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Arjmandi-Rad S, Vestergaard Nieland JD, Goozee KG, Vaseghi S. The effects of different acetylcholinesterase inhibitors on EEG patterns in patients with Alzheimer's disease: A systematic review. Neurol Sci 2024; 45:417-430. [PMID: 37843690 DOI: 10.1007/s10072-023-07114-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2023] [Accepted: 10/01/2023] [Indexed: 10/17/2023]
Abstract
OBJECTIVE Alzheimer's disease (AD) is a progressive neurodegenerative disorder and the most common type of dementia. The early diagnosis of AD is an important factor for the control of AD progression. Electroencephalography (EEG) can be used for early diagnosis of AD. Acetylcholinesterase inhibitors (AChEIs) are also used for the amelioration of AD symptoms. In this systematic review, we reviewed the effect of different AChEIs including donepezil, rivastigmine, tacrine, physostigmine, and galantamine on EEG patterns in patients with AD. METHODS PubMed electronic database was searched and 122 articles were found. After removal of unrelated articles, 24 articles were selected for the present study. RESULTS AChEIs can decrease beta, theta, and delta frequency bands in patients with AD. However, conflicting results were found for alpha band. Some studies have shown increased alpha frequency, while others have shown decreased alpha frequency following treatment with AChEIs. The only difference was the type of drug. CONCLUSIONS We found that studies reporting the decreased alpha frequency used donepezil and galantamine, while studies reporting the increased alpha frequency used rivastigmine and tacrine. It was suggested that future studies should focus on the effect of different AChEIs on EEG bands, especially alpha frequency in patients with AD, to compare their effects and find the reason for their different influence on EEG patterns. Also, differences between the effects of AChEIs on oligodendrocyte differentiation and myelination may be another important factor. This is the first article investigating the effect of different AChEIs on EEG patterns in patients with AD.
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Affiliation(s)
- Shirin Arjmandi-Rad
- Institute for Cognitive & Brain Sciences, Shahid Beheshti University, Tehran, Iran
| | | | - Kathryn G Goozee
- KaRa Institute of Neurological Diseases Pty Ltd, Macquarie, NSW, Australia
- Faculty of Medicine and Health Sciences, Macquarie University, Sydney, NSW, Australia
| | - Salar Vaseghi
- Cognitive Neuroscience Lab, Medicinal Plants Research Center, Institute of Medicinal Plants, ACECR, Karaj, Iran.
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Li X, Zhou X, Zheng H, Wang C. The modulation of pain in reward processing is reflected by increased P300 and delta oscillation. Brain Cogn 2023; 168:105972. [PMID: 37079997 DOI: 10.1016/j.bandc.2023.105972] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2022] [Revised: 03/16/2023] [Accepted: 03/26/2023] [Indexed: 04/22/2023]
Abstract
Pain elicits the desire for a reward to alleviate the unpleasant sensation. This may be a consequence of facilitated neural activities in the reward circuit. However, the temporal modulation of pain on reward processing remains unclear. We addressed this issue by recording electroencephalogram when participants received win or loss feedback in a simple gambling task. Pain treatment was conducted on 33 participants with topical capsaicin cream and on 33 participants with hand cream as a control. Results showed that pain generally increased the P300 amplitude for both types of feedback but did not affect feedback-related negativity (FRN). A significant interaction effect of treatment (painful, non-painful) and outcome (win, loss) was observed on delta oscillation as pain only enhanced the power of win feedback. In addition, the FRN and theta oscillation responded more to loss feedback, but this effect was unaffected by pain. These findings indicate that pain may enhance secondary value representation and evaluation processes of rewards, but does not influence primary distinction of reward or reward expectation. The temporal unfolding of how pain affects reward-related neural activities highlights the prominent impact of pain on high-level cognitive processes associated with reward.
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Affiliation(s)
- Xingyao Li
- Shanghai Key Laboratory of Mental Health and Psychological Crisis Intervention, Affiliated Mental Health Center (ECNU), School of Psychology and Cognitive Science, East China Normal University, Shanghai, China; Institute of Brain and Education Innovation, East China Normal University, Shanghai, China
| | - Xianzhen Zhou
- Shanghai Key Laboratory of Mental Health and Psychological Crisis Intervention, Affiliated Mental Health Center (ECNU), School of Psychology and Cognitive Science, East China Normal University, Shanghai, China; Cognitive Neurophysiology, Department of Child and Adolescent Psychiatry, Faculty of Medicine, TU Dresden, Germany
| | - Hong Zheng
- Shanghai Key Laboratory of Mental Health and Psychological Crisis Intervention, Affiliated Mental Health Center (ECNU), School of Psychology and Cognitive Science, East China Normal University, Shanghai, China; Shanghai Changning Mental Health Center, Shanghai, China.
| | - Chenbo Wang
- Shanghai Key Laboratory of Mental Health and Psychological Crisis Intervention, Affiliated Mental Health Center (ECNU), School of Psychology and Cognitive Science, East China Normal University, Shanghai, China; Institute of Brain and Education Innovation, East China Normal University, Shanghai, China.
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Saikia UP, Chander NG, Balasubramanian M. Effect of fixed dental prosthesis on the brain functions of partially edentulous patients - pilot study with power spectrum density analysis. Eur Oral Res 2020; 54:114-118. [PMID: 33543115 PMCID: PMC7837703 DOI: 10.26650/eor.20200032] [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] [Indexed: 11/21/2022] Open
Abstract
Purpose: This study was done to analyse the influence of fixed dental prosthesis (FDP) on
brain function by analysing power spectral density of partially edentulous patients. Materials and methods: The study included unilateral missing mandibular molar replacement patients. The
patients were restored with three-unit metal ceramic FDP restorations. The cognitive
function was analysed with a mental state questionnaire. Power spectral density
(PSD) analysis of EEG alpha waves was made pre- treatment, post treatment and 3
months after FDP treatment to analyse the brain function. The data in various phases
were obtained before and after chewing. The results were statistically analysed. Results: The mean pre and post treatment PSD was 0.0175 (SD ±0.0132) and 0.0178 (SD
±0.0135). The mean post treatment PSD after three months was 0.024 (SD± 0.019).
The results were analysed with repeated ANOVA and were statistically significant.
(p<0.01). Conclusion: The study displayed improvement in brain function of partially edentulous patients
with FDP rehabilitation.
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Affiliation(s)
| | - N Gopi Chander
- Department of Prosthodontics, SRM Dental College, Ramapuram, Chennai, Tamilnadu,India
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Cassani R, Estarellas M, San-Martin R, Fraga FJ, Falk TH. Systematic Review on Resting-State EEG for Alzheimer's Disease Diagnosis and Progression Assessment. DISEASE MARKERS 2018; 2018:5174815. [PMID: 30405860 PMCID: PMC6200063 DOI: 10.1155/2018/5174815] [Citation(s) in RCA: 141] [Impact Index Per Article: 23.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/20/2018] [Revised: 07/12/2018] [Accepted: 07/29/2018] [Indexed: 12/17/2022]
Abstract
Alzheimer's disease (AD) is a neurodegenerative disorder that accounts for nearly 70% of the more than 46 million dementia cases estimated worldwide. Although there is no cure for AD, early diagnosis and an accurate characterization of the disease progression can improve the quality of life of AD patients and their caregivers. Currently, AD diagnosis is carried out using standardized mental status examinations, which are commonly assisted by expensive neuroimaging scans and invasive laboratory tests, thus rendering the diagnosis time consuming and costly. Notwithstanding, over the last decade, electroencephalography (EEG) has emerged as a noninvasive alternative technique for the study of AD, competing with more expensive neuroimaging tools, such as MRI and PET. This paper reports on the results of a systematic review on the utilization of resting-state EEG signals for AD diagnosis and progression assessment. Recent journal articles obtained from four major bibliographic databases were analyzed. A total of 112 journal articles published from January 2010 to February 2018 were meticulously reviewed, and relevant aspects of these papers were compared across articles to provide a general overview of the research on this noninvasive AD diagnosis technique. Finally, recommendations for future studies with resting-state EEG were presented to improve and facilitate the knowledge transfer among research groups.
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Affiliation(s)
- Raymundo Cassani
- Institut national de la recherche scientifique (INRS-EMT), University of Québec, Montreal, Canada
| | - Mar Estarellas
- Institut national de la recherche scientifique (INRS-EMT), University of Québec, Montreal, Canada
- Department of Bioengineering, Imperial College London, London, UK
| | - Rodrigo San-Martin
- Center for Mathematics, Computation and Cognition, Universidade Federal do ABC, São Bernardo do Campo, Brazil
| | - Francisco J. Fraga
- Engineering, Modeling and Applied Social Sciences Center, Universidade Federal do ABC, São Bernardo do Campo, Brazil
| | - Tiago H. Falk
- Institut national de la recherche scientifique (INRS-EMT), University of Québec, Montreal, Canada
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Houmani N, Vialatte F, Gallego-Jutglà E, Dreyfus G, Nguyen-Michel VH, Mariani J, Kinugawa K. Diagnosis of Alzheimer's disease with Electroencephalography in a differential framework. PLoS One 2018; 13:e0193607. [PMID: 29558517 PMCID: PMC5860733 DOI: 10.1371/journal.pone.0193607] [Citation(s) in RCA: 54] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2017] [Accepted: 02/14/2018] [Indexed: 11/19/2022] Open
Abstract
This study addresses the problem of Alzheimer’s disease (AD) diagnosis with Electroencephalography (EEG). The use of EEG as a tool for AD diagnosis has been widely studied by comparing EEG signals of AD patients only to those of healthy subjects. By contrast, we perform automated EEG diagnosis in a differential diagnosis context using a new database, acquired in clinical conditions, which contains EEG data of 169 patients: subjective cognitive impairment (SCI) patients, mild cognitive impairment (MCI) patients, possible Alzheimer’s disease (AD) patients, and patients with other pathologies. We show that two EEG features, namely epoch-based entropy (a measure of signal complexity) and bump modeling (a measure of synchrony) are sufficient for efficient discrimination between these groups. We studied the performance of our methodology for the automatic discrimination of possible AD patients from SCI patients and from patients with MCI or other pathologies. A classification accuracy of 91.6% (specificity = 100%, sensitivity = 87.8%) was obtained when discriminating SCI patients from possible AD patients and 81.8% to 88.8% accuracy was obtained for the 3-class classification of SCI, possible AD and other patients.
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Affiliation(s)
- Nesma Houmani
- SAMOVAR, Télécom SudParis, CNRS, Université Paris-Saclay, 9 rue Charles Fourier EVRY, France
- * E-mail:
| | - François Vialatte
- UMR CNRS 8249 Brain Plasticity Laboratory, Paris, France
- ESPCI Paris, PSL Research University, Paris, France
| | - Esteve Gallego-Jutglà
- Data and Signal Processing Research Group, U Science Tech, University of Vic–Central University of Catalonia, Vic, Catalonia, Spain
| | | | - Vi-Huong Nguyen-Michel
- AP-HP, DHU FAST, GH Pitié-Salpêtrière-Charles Foix, Functional Exploration Unit of older patients, Ivry-sur-Seine, France
| | - Jean Mariani
- AP-HP, DHU FAST, GH Pitié-Salpêtrière-Charles Foix, Functional Exploration Unit of older patients, Ivry-sur-Seine, France
- Sorbonne Universités, UPMC Univ Paris 06, UMR 8256, Biological Adaptation and Ageing, Paris, France
- CNRS, UMR 8256, Biological Adaptation and Ageing, Paris, France
| | - Kiyoka Kinugawa
- AP-HP, DHU FAST, GH Pitié-Salpêtrière-Charles Foix, Functional Exploration Unit of older patients, Ivry-sur-Seine, France
- Sorbonne Universités, UPMC Univ Paris 06, UMR 8256, Biological Adaptation and Ageing, Paris, France
- CNRS, UMR 8256, Biological Adaptation and Ageing, Paris, France
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Wen D, Jia P, Lian Q, Zhou Y, Lu C. Review of Sparse Representation-Based Classification Methods on EEG Signal Processing for Epilepsy Detection, Brain-Computer Interface and Cognitive Impairment. Front Aging Neurosci 2016; 8:172. [PMID: 27458376 PMCID: PMC4937019 DOI: 10.3389/fnagi.2016.00172] [Citation(s) in RCA: 22] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2016] [Accepted: 06/28/2016] [Indexed: 12/16/2022] Open
Abstract
At present, the sparse representation-based classification (SRC) has become an important approach in electroencephalograph (EEG) signal analysis, by which the data is sparsely represented on the basis of a fixed dictionary or learned dictionary and classified based on the reconstruction criteria. SRC methods have been used to analyze the EEG signals of epilepsy, cognitive impairment and brain computer interface (BCI), which made rapid progress including the improvement in computational accuracy, efficiency and robustness. However, these methods have deficiencies in real-time performance, generalization ability and the dependence of labeled sample in the analysis of the EEG signals. This mini review described the advantages and disadvantages of the SRC methods in the EEG signal analysis with the expectation that these methods can provide the better tools for analyzing EEG signals.
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Affiliation(s)
- Dong Wen
- School of Information Science and Engineering, Yanshan UniversityQinhuangdao, China; The Key Laboratory for Computer Virtual Technology and System Integration of Hebei Province, Yanshan UniversityQinhuangdao, China
| | - Peilei Jia
- School of Information Science and Engineering, Yanshan UniversityQinhuangdao, China; The Key Laboratory for Computer Virtual Technology and System Integration of Hebei Province, Yanshan UniversityQinhuangdao, China
| | - Qiusheng Lian
- School of Information Science and Engineering, Yanshan UniversityQinhuangdao, China; The Key Laboratory for Computer Virtual Technology and System Integration of Hebei Province, Yanshan UniversityQinhuangdao, China
| | - Yanhong Zhou
- School of Mathematics and Information Science and Technology, Hebei Normal University of Science and Technology Qinhuangdao, China
| | - Chengbiao Lu
- School of Basic Medicine, Xinxiang Medical University Xinxiang, China
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Cacabelos R, Cacabelos P, Torrellas C, Tellado I, Carril JC. Pharmacogenomics of Alzheimer's disease: novel therapeutic strategies for drug development. Methods Mol Biol 2014; 1175:323-556. [PMID: 25150875 DOI: 10.1007/978-1-4939-0956-8_13] [Citation(s) in RCA: 54] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
Alzheimer's disease (AD) is a major problem of health and disability, with a relevant economic impact on our society. Despite important advances in pathogenesis, diagnosis, and treatment, its primary causes still remain elusive, accurate biomarkers are not well characterized, and the available pharmacological treatments are not cost-effective. As a complex disorder, AD is a polygenic and multifactorial clinical entity in which hundreds of defective genes distributed across the human genome may contribute to its pathogenesis. Diverse environmental factors, cerebrovascular dysfunction, and epigenetic phenomena, together with structural and functional genomic dysfunctions, lead to amyloid deposition, neurofibrillary tangle formation, and premature neuronal death, the major neuropathological hallmarks of AD. Future perspectives for the global management of AD predict that genomics and proteomics may help in the search for reliable biomarkers. In practical terms, the therapeutic response to conventional drugs (cholinesterase inhibitors, multifactorial strategies) is genotype-specific. Genomic factors potentially involved in AD pharmacogenomics include at least five categories of gene clusters: (1) genes associated with disease pathogenesis; (2) genes associated with the mechanism of action of drugs; (3) genes associated with drug metabolism (phase I and II reactions); (4) genes associated with drug transporters; and (5) pleiotropic genes involved in multifaceted cascades and metabolic reactions. The implementation of pharmacogenomic strategies will contribute to optimize drug development and therapeutics in AD and related disorders.
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Affiliation(s)
- Ramón Cacabelos
- Chair of Genomic Medicine, Camilo José Cela University, 28692, Villanueva de la Cañada, Madrid, Spain,
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