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- Hajebrahimi, F, et al.
(författare)
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Clinical evaluation and resting state fMRI analysis of virtual reality based training in Parkinson's disease through a randomized controlled trial
- 2022
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Ingår i: Scientific reports. - : Springer Science and Business Media LLC. - 2045-2322. ; 12:1, s. 8024-
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Tidskriftsartikel (refereegranskat)abstract
- There are few studies investigating the short-term effects of Virtual Reality based Exergaming (EG) on motor and cognition simultaneously and pursue the brain functional activity changes after these interventions in patients with Parkinson’s Disease (PD). The purpose of this study was to investigate the synergistic therapeutic effects of Virtual Reality based EG on motor and cognitive symptoms in PD and its possible effects on neuroplasticity. Eligible patients with the diagnosis of PD were randomly assigned to one of the two study groups: (1) an experimental EG group, (2) an active control Exercise Therapy (ET) group. All patients participated in a 4-week exercise program consisting of 12 treatment sessions. Every session lasted 60 min. Participants underwent a motor evaluation, extensive neuropsychological assessment battery and rs-fMRI before and after the interventions. Thirty patients fulfilled the inclusion criteria and were randomly assigned to the EG and ET groups. After the dropouts, 23 patients completed the assessments and interventions (11 in EG, 13 in ET). Within group analysis showed significant improvements in both groups. Between group comparisons considering the interaction of group × time effect, showed superiority of EG in terms of general cognition, delayed visual recall memory and Boston Naming Test. These results were consistent in the within-group and between-group analysis. Finally, rs-fMRI analysis showed increased activity in the precuneus region in the time × group interaction in the favor of EG group. EG can be an effective alternative in terms of motor and cognitive outcomes in patients with PD. Compared to ET, EG may affect brain functional connectivity and can have beneficial effects on patients’ cognitive functions and motor symptoms. Whenever possible, using EG and ET in combination, may have the better effects on patients daily living and patients can benefit from the advantages of both interventions.
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- Hanoglu, L, et al.
(författare)
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Therapeutic Role of Repetitive Transcranial Magnetic Stimulation in Alzheimer's and Parkinson's Disease: Electroencephalography Microstate Correlates
- 2022
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Ingår i: Frontiers in neuroscience. - : Frontiers Media SA. - 1662-4548 .- 1662-453X. ; 16, s. 798558-
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Tidskriftsartikel (refereegranskat)abstract
- The microstate analysis is a method to convert the electrical potentials on the multi-channel electrode array to topographical electroencephalography (EEG) data. Repetitive transcranial magnetic stimulation (rTMS) is a non-invasive method that can modulate brain networks. This study explores the pathophysiological changes through microstate analysis in two different neurodegenerative diseases, Alzheimer’s (AD) and Parkinson’s disease (PD), characterized by motor and cognitive symptoms and analysis the effect of rTMS on the impaired cognitive and motor functions.Materials and MethodsWe included 18 AD, 8 PD patients, and 13 age-matched controls. For both groups, we applied 5 Hz rTMS on the left pre-SMA in PD patients while 20 Hz rTMS on the left lateral parietal region in AD patients. Each patient was re-evaluated 1 week after the end of the sessions, which included a detailed clinical evaluation and measurement of EEG microstates.ResultsAt the baseline, the common findings between our AD and PD patients were altered microstate (MS) B, MS D durations and transition frequencies between MS A–MS B, MS C–MS D while global explained variance (GEV) ratio and the extent and frequency of occurrence of MS A, MS B, and MS D were separately altered in AD patients. Although no specific microstate parameter adequately differentiated between AD and PD patients, we observed significant changes in MS B and MS D parameters in PD patients. Further, we observed that Mini-Mental State Examination (MMSE) performances were associated with the transition frequencies between MS A–MS B and MS C–MS D and GEV ratio. After left parietal rTMS application, we have observed significantly increased visual memory recognition and clock drawing scores after left parietal rTMS application associated with improved microstate conditions prominent, especially in the mean duration of MS C in AD patients. Also, pre-SMA rTMS resulted in significant improvement in motor scores and frequency of transitions from MS D to MS C in PD patients.ConclusionThis study shows that PD and AD can cause different and similar microstate changes that can be modulated through rTMS, suggesting the role of MS parameters and rTMS as a possible combination in monitoring the treatment effect in neurodegenerative diseases.
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- Kayasandik, CB, et al.
(författare)
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Predicting the Effects of Repetitive Transcranial Magnetic Stimulation on Cognitive Functions in Patients With Alzheimer's Disease by Automated EEG Analysis
- 2022
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Ingår i: Frontiers in cellular neuroscience. - : Frontiers Media SA. - 1662-5102. ; 16, s. 845832-
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Tidskriftsartikel (refereegranskat)abstract
- Alzheimer's disease (AD) is a progressive, neurodegenerative brain disorder that generally affects the elderly. Today, after the limited benefit of the pharmacological treatment strategies, numerous noninvasive brain stimulation techniques have been developed. Transcranial magnetic stimulation (TMS), based on electromagnetic stimulation, is one of the most widely used methods. The main problem in the use of TMS is the existence of large individual variability in the results. This causes a waste of money, time, and more importantly, a burden for delicate patients. Hence, it is a necessity to form an efficient and personalized TMS application protocol. In this paper, we performed a machine-learning analysis to see whether it is possible to predict the responses of patients with AD to TMS by analyzing their electroencephalography (EEG) signals. For that purpose, we analyzed both the EEG signals collected before and after the TMS application (EEG1 and EEG2, respectively). Through correlating EEG1 and repetitive transcranial magnetic stimulation (rTMS) outcomes, we tried to see whether it is possible to predict patients' responses before the treatment application. On the other hand, by EEG2 analysis, we investigated TMS impacts on EEG, more importantly if this impact is correlated with patients' response to the treatment. We used the support vector machine (SVM) classifier due to its multiple advantages for the current task with feature selection processes by stepwise linear discriminant analysis (SWLDA) and SVM. However, to justify our numerical analysis framework, we examined and compared the performances of different feature selection and classification techniques. Since we have a limited sample number, we used the leave-one-out method for the validation with the Monte Carlo technique to eliminate bias by a small sample size. In the conclusion, we observed that the correlation between rTMS outcomes and EEG2 is stronger than EEG1, since we observed, respectively, 93 and 79% of accuracies during our data analysis. Besides the informative features of EEG2 are focused on theta band, it indicates that TMS is characterizing the theta band signals in patients with AD in direct relation to patients' response to rTMS. This shows that it is more possible to determine patients' benefit from the TMS at the early stages of the treatment, which would increase the efficiency of rTMS applications in patients with Alzheimer's disease.
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- Yulug, B., et al.
(författare)
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Combined metabolic activators improve cognitive functions in Alzheimer's disease patients: a randomised, double-blinded, placebo-controlled phase-II trial
- 2023
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Ingår i: Translational Neurodegeneration. - : Springer Science and Business Media LLC. - 2047-9158. ; 12:1
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Tidskriftsartikel (refereegranskat)abstract
- Background Alzheimer's disease (AD) is associated with metabolic abnormalities linked to critical elements of neurodegeneration. We recently administered combined metabolic activators (CMA) to the AD rat model and observed that CMA improves the AD-associated histological parameters in the animals. CMA promotes mitochondrial fatty acid uptake from the cytosol, facilitates fatty acid oxidation in the mitochondria, and alleviates oxidative stress.Methods Here, we designed a randomised, double-blinded, placebo-controlled phase-II clinical trial and studied the effect of CMA administration on the global metabolism of AD patients. One-dose CMA included 12.35 g L-serine (61.75%), 1 g nicotinamide riboside (5%), 2.55 g N-acetyl-L-cysteine (12.75%), and 3.73 g L-carnitine tartrate (18.65%). AD patients received one dose of CMA or placebo daily during the first 28 days and twice daily between day 28 and day 84. The primary endpoint was the difference in the cognitive function and daily living activity scores between the placebo and the treatment arms. The secondary aim of this study was to evaluate the safety and tolerability of CMA. A comprehensive plasma metabolome and proteome analysis was also performed to evaluate the efficacy of the CMA in AD patients.Results We showed a significant decrease of AD Assessment Scale-cognitive subscale (ADAS-Cog) score on day 84 vs day 0 (P = 0.00001, 29% improvement) in the CMA group. Moreover, there was a significant decline (P = 0.0073) in ADAS-Cog scores (improvement of cognitive functions) in the CMA compared to the placebo group in patients with higher ADAS-Cog scores. Improved cognitive functions in AD patients were supported by the relevant alterations in the hippocampal volumes and cortical thickness based on imaging analysis. Moreover, the plasma levels of proteins and metabolites associated with NAD + and glutathione metabolism were significantly improved after CMA treatment.Conclusion Our results indicate that treatment of AD patients with CMA can lead to enhanced cognitive functions and improved clinical parameters associated with phenomics, metabolomics, proteomics and imaging analysis.
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