitive Decline: A Systematic Review and Meta-Analysis of Randomized Controlled Trials. EVIDENCE-BASED COMPLEMENTARY AND ALTERNATIVE MEDICINE 2021. [DOI: 10.1155/2021/8882961] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
Background. Subjective cognitive decline (SCD) is recognized as the earliest prodromal stage of Alzheimer’s disease (AD). Emerging studies explored the effects of combined physical activity and cognitive training interventions on cognitive ability, psychological well-being, and emotion of older adults with SCD, but the results are now still controversial. Objective. This study systematically evaluated the enhancement effects of the combined physical-cognitive interventions on memory self-efficacy, objective cognitive function, psychological well-being, and emotion of older adults with SCD. Methods. Data sources PubMed, EMBASE, Web of Science, China National Knowledge Infrastructure (CNKI), Wanfang degree and conference papers database, Chinese Science and Technology Periodical (VIP) databases from their inception to 28 February 2020, the Cochrane Central Register of Controlled Trials (Cochrane Library, 2020, Issue 3), and the reference lists of all retrieved articles were searched. Data analysis and bias risk evaluation were conducted in 2020. Two reviewers (SG and YY) independently evaluated the risk of bias of the included studies using the RoB 2 tool. Results. Eleven RCTs involving 1713 participants with SCD (age 68.0 ± 6.1) were included for review and meta-analysis. The interventions in the included studies were physical activity combined with cognitive training. Multiple-modality exercise with mind-motor training, supervised strategy-based memory training sequentially after stationary cycling, Dejian Mind-Body intervention, and physical activity and cognitive stimulation were also practiced. Conclusions. Compared to the active or nonactive control groups, the combined interventions are effective in improving objective cognitive function in SCD which may show the potential value of combined physical-cognitive interventions in improving objective cognitive ability and preventing the conversion of SCD to MCI or AD and no adverse effects. However, owing to the limitations of the included studies, these findings should be interpreted cautiously.
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19
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Liang L, Yuan Y, Wei Y, Yu B, Mai W, Duan G, Nong X, Li C, Su J, Zhao L, Zhang Z, Deng D. Recurrent and concurrent patterns of regional BOLD dynamics and functional connectivity dynamics in cognitive decline. ALZHEIMERS RESEARCH & THERAPY 2021; 13:28. [PMID: 33453729 PMCID: PMC7811744 DOI: 10.1186/s13195-020-00764-6] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/03/2020] [Accepted: 12/23/2020] [Indexed: 11/10/2022]
Abstract
Background The brain’s dynamic spontaneous neural activity and dynamic functional connectivity (dFC) are both important in supporting cognition, but how these two types of brain dynamics evolve and co-evolve in subjective cognitive decline (SCD) and mild cognitive impairment (MCI) remain unclear. The aim of the present study was to investigate recurrent and concurrent patterns of two types of dynamic brain states correlated with cognitive decline. Methods The present study analyzed resting-state functional magnetic resonance imaging data from 62 SCD patients, 75 MCI patients, and 70 healthy controls (HCs). We used the sliding-window and clustering method to identify two types of recurrent brain states from both dFC and dynamic regional spontaneous activity, as measured by dynamic fractional amplitude of low-frequency fluctuations (dfALFF). Then, the occurrence frequency of a dFC or dfALFF state and the co-occurrence frequency of a pair of dFC and dfALFF states among all time points are extracted for each participant to describe their dynamics brain patterns. Results We identified a few recurrent states of dfALFF and dFC and further ascertained the co-occurrent patterns of these two types of dynamic brain states (i.e., dfALFF and dFC states). Importantly, the occurrence frequency of a default-mode network (DMN)-dominated dFC state was significantly different between HCs and SCD patients, and the co-occurrence frequencies of a DMN-dominated dFC state and a DMN-dominated dfALFF state were also significantly different between SCD and MCI patients. These two dynamic features were both significantly positively correlated with Mini-Mental State Examination scores. Conclusion Our findings revealed novel fMRI-based neural signatures of cognitive decline from recurrent and concurrent patterns of dfALFF and dFC, providing strong evidence supporting SCD as the transition phase between normal aging and MCI. This finding holds potential to differentiate SCD patients from HCs via both dFC and dfALFF as objective neuroimaging biomarkers, which may aid in the early diagnosis and intervention of Alzheimer’s disease. Supplementary Information The online version contains supplementary material available at 10.1186/s13195-020-00764-6.
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Affiliation(s)
- Lingyan Liang
- Department of Radiology, First Affiliated Hospital, Guangxi University of Chinese Medicine, Nanning, 530023, Guangxi, China
| | - Yueming Yuan
- School of Biomedical Engineering, Health Science Center, Shenzhen University, Shenzhen, 518060, China.,Guangdong Provincial Key Laboratory of Biomedical Measurements and Ultrasound Imaging, Shenzhen, 518060, China
| | - Yichen Wei
- Department of Radiology, First Affiliated Hospital, Guangxi University of Chinese Medicine, Nanning, 530023, Guangxi, China
| | - Bihan Yu
- Department of Acupuncture, First Affiliated Hospital, Guangxi University of Chinese Medicine, Nanning, 530023, Guangxi, China
| | - Wei Mai
- Department of Acupuncture, First Affiliated Hospital, Guangxi University of Chinese Medicine, Nanning, 530023, Guangxi, China
| | - Gaoxiong Duan
- Department of Radiology, First Affiliated Hospital, Guangxi University of Chinese Medicine, Nanning, 530023, Guangxi, China
| | - Xiucheng Nong
- Department of Acupuncture, First Affiliated Hospital, Guangxi University of Chinese Medicine, Nanning, 530023, Guangxi, China
| | - Chong Li
- Department of Acupuncture, First Affiliated Hospital, Guangxi University of Chinese Medicine, Nanning, 530023, Guangxi, China
| | - Jiahui Su
- Department of Acupuncture, First Affiliated Hospital, Guangxi University of Chinese Medicine, Nanning, 530023, Guangxi, China
| | - Lihua Zhao
- Department of Acupuncture, First Affiliated Hospital, Guangxi University of Chinese Medicine, Nanning, 530023, Guangxi, China.
| | - Zhiguo Zhang
- School of Biomedical Engineering, Health Science Center, Shenzhen University, Shenzhen, 518060, China. .,Guangdong Provincial Key Laboratory of Biomedical Measurements and Ultrasound Imaging, Shenzhen, 518060, China. .,Peng Cheng Laboratory, Shenzhen, 518055, China.
| | - Demao Deng
- The People's Hospital of Guangxi Zhuang Autonomous Region, Nanning, 530021, Guangxi, China.
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20
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Auditory event-related potentials in individuals with subjective and mild cognitive impairment. Behav Brain Res 2020; 391:112700. [DOI: 10.1016/j.bbr.2020.112700] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2019] [Revised: 04/19/2020] [Accepted: 05/08/2020] [Indexed: 12/11/2022]
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21
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Human brain connectivity: Clinical applications for clinical neurophysiology. Clin Neurophysiol 2020; 131:1621-1651. [DOI: 10.1016/j.clinph.2020.03.031] [Citation(s) in RCA: 34] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2019] [Revised: 03/13/2020] [Accepted: 03/17/2020] [Indexed: 12/12/2022]
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Ioulietta L, Kostas G, Spiros N, Vangelis OP, Anthoula T, Ioannis K, Magda T, Dimitris K. A Novel Connectome-Based Electrophysiological Study of Subjective Cognitive Decline Related to Alzheimer's Disease by Using Resting-State High-Density EEG EGI GES 300. Brain Sci 2020; 10:brainsci10060392. [PMID: 32575641 PMCID: PMC7349850 DOI: 10.3390/brainsci10060392] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2020] [Revised: 06/17/2020] [Accepted: 06/18/2020] [Indexed: 12/17/2022] Open
Abstract
Aim: To investigate for the first time the brain network in the Alzheimer’s disease (AD) spectrum by implementing a high-density electroencephalography (HD-EEG - EGI GES 300) study with 256 channels in order to seek if the brain connectome can be effectively used to distinguish cognitive impairment in preclinical stages. Methods: Twenty participants with AD, 30 with mild cognitive impairment (MCI), 20 with subjective cognitive decline (SCD) and 22 healthy controls (HC) were examined with a detailed neuropsychological battery and 10 min resting state HD-EEG. We extracted correlation matrices by using Pearson correlation coefficients for each subject and constructed weighted undirected networks for calculating clustering coefficient (CC), strength (S) and betweenness centrality (BC) at global (256 electrodes) and local levels (29 parietal electrodes). Results: One-way ANOVA presented a statistically significant difference among the four groups at local level in CC [F (3, 88) = 4.76, p = 0.004] and S [F (3, 88) = 4.69, p = 0.004]. However, no statistically significant difference was found at a global level. According to the independent sample t-test, local CC was higher for HC [M (SD) = 0.79 (0.07)] compared with SCD [M (SD) = 0.72 (0.09)]; t (40) = 2.39, p = 0.02, MCI [M (SD) = 0.71 (0.09)]; t (50) = 0.41, p = 0.004 and AD [M (SD) = 0.68 (0.11)]; t (40) = 3.62, p = 0.001 as well, while BC showed an increase at a local level but a decrease at a global level as the disease progresses. These findings provide evidence that disruptions in brain networks in parietal organization may potentially represent a key factor in the ability to distinguish people at early stages of the AD continuum. Conclusions: The above findings reveal a dynamically disrupted network organization of preclinical stages, showing that SCD exhibits network disorganization with intermediate values between MCI and HC. Additionally, these pieces of evidence provide information on the usefulness of the 256 HD-EEG in network construction.
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Affiliation(s)
- Lazarou Ioulietta
- Information Technologies Institute, Centre for Research and Technology Hellas (CERTH-ITI), 57001 Thessaloniki, Greece; (G.K.); (N.S.); (O.V.P.); (T.A.); (K.I.); (T.M.)
- 1st Department of Neurology, G.H. “AHEPA”, School of Medicine, Faculty of Health Sciences, Aristotle University of Thessaloniki (AUTH), 54124 Thessaloniki, Greece
- Correspondence:
| | - Georgiadis Kostas
- Information Technologies Institute, Centre for Research and Technology Hellas (CERTH-ITI), 57001 Thessaloniki, Greece; (G.K.); (N.S.); (O.V.P.); (T.A.); (K.I.); (T.M.)
- Informatics Department, Aristotle University of Thessaloniki (AUTH), 54124 Thessaloniki, Greece
| | - Nikolopoulos Spiros
- Information Technologies Institute, Centre for Research and Technology Hellas (CERTH-ITI), 57001 Thessaloniki, Greece; (G.K.); (N.S.); (O.V.P.); (T.A.); (K.I.); (T.M.)
| | - Oikonomou P. Vangelis
- Information Technologies Institute, Centre for Research and Technology Hellas (CERTH-ITI), 57001 Thessaloniki, Greece; (G.K.); (N.S.); (O.V.P.); (T.A.); (K.I.); (T.M.)
| | - Tsolaki Anthoula
- Information Technologies Institute, Centre for Research and Technology Hellas (CERTH-ITI), 57001 Thessaloniki, Greece; (G.K.); (N.S.); (O.V.P.); (T.A.); (K.I.); (T.M.)
- Greek Association of Alzheimer’s Disease and Related Disorders (GAADRD), 54643 Thessaloniki, Greece
| | - Kompatsiaris Ioannis
- Information Technologies Institute, Centre for Research and Technology Hellas (CERTH-ITI), 57001 Thessaloniki, Greece; (G.K.); (N.S.); (O.V.P.); (T.A.); (K.I.); (T.M.)
| | - Tsolaki Magda
- Information Technologies Institute, Centre for Research and Technology Hellas (CERTH-ITI), 57001 Thessaloniki, Greece; (G.K.); (N.S.); (O.V.P.); (T.A.); (K.I.); (T.M.)
- 1st Department of Neurology, G.H. “AHEPA”, School of Medicine, Faculty of Health Sciences, Aristotle University of Thessaloniki (AUTH), 54124 Thessaloniki, Greece
- Greek Association of Alzheimer’s Disease and Related Disorders (GAADRD), 54643 Thessaloniki, Greece
| | - Kugiumtzis Dimitris
- Department of Electrical and Computer Engineering, Faculty of Engineering, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece;
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23
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Si T, Xing G, Han Y. Subjective Cognitive Decline and Related Cognitive Deficits. Front Neurol 2020; 11:247. [PMID: 32508729 PMCID: PMC7248257 DOI: 10.3389/fneur.2020.00247] [Citation(s) in RCA: 34] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/22/2019] [Accepted: 03/13/2020] [Indexed: 12/21/2022] Open
Abstract
Since late stage dementia, including Alzheimer's disease (AD), cannot be reversed by any available drugs, there is increasing research interest in the preclinical stage of AD, i.e., subjective cognitive decline (SCD). SCD is characterized by self-perceptive cognitive decline but is difficult to detect using objective tests. At SCD stage, the cognitive deficits can be more easily reversed compared to that of mild cognitive impairment (MCI) and AD only if accurate diagnosis of SCD and early intervention can be developed. In this paper, we review the recent progress of SCD research including current assessment tools, biomarkers, neuroimaging, intervention and expected prognosis, and the potential relevance to traumatic brain injury (TBI)-induced cognitive deficits.
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Affiliation(s)
- Tong Si
- Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Guoqiang Xing
- The Affiliated Hospital and the Second Clinical Medical College of North Sichuan Medical University, Nanchong Central Hospital, Nanchong, China
| | - Ying Han
- Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, China.,National Clinical Research Center for Geriatric Disorders, Beijing, China.,Center of Alzheimer's Disease, Beijing Institute for Brain Disorders, Beijing, China
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