Cognitive impairment involves sustained deficits across several key domains: memory, executive function, attention, and behavioral regulation. The condition encompasses cognitive dysfunction linked to Alzheimer's disease, mild cognitive impairment, vascular cognitive impairment, and other forms of neurodegeneration. Existing pharmacotherapies frequently yield inconsistent clinical benefits, are often accompanied by side effects, and generally lack disease-modifying properties. These limitations have spurred increasing attention toward safe, repeatable non-pharmacological strategies. Non-invasive brain stimulation, a central non-pharmacological tool, can regulate excitability in targeted brain regions, shape network-level connectivity, and facilitate activity-dependent neuroplasticity. Evidence from multiple clinical settings supports its potential to improve cognitive outcomes. This review centers on major NIBS techniques: repetitive transcranial magnetic stimulation, transcranial electrical stimulation, gamma-frequency sensory stimulation, photobiomodulation, and transcranial ultrasound stimulation. We synthesize their underlying mechanisms, clinical applications, and supporting evidence, aiming to provide an evidence-based framework to guide standardized clinical implementation and future research design in this area.

Background:Early clinical manifestations of Alzheimer's disease (AD) include an apparent decline in memory and executive function. Executive function is closely related to activities of daily living (ADL) and is important for maintaining an independent, high-quality lifestyle. Objective:This study aimed to explore the executive control ability and neuromechanisms of AD patients through stop-signal task (SST) elicited event-related potentials (ERPs) and their relationship with ADL. Methods:Thirty-six patients with AD and 36 sex and age matched healthy controls (HCs) were recruited. Electroencephalography (EEG) data recorded during the SST was compared between groups, and SST-related indicators were determined to assess executive control ability in AD patients. The relationship between ADL and SST-related indicators was explored. We performed Receiver Operating Characteristic (ROC) analysis on SST- and EEG-related indices. Results:Differences in the following indices were found between the two groups: Go accuracy (P< 0.001), Go omissions (P< 0.001), Go errors (P< 0.001), Go error reaction time (RT) (P< 0.001), failed stop RT (P = 0.021), all accuracies (P = 0.005), mean amplitude of N300 (P = 0.043), peak amplitude of N300 (P = 0.043), and peak latency of N300 (P< 0.001). And Go accuracy (r = -0.603, P = 0.005) and all accuracy (r = -0.624, P = 0.003) in the AD group were negatively partially correlated with ADL. These SST- and EEG-related indicators had an Area Under the Curve of 0.771 and 0.831, both of which could be used to jointly diagnose AD (both P< 0.001). Conclusion:This study suggests that the worse the executive function of AD patients, the more serious the ADL impairment. AD patients have electrical abnormalities associated with executive control. Different SST- and EEG-related indicators can be used to diagnose AD. This provides a new avenue for further elucidation of the pathological mechanisms of AD.

Alzheimer’s disease (AD) is characterized by cognitive decline. Gamma-frequency (40 Hz) transcranial alternating current stimulation (tACS) may enhance cognition, although its efficacy and neural mechanisms remain unclear. This study evaluated whether 40-Hz tACS improves cognition in individuals with AD and explored the associated neural correlates using resting-state electroencephalography (rs-EEG) and plasma phosphorylated tau. In a randomized, double-blind, sham-controlled trial, 39 participants with AD received either 40-Hz tACS (n = 20) or sham stimulation (n = 19) targeting the left dorsolateral prefrontal cortex (2.0 mA, 30 min/day, 2 weeks). Cognitive and mood outcomes and rs-EEG spectral and connectivity measures were assessed. Compared with sham, 40-Hz tACS was associated with a trajectory-level signal favoring improved global cognition, reduced depressive symptoms, increased frontal–central theta power, enhanced theta band hippocampal–prefrontal connectivity, stronger low-gamma connectivity at the ROI level, and exploratory reductions in plasma p-tau217 and p-tau181. Two weeks of low-intensity 40-Hz tACS showed target engagement and a trajectory-level cognitive signal in patients with AD. Biomarker changes were exploratory and require confirmation. ClinicalTrials.gov NCT06565143 Date: 2024.08.19.

Background Growing evidence links periodontitis to Alzheimer's disease (AD), yet the specific links between periodontitis severity gradients and brain functional alterations remain poorly understood.Objective To investigate brain functional alterations quantified by functional connectivity density (FCD) and regional homogeneity (ReHo) across periodontitis severity gradients, include microbiota measures as explanatory variables, and assess correlations between these functional alterations and cognitive impairment.Methods Clinical periodontal data, subgingival plaque, cognitive tests, and brain MRI data were collected from all 89 participants, including community-recruited normal cognition (NC) and patients with amnestic mild cognitive impairment (aMCI) and AD from a hospital neurology department. According to periodontal examination, participants were categorized into mild, moderate, and severe groups. FCD and ReHo were compared among different periodontal condition groups and subgroups. Correlation analyses were conducted to explore the relationship among FCD, ReHo, periodontal indices, and cognition.Results With increasing severity of periodontitis, the FCD of bilateral middle frontal gyrus (MFG.R, MFG.L), right inferior frontal gyrus, triangular part (IFGtriang.R), and the ReHo of IFGtriang.R all decreased. These regions are commonly associated with executive control, working memory, and attention. These changes were more strongly correlated with overall periodontal inflammatory burden and cognitive performance than to the abundance of specific taxa in the subgingival plaque microbiota.Conclusions Periodontitis severity is associated with reduced prefrontal FCD/ReHo and cognitive decline, and these associations appear to be more strongly driven by overall periodontal inflammatory burden than by specific subgingival taxa.

Early recognition of Alzheimer’s disease (AD) is crucial for timely intervention and delaying disease progression. Electroencephalogram (EEG) technology provides a direct reflection of the brain’s dynamic activity. However, the relationship between potential EEG features and cognitive function in early-stage AD patients, as well as cerebrospinal fluid (CSF) pathological biomarkers, remains unclear. This study included 101 patients with mild cognitive impairment (MCI) and mild AD, alongside 69 healthy controls (HC) matched for gender, age, and educational attainment. Extracting EEG power spectral density (PSD) and microstates analysis features as training features for machine learning (ML), we employed five ML algorithms—Support Vector Machines (SVM), Logistic Regression (LR), Random Forests (RF), XGBoost, and LightGBM—for training and testing. Model performance was assessed using the area under the receiver operating characteristic curve (AUC). SHapley Additive exPlanations (SHAP) plots were employed to elucidate variable importance within the model, and sequential forward selection (SFS) was utilised to identify potential features. Correlation analysis and mediation analysis were conducted to investigate the relationships between EEG features, CSF pathological biomarkers, and cognitive function. The LR model demonstrated the highest average predictive performance in the training set (mean AUC = 0.859 ± 0.059). The model incorporating PSD and microstates features demonstrated optimal predictive performance in the test set (AUC = 0.949, 95

Background: Behavioral and psychological symptoms of dementia (BPSD) are common in Alzheimer's disease (AD), yet their mechanisms remain unclear. Objective: We aim to explore the possible neurophysiological mechanisms of BPSD using high temporal resolution electroencephalography (EEG) microstate technology, laying the foundation for clinical evaluation and subsequent treatment. Methods: We enrolled 52 AD patients (25 with BPSD, 27 without) and 29 age- and gender-matched healthy controls (HC). All participants underwent various neuropsychological assessments and resting-state EEG recordings. Resting-state EEG data were analyzed employing microstate analysis techniques, with a focus on four key microstate parameters: duration, occurrence, coverage, and transition probability. Inter-group comparisons were performed using post-hoc tests, with statistical significance determined through False Discovery Rate (FDR) correction. Furthermore, the correlations between the indicators and neuropsychological assessment scores were analyzed. Results: Compared to the HC and non-BPSD groups, the BPSD group showed an increase in the transition rate from microstate A to microstate C. Compared to the HC group, the BPSD group showed an extension in the duration of microstate A and a decrease in the frequency of microstate D. Compared to the HC group, the non-BPSD group showed prolonged durations (A, B, mean) and reduced occurrences (C, D, mean).The partial correlation analysis with years of education as a covariate showed that in the BPSD group, the duration of microstate A was correlated with the severity of the Neuropsychiatric Inventory (NPI) and the Hamilton Anxiety Scale (HAMA). Conclusions: AD with and without BPSD exhibits different altered brain dynamics.

Microglia are brain-resident macrophages that play a crucial role in synapse pruning during the development and progression of various neuropsychiatric disorders, including autism spectrum disorder (ASD) and Alzheimer’s disease (AD). Mechanistically, CD47 protein acts as a potent ‘do not eat me’ signal, protecting synapses from phagocytosis by microglia. However, the functional role of the upregulated neuronal CD47 signal under both physiological and pathological conditions remains unclear. We utilized an adeno-associated virus gene expression system to induce neuron-specific overexpression of CD47 in wild-type and 5xFAD mice, assessing its effects on microglial synaptic phagocytosis and mouse behaviors. Our results indicate that neuronal CD47 induces ASD-like behaviors and synaptic pruning defects, while promoting behavioral disinhibition and improving memory in wild-type mice. Single-nucleus RNA sequencing was employed to profile gene expression patterns in subpopulations of neurons and microglia. Notably, neuronal CD47 enhances synaptic pathways in neurons and particularly shifts microglial subpopulations from a disease-associated state to a homeostatic state. Additionally, neuronal CD47 reduces excessive microglial synaptic phagocytosis induced by Aβ pathology in 5xFAD mice. Our study provides evidence that neuronal CD47 overexpression results in synaptic pruning defects and is involved in the pathogenesis of ASD, while also playing a beneficial role in mitigating excessive synaptic loss in Alzheimer’s disease.

AIM:To explore if periodontitis and subgingival plaque microbiota have a relation with brain regional grey matter volume (rGMV) and their association with impaired cognition. MATERIAL AND METHODS:Clinical periodontal data, subgingival plaque, cognitive test and brain MRI data were collected from 137 participants. rGMVs were compared among groups and subgroups with different periodontal conditions. Correlation analyses and multivariate linear regression were conducted to explore the relationship betweem rGMV, clinical periodontal indices, subgingival plaque microbiota and cognition. The random forest method was used to find the best model for cognition status prediction. RESULTS:There were significant differences in rGMV of the left calcarine fissure and the surrounding cortex, bilateral lingual, left inferior parietal marginal, left superior parietal, left lenticular nucleus pallidum, left posterior orbital gyrus, left cuneus and left middle frontal gyrus of orbital part among groups with different periodontal conditions. In whole and subgroup analyses, the major trends were the same: patients with severe periodontitis had smaller rGMV. The clinical indicators of periodontitis and the composition of the subgingival microbiota were associated with rGMV and impaired cognition. Further, cognitive prediction model accuracy was improved by adding periodontitis-related information. CONCLUSIONS:Subgingival plaque microbiota and periodontitis were associated with rGMV and cognitive decline.

BackgroundSex differences in Alzheimer's disease (AD) progression offer insights into pathogenesis and clinical management. White matter (WM) amplitude of low-frequency fluctuation (ALFF), reflecting neural activity, represents a potential disease biomarker.ObjectiveTo explore whether there are sex differences in regional WM ALFF among AD patients, amnestic mild cognitive impairment (aMCI) patients, and healthy controls (HCs), how it is related to cognitive performance, and whether it can be used for disease classification.MethodsResting-state functional magnetic resonance images and cognitive assessments were obtained from 85 AD (36 female), 52 aMCI (23 female), and 78 HCs (43 female). Two-way ANOVA examined group × sex interactions for regional WM ALFF and cognitive scores. WM ALFF-cognition correlations and support vector machine diagnostic accuracy were evaluated.ResultsSex × group interaction effects on WM ALFF were detected in the right superior longitudinal fasciculus (F = 20.08, pFDR_corrected < 0.001), left superior longitudinal fasciculus (F = 5.45, pGRF_corrected < 0.001) and right inferior longitudinal fasciculus (F = 6.00, pGRF_corrected = 0.001). These WM ALFF values positively correlated with different cognitive performance between sexes. The support vector machine learning best differentiated aMCI from AD in the full cohort and males (accuracy = 75%), and HCs from aMCI in females (accuracy = 93%).ConclusionsSex differences in regional WM ALFF during AD progression are associated with cognitive performance and can be utilized for disease classification.

Background Alzheimer's disease (AD) is strongly associated with slowly progressive hippocampal atrophy. Elucidating the relationships between local morphometric changes and disease status for early diagnosis could be aided by machine learning algorithms trained on neuroimaging datasets. Objective This study intended to propose machine learning models for the accurate identification and cognitive function prediction across the AD severity spectrum based on structural magnetic resonance imaging (sMRI) of the bilateral hippocampi. Methods The high-resolution sMRI data of 120 AD dementia patients, 232 amnestic mild cognitive impairment (aMCI) patients, and 206 healthy controls (HCs) were included from the Alzheimer's Disease Neuroimaging Initiative (ADNI). The classification capacity and cognitive predict ability of hippocampal volume was evaluated by multiple pattern analysis using the support vector machine (SVM) and relevance vector regression (RVR) application of the Pattern Recognition for Neuroimaging Toolbox, separately. For validation, the analyses were performed using a biomarker-based regrouping method and another independent local dataset. Results The SVM application produced a total accuracy of 94.17%, 80.85%, and 70.74% and area under receiver operating characteristic curves of 0.97, 0.87, and 0.72 between HC versus AD dementia, HC versus aMCI, and aMCI versus AD dementia classification, respectively. The RVR application significantly predicted the baseline and mean cognitive function at three years of follow-up. Qualitatively consistent results were obtained using different regrouping method and the local dataset. Conclusions The machine learning methods based on the bilateral hippocampi distinguished across the AD severity spectrum and predicted the baseline and the longitudinal cognitive function with greater accuracy.

BACKGROUND:Cerebral specialization and interhemispheric cooperation are two vital features of the human brain. Their dysfunction may be associated with disease progression in patients with Alzheimer's disease (AD), which is featured as progressive cognitive degeneration and asymmetric neuropathology. OBJECTIVE:This study aimed to examine and define two inherent properties of hemispheric function in patients with AD by utilizing resting-state functional magnetic resonance imaging (rs-fMRI). METHODS:Sixty-four clinically diagnosed AD patients and 52 age- and sex-matched cognitively normal subjects were recruited and underwent MRI and clinical evaluation. We calculated and compared brain specialization (autonomy index, AI) and interhemispheric cooperation (connectivity between functionally homotopic voxels, CFH). RESULTS:In comparison to healthy controls, patients with AD exhibited enhanced AI in the left middle occipital gyrus. This increase in specialization can be attributed to reduced functional connectivity in the contralateral region, such as the right temporal lobe. The CFH of the bilateral precuneus and prefrontal areas was significantly decreased in AD patients compared to controls. Imaging-cognitive correlation analysis indicated that the CFH of the right prefrontal cortex was marginally positively related to the Montreal Cognitive Assessment score in patients and the Auditory Verbal Learning Test score. Moreover, taking abnormal AI and CFH values as features, support vector machine-based classification achieved good accuracy, sensitivity, specificity, and area under the curve by leave-one-out cross-validation. CONCLUSION:This study suggests that individuals with AD have abnormal cerebral specialization and interhemispheric cooperation. This provides new insights for further elucidation of the pathological mechanisms of AD.

Background Previous studies have demonstrated that excitatory repetitive transcranial magnetic stimulation (rTMS) can improve the cognitive function of patients with Alzheimer’s disease (AD). Intermittent theta burst stimulation (iTBS) is a novel excitatory rTMS protocol for brain activity stimulation with the ability to induce long-term potentiation-like plasticity and represents a promising treatment for AD. However, the long-term effects of iTBS on cognitive decline and brain structure in patients with AD are unknown.Aims We aimed to explore whether repeating accelerated iTBS every three months could slow down the cognitive decline in patients with AD.Methods In this randomised, assessor-blinded, controlled trial, iTBS was administered to the left dorsolateral prefrontal cortex (DLPFC) of 42 patients with AD for 14 days every 13 weeks. Measurements included the Montreal Cognitive Assessment (MoCA), a comprehensive neuropsychological battery, and the grey matter volume (GMV) of the hippocampus. Patients were evaluated at baseline and after follow-up. The longitudinal pipeline of the Computational Anatomy Toolbox for SPM was used to detect significant treatment-related changes over time.Results The iTBS group maintained MoCA scores relative to the control group (t=3.26, p=0.013) and reduced hippocampal atrophy, which was significantly correlated with global degeneration scale changes. The baseline Mini-Mental State Examination (MMSE) score, apolipoprotein E genotype and Clinical Dementia Rating were indicative of MoCA scores at follow-up. Moreover, the GMV of the left (t=0.08, p=0.996) and right (t=0.19, p=0.977) hippocampus were maintained in the active group but significantly declined in the control group (left: t=4.13, p<0.001; right: t=5.31, p<0.001). GMV change in the left (r=0.35, p=0.023) and right (r=0.36, p=0.021) hippocampus across the intervention positively correlated with MoCA changes; left hippocampal GMV change was negatively correlated with global degeneration scale (r=−0.32, p=0.041) changes.Conclusions DLPFC-iTBS may be a feasible and easy-to-implement non-pharmacological intervention to slow down the progressive decline of overall cognition and quality of life in patients with AD, providing a new AD treatment option.Trial registration number NCT04754152.

Electroencephalography (EEG) microstates are used to study cognitive processes and brain disease-related changes. However, dysfunctional patterns of microstate dynamics in Alzheimer's disease (AD) remain uncertain. To investigate microstate changes in AD using EEG and assess their association with cognitive function and pathological changes in cerebrospinal fluid (CSF). We enrolled 56 patients with AD and 38 age- and sex-matched healthy controls (HC). All participants underwent various neuropsychological assessments and resting-state EEG recordings. Patients with AD also underwent CSF examinations to assess biomarkers related to the disease. Stepwise regression was used to analyze the relationship between changes in microstate patterns and CSF biomarkers. Receiver operating characteristics analysis was used to assess the potential of these microstate patterns as diagnostic predictors for AD. Compared with HC, patients with AD exhibited longer durations of microstates C and D, along with a decreased occurrence of microstate B. These microstate pattern changes were associated with Stroop Color Word Test and Activities of Daily Living scale scores (all P < 0.05). Mean duration, occurrences of microstate B, and mean occurrence were correlated with CSF Aβ 1–42 levels, while duration of microstate C was correlated with CSF Aβ 1–40 levels in AD (all P < 0.05). EEG microstates are used to predict AD classification with moderate accuracy. Changes in EEG microstate patterns in patients with AD correlate with cognition and disease severity, relate to Aβ deposition, and may be useful predictors for disease classification.

Background: Alzheimer’s disease (AD) is a neurodegenerative disease characterized by brain network dysfunction. Few studies have investigated whether the functional connections between executive control networks (ECN) and other brain regions can predict the therapeutic effect of repetitive transcranial magnetic stimulation (rTMS). Objective: The purpose of this study is to examine the relationship between the functional connectivity (FC) within ECN networks and the efficacy of rTMS. Methods: We recruited AD patients for rTMS treatment. We established an ECN using baseline period fMRI data and conducted an analysis of the ECN’s FC throughout the brain. Concurrently, the support vector regression (SVR) method was employed to project post-rTMS cognitive scores, utilizing the connectional attributes of the ECN as predictive markers. Results: The average age of the patients was 66.86±8.44 years, with 8 males and 13 females. Significant improvement on most cognitive measures. We use ECN connectivity and brain region functions in baseline patients as features for SVR model training and fitting. The SVR model could demonstrate significant predictability for changes in Montreal Cognitive Assessment scores among AD patients after rTMS treatment. The brain regions that contributed most to the prediction of the model (the top 10% of weights) were located in the medial temporal lobe, middle temporal gyrus, frontal lobe, parietal lobe and occipital lobe. Conclusions: The stronger the antagonism between ECN and parieto-occipital lobe function, the better the prediction of cognitive improvement; the stronger the synergy between ECN and fronto-temporal lobe function, the better the prediction of cognitive improvement.

Alzheimer's disease (AD) is a neurodegenerative disease characterized by cognitive decline. Sex differences in the progression of AD exist, but the neural mechanisms are not well understood. The purpose of the current study was to explore sex differences in brain functional connectivity (FC) at different stages of AD and their predictive ability on Montreal Cognitive Assessment (MoCA) scores using connectome-based predictive modeling (CPM). Resting-state functional magnetic resonance imaging was collected from 81 AD patients (44 females), 78 amnestic mild cognitive impairment patients (44 females), and 92 healthy controls (50 females). The FC analysis was conducted and the interaction effect between sex and group was investigated using two-factor variance analysis. The CPM was used to predict MoCA scores. There were sex-by-group interaction effects on FC between the left dorsolateral superior frontal gyrus and left middle temporal gyrus, left precuneus and right calcarine fissure surrounding cortex, left precuneus and left middle occipital gyrus, left middle temporal gyrus and left precentral gyrus, and between the left middle temporal gyrus and right cuneus. In the CPM, the positive network predictive model significantly predicted MoCA scores in both males and females. There were significant sex-by-group interaction effects on FC between the left precuneus and left middle occipital gyrus, and between the left middle temporal gyrus and right cuneus could predict MoCA scores in female patients. Our results suggest that there are sex differences in FC at different stages of AD. The sex-specific FC can further predict MoCA scores at individual level. Functional connectivity with sex specificity predicts cognitive scores.image

OBJECTIVE:Formal education and other cognitive challenges influence brain structure and improve function. It is believed that cognitive activities create a cognitive reserve (CR) that can slow the decline due to aging and neurodegenerative diseases. This study investigated alterations of regional cerebral blood flow (rCBF) associated with high and low CR in different stages of Alzheimer's disease (AD) and examined whether rCBF alteration mediates the relationship between education and cognitive performance.METHODS:Patients with AD or amnestic mild cognitive impairment (aMCI) and healthy controls were divided into low cognitive reserve (LCR) and high cognitive reserve (HCR) subgroups according to median of education years (≤ 9 vs. > 9 years). The final study population included 89 AD patients (67 LCR, 22 HCR), 74 aMCI patients (44 LCR, 30 HCR), and 66 healthy controls (29 LCR, 37 HCR). All subjects were examined by arterial spin labeling magnetic resonance imaging and a neurocognitive test battery. rCBF was compared among groups by two-way analysis of variance. Mediation analyses were used to explore the relationships among education, rCBF, and cognitive test scores.RESULTS:There were significant interaction effects of disease state (AD, aMCI, HC) and education level (LCR, HCR) on CBF in right hippocampus, posterior cingulate cortex, and right inferior parietal cortex (R_IPC). Education regulated episodic memory score by influencing right hippocampal CBF in HC_HCR and aMCI_HCR subgroups.CONCLUSION:Our results indicate that the protective effect of education against cognitive dysfunction in early-stage AD is mediated at least partially by altered CBF in right hippocampus.

IntroductionPathological changes in Alzheimer’s disease can cause retina and optic nerve degeneration. The retinal changes are correlated with cognitive function. This study aimed to explore the relationship of retinal differences with neuroimaging in patients with Alzheimer’s disease, analyze the association of cognitive function with retinal structure and vascular density, and identify potential additional biomarkers for early diagnosis of Alzheimer’s disease.MethodWe performed magnetic resonance imaging (MRI) scans and neuropsychological assessments in 28 patients with mild Alzheimer’s disease and 28 healthy controls. Retinal structure and vascular density were evaluated by optical coherence tomography angiography (OCTA). Furthermore, we analyzed the correlation between neuroimaging and OCTA parameters in patients with mild Alzheimer’s disease with adjustment for age, gender, years of education, and hypertension.ResultsIn patients with mild Alzheimer’s disease, OCTA-detected retinal parameters were not significantly correlated with MRI-detected neuroimaging parameters after Bonferroni correction for multiple testing. Under multivariable analysis controlled for age, gender, years of education, and hypertension, the S-Hemi (0–3) sector of macular thickness was significantly associated with Mini-cog (β = 0.583, P = 0.002) with Bonferroni-corrected threshold at P < 0.003.ConclusionOur findings suggested decreased macular thickness might be associated with cognitive function in mild AD patients. However, the differences in retinal parameters didn’t correspond to MRI-detected parameters in this study. Whether OCTA can be used as a new detection method mirroring MRI for evaluating the effect of neuronal degeneration in patients with mild Alzheimer’s disease still needs to be investigated by more rigorous and larger studies in the future.

Background: Abnormalities in white matter (WM) may be a crucial physiologic feature of Alzheimer's disease (AD). However, neuroimaging's ability to visualize the underlying functional degradation of the WM region in AD is unclear. Objective: This study aimed to explore the differences in amplitude of low-frequency fluctuation (ALFF) and fractional ALFF (fALFF) in the WM region of patients with AD and healthy controls (HC) and to investigate further whether these values can provide supplementary information for diagnosing AD. Methods: Forty-eight patients with AD and 46 age-matched HC were enrolled and underwent resting-state functional magnetic resonance imaging and a neuropsychological battery assessment. We analyzed the differences in WM activity between the two groups and further explored the correlation between WM activity in the different regions and cognitive function in the AD group. Finally, a machine learning algorithm was adopted to construct a classifier in detecting the clinical classification ability of the values of ALFF/ALFF in the WM. Results: Compared with HCs, patients with AD had lower WM activity in the right anterior thalamic radiation, left frontal aslant tract, and left forceps minor, which are all positively related to global cognitive function, memory, and attention function (all p < 0.05). Based on the combined WM ALFF and fALFF characteristics in the different regions, individuals not previously assessed were classified with moderate accuracy (75%), sensitivity (71%), specificity (79%), and area under the receiver operating characteristic curve (85%). Conclusion: Our results suggest that WM activity is reduced in AD and can be used for disease classification.

目的:利用磁共振3D伪连续动脉自旋标记(3D-pcASL)成像,探讨阿尔茨海默病(AD)患者脑血流灌注(CBF)改变是否存在性别差异,及其与认知损害的相关性.方法:招募74例AD患者(男33例、女41例)、74例AD伴遗忘型轻度认知障碍(aMCI)患者(男29例、女45例)及74例健康志愿者(对照组,包括男31例、女43例),所有被试行3D-pcASL成像,获得脑血流量(CBF)图,使用双因素协方差分析获得性别与组别(AD、aMCI及H C组)存在交互作用的脑区,并将这些脑区的CBF值与简易精神状态检查量表(MMSE)及蒙特利尔认知功能评估量表(MoCA)得分进行偏相关分析.结果:对照组和aMCI组中男性组与女性组之间MMSE和MoCA得分的差异均无统计学意义(P>0.05),而AD组中女性组的MMSE和MoCA得分显著低于男性组(P<0.05).对CBF值的双因素协方差分析结果显示左侧顶下缘角回、缘上回、颞上回及颞中回存在性别与组别(AD、aMCI及H C组)的交互作用,女性AD组中上述脑区的CBF值与MoCA得分均呈显著正相关(r=0.378,P=0.019;r=0.377,P=0.020;r=0.347,P=0.033;r=0.433,P=0.007),而男性AD组中上述脑区的CBF值与MoCA得分均无显著相关性(P>0.05).结论:在AD进展过程中,男性和女性的脑血流灌注改变存在性别差异,且与认知障碍相关,这提示我们在进行AD进展研究时应充分考虑性别差异,以开发更有效的生物标志物.

Background: Deficits in associative memory (AM) are the earliest and most prominent feature of Alzheimer's disease (AD) and demonstrate a clear cause of distress for patients and their families. Objective: The present study aimed to determine AM enhancements following accelerated intermittent theta-burst stimulation (iTBS) in patients with AD. Methods: In a randomized, double-blind, sham-controlled design, iTBS was administered to the left dorsolateral prefrontal cortex (DLPFC) of patients with AD for 14 days. Measurements included AM (primary outcome) and a comprehensive neuropsychological battery. Patients were evaluated at baseline, following the intervention (week 2), and 8 weeks after treatment cessation (week 10). Results: Sixty patients with AD were initially enrolled; 47 completed the trial. The active group displayed greater AM improvements compared with the sham group at week 2 (P = 0.003), which was sustained at week 10. Furthermore, higher Mini-Mental State Examination (MMSE) scores at baseline were associated with greater AM improvements at weeks 2 and 10. For the independent iTBS group, this correlation predicted improvements in AM (P < 0.001) and identified treatment responders with 92% accuracy. Most of the neuropsychological tests were markedly improved in the active group. In particular, the Montreal Cognitive Assessment and MMSE in the active group increased by 2.8 and 2.3 points, respectively, at week 2, while there was no marked change in the sham group. Conclusion: In the present study, accelerated iTBS of the DLPFC demonstrated an effective and well-tolerated complementary treatment for patients with AD, especially for individuals with relatively high MMSE scores. (C) 2021 Published by Elsevier Inc.