scholarly journals Non-invasive Brain Stimulation in Alzheimer's Disease and Mild Cognitive Impairment—A State-of-the-Art Review on Methodological Characteristics and Stimulation Parameters

2020 ◽  
Vol 14 ◽  
Author(s):  
Adrienn Holczer ◽  
Viola Luca Németh ◽  
Teodóra Vékony ◽  
László Vécsei ◽  
Péter Klivényi ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Brain Stimulation ◽  
State Of The Art ◽  
Non Invasive ◽  
Stimulation Parameters

scholarly journals Classification of Alzheimer’s Disease and Mild Cognitive Impairment Based on Cortical and Subcortical Features from MRI T1 Brain Images Utilizing Four Different Types of Datasets

2020 ◽  
Vol 2020 ◽  
pp. 1-14 ◽  
Author(s):  
Saidjalol Toshkhujaev ◽  
Kun Ho Lee ◽  
Kyu Yeong Choi ◽  
Jang Jae Lee ◽  
Goo-Rak Kwon ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
State Of The Art ◽  
Principal Component ◽  
Label Propagation ◽  
Support Vector ◽  
Brain Volumes

Alzheimer’s disease (AD) is one of the most common neurodegenerative illnesses (dementia) among the elderly. Recently, researchers have developed a new method for the instinctive analysis of AD based on machine learning and its subfield, deep learning. Recent state-of-the-art techniques consider multimodal diagnosis, which has been shown to achieve high accuracy compared to a unimodal prognosis. Furthermore, many studies have used structural magnetic resonance imaging (MRI) to measure brain volumes and the volume of subregions, as well as to search for diffuse changes in white/gray matter in the brain. In this study, T1-weighted structural MRI was used for the early classification of AD. MRI results in high-intensity visible features, making preprocessing and segmentation easy. To use this image modality, we acquired four types of datasets from each dataset’s server. In this work, we downloaded 326 subjects from the National Research Center for Dementia homepage, 123 subjects from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) homepage, 121 subjects from the Alzheimer’s Disease Repository Without Borders homepage, and 131 subjects from the National Alzheimer’s Coordinating Center homepage. In our experiment, we used the multiatlas label propagation with expectation–maximization-based refinement segmentation method. We segmented the images into 138 anatomical morphometry images (in which 40 features belonged to subcortical volumes and the remaining 98 features belonged to cortical thickness). The entire dataset was split into a 70 : 30 (training and testing) ratio before classifying the data. A principal component analysis was used for dimensionality reduction. Then, the support vector machine radial basis function classifier was used for classification between two groups—AD versus health control (HC) and early mild cognitive impairment (MCI) (EMCI) versus late MCI (LMCI). The proposed method performed very well for all four types of dataset. For instance, for the AD versus HC group, the classifier achieved an area under curve (AUC) of more than 89% for each dataset. For the EMCI versus LMCI group, the classifier achieved an AUC of more than 80% for every dataset. Moreover, we also calculated Cohen kappa and Jaccard index statistical values for all datasets to evaluate the classification reliability. Finally, we compared our results with those of recently published state-of-the-art methods.

scholarly journals Cognitive effects and acceptability of non-invasive brain stimulation on Alzheimer’s disease and mild cognitive impairment: a component network meta-analysis

2020 ◽  
pp. jnnp-2020-323870 ◽  
Author(s):  
Che-Sheng Chu ◽  
Cheng-Ta Li ◽  
Andre R. Brunoni ◽  
Fu-Chi Yang ◽  
Ping-Tao Tseng ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Brain Stimulation ◽  
Repetitive Transcranial Magnetic Stimulation ◽  
Cochrane Library ◽  
Separate Analysis ◽  
Cognitive Effects ◽  
Positive Effects

ObjectivesTo compare cognitive effects and acceptability of repetitive transcranial magnetic stimulation (rTMS) and transcranial direct current stimulation (tDCS) in patients with Alzheimer’s disease (AD) or mild cognitive impairment (MCI), and to determine whether cognitive training (CT) during rTMS or tDCS provides additional benefits.MethodsElectronic search of PubMed, Medline, Embase, the Cochrane Library and PsycINFO up to 5 March 2020. We enrolled double-blind, randomised controlled trials (RCTs). The primary outcomes were acceptability and pre–post treatment changes in general cognition measured by Mini-Mental State Examination, and the secondary outcomes were memory function, verbal fluency, working memory and executive function. Durability of cognitive benefits (1, 2 and ≥3 months) after brain stimulation was examined.ResultsWe included 27 RCTs (n=1070), and the treatment components included high-frequency rTMS (HFrTMS) and low-frequency rTMS, anodal tDCS (atDCS) and cathodal tDCS (ctDCS), CT, sham CT and sham brain stimulation. Risk of bias of evidence in each domain was low (range: 0%–11.1%). HFrTMS (1.08, 9, 0.35–1.80) and atDCS (0.56, 0.03–1.09) had short-term positive effects on general cognition. CT might be associated with negative effects on general cognition (−0.79, –2.06 to 0.48) during rTMS or tDCS. At 1-month follow-up, HFrTMS (1.65, 0.77–2.54) and ctDCS (2.57, 0.20–4.95) exhibited larger therapeutic responses. Separate analysis of populations with pure AD and MCI revealed positive effects only in individuals with AD. rTMS and tDCS were well tolerated.ConclusionsHFrTMS is more effective than atDCS for improving global cognition, and patients with AD may have better responses to rTMS and tDCS than MCI.

scholarly journals Urinary metabolic phenotyping for Alzheimer’s disease

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Natalja Kurbatova ◽  
Manik Garg ◽  
Luke Whiley ◽  
Elena Chekmeneva ◽  
Beatriz Jiménez ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Feature Reduction ◽  
Early Disease ◽  
Metabolic Phenotyping ◽  
Non Invasive ◽  
Disease States ◽  
Alzheimer’S Pathology

AbstractFinding early disease markers using non-invasive and widely available methods is essential to develop a successful therapy for Alzheimer’s Disease. Few studies to date have examined urine, the most readily available biofluid. Here we report the largest study to date using comprehensive metabolic phenotyping platforms (NMR spectroscopy and UHPLC-MS) to probe the urinary metabolome in-depth in people with Alzheimer’s Disease and Mild Cognitive Impairment. Feature reduction was performed using metabolomic Quantitative Trait Loci, resulting in the list of metabolites associated with the genetic variants. This approach helps accuracy in identification of disease states and provides a route to a plausible mechanistic link to pathological processes. Using these mQTLs we built a Random Forests model, which not only correctly discriminates between people with Alzheimer’s Disease and age-matched controls, but also between individuals with Mild Cognitive Impairment who were later diagnosed with Alzheimer’s Disease and those who were not. Further annotation of top-ranking metabolic features nominated by the trained model revealed the involvement of cholesterol-derived metabolites and small-molecules that were linked to Alzheimer’s pathology in previous studies.

scholarly journals Exercise priming with transcranial direct current stimulation: a study protocol for a randomized, parallel-design, sham-controlled trial in mild cognitive impairment and Alzheimer’s disease

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Celina S. Liu ◽  
Nathan Herrmann ◽  
Bing Xin Song ◽  
Joycelyn Ba ◽  
Damien Gallagher ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Aerobic Exercise ◽  
Direct Current ◽  
Transcranial Direct Current Stimulation ◽  
Cortical Excitability ◽  
Parallel Design ◽  
Non Invasive

Abstract Background Transcranial direct current stimulation (tDCS) is a non-invasive type of brain stimulation that uses electrical currents to modulate neuronal activity. A small number of studies have investigated the effects of tDCS on cognition in patients with Mild Cognitive Impairment (MCI) and Alzheimer’s disease (AD), and have demonstrated variable effects. Emerging evidence suggests that tDCS is most effective when applied to active brain circuits. Aerobic exercise is known to increase cortical excitability and improve brain network connectivity. Exercise may therefore be an effective, yet previously unexplored primer for tDCS to improve cognition in MCI and mild AD. Methods Participants with MCI or AD will be randomized to receive 10 sessions over 2 weeks of either exercise primed tDCS, exercise primed sham tDCS, or tDCS alone in a blinded, parallel-design trial. Those randomized to an exercise intervention will receive individualized 30-min aerobic exercise prescriptions to achieve a moderate-intensity dosage, equivalent to the ventilatory anaerobic threshold determined by cardiopulmonary assessment, to sufficiently increase cortical excitability. The tDCS protocol consists of 20 min sessions at 2 mA, 5 times per week for 2 weeks applied through 35 cm2 bitemporal electrodes. Our primary aim is to assess the efficacy of exercise primed tDCS for improving global cognition using the Montreal Cognitive Assessment (MoCA). Our secondary aims are to evaluate the efficacy of exercise primed tDCS for improving specific cognitive domains using various cognitive tests (n-back, Word Recall and Word Recognition Tasks from the Alzheimer’s Disease Assessment Scale-Cognitive subscale) and neuropsychiatric symptoms (Neuropsychiatric Inventory). We will also explore whether exercise primed tDCS is associated with an increase in markers of neurogenesis, oxidative stress and angiogenesis, and if changes in these markers are correlated with cognitive improvement. Discussion We describe a novel clinical trial to investigate the effects of exercise priming before tDCS in patients with MCI or mild AD. This proof-of-concept study may identify a previously unexplored, non-invasive, non-pharmacological combination intervention that improves cognitive symptoms in patients. Findings from this study may also identify potential mechanistic actions of tDCS in MCI and mild AD. Trial registration Clinicaltrials.gov, NCT03670615. Registered on September 13, 2018.

scholarly journals Olfactory Measures as Predictors of Conversion to Mild Cognitive Impairment and Alzheimer’s Disease

2021 ◽  
Vol 11 (11) ◽  
pp. 1391
Author(s):  
Paul Loyd Wheeler ◽  
Claire Murphy
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Roc Curve ◽  
Disease Risk ◽  
Characteristic Curve ◽  
Odor Identification ◽  
Non Invasive ◽  
Prodromal Alzheimer’S Disease

Background: Early biomarkers of prodromal Alzheimer’s disease (AD) are critical both to initiate interventions and to choose participants for clinical trials. Odor threshold, odor identification and odor familiarity are impaired in AD. Methods: We investigated the relative abilities of standard screening (MMSE) and olfactory measures to predict transitions from cognitively normal (CN) to mild cognitive impairment (MCI), from CN to AD, and MCI to AD. The archival sample of 497, from the UCSD ADRC, included participants who were CN, MCI, AD and converters to MCI or AD. Apoe ε4 status, a genetic risk factor, was available for 256 participants, 132 were ε4 carriers. A receiver operating characteristic curve (ROC) curve plots the trade-off between sensitivity and specificity. Area under the ROC curve (AUC) was used to determine diagnostic accuracy. Results: Different measures were better predictors at specific stages of disease risk; e.g., odor familiarity, odor identification and the combination showed higher predictive value for converting from MCI to AD in ε4 carriers than the MMSE. Combining odor familiarity and odor identification produced an AUC of 1.0 in ε4 carriers, MMSE alone was 0.58. Conclusions: Olfactory biomarkers show real promise as non-invasive indicators of prodromal AD. The results support the value of combining olfactory measures in assessment of risk for conversion to MCI and to AD.

Sign in / Sign up

Export Citation Format

Share Document