Amnesic Mild Cognitive Impairment Research Articles

Subjective organization in the episodic memory of individuals with Parkinson's disease associated with mild cognitive impairment.

Word clustering (i.e., the ability to reproduce the same word pairs in consecutive recall trials of an unrelated word list) has been extensively investigated as a proxy of subjective organization (SO) of memorandum. In healthy subjects and in groups of brain-damaged patients, the rate of SO generally predicts accuracy of word list recall. This study aimed at evaluating SO in the performance of patients with Parkinson's disease (PD) on a word list recall task in order to investigate the basic mechanisms of episodic memory impairment that are frequently observed in these patients. For this purpose, 56 PD patients, who were stratified according to the presence and quality of mild cognitive impairment (MCI), and a group of healthy controls (HCs) were administered a word list task and an extensive battery of neuropsychological tests. Results showed that recall accuracy on the word list task progressively decreased passing from HC to PD patients without cognitive impairment, to patients with single-domain dysexecutive MCI and to patients with multiple-domain dysexecutive and amnesic MCI. Conversely, only the latter PD group showed a lower SO score than that achieved by the other groups. In the overall PD group, correlational and regression analyses demonstrated that SO scores and a composite score of executive functions were not reciprocally related, but both provided an independent and significant contribution to the prediction of word list recall accuracy. These data are discussed in terms of the contribution of executive functions and hippocampal storage processes to the onset of memory impairment in PD.

Verbal and spatial memory spans in mild cognitive impairment.

Working memory (WM) for verbal and visual material may be affected early in individuals with mild cognitive impairment (MCI). Verbal and visuospatial span tasks, that is neuropsychological procedures commonly used for the clinical assessment of WM, have been scarcely investigated in these patients. Therefore, this study was aimed at evaluating whether performance on tests of verbal and visual-spatial span (which rely to different extents on distinct components of the WM system) is differently sensitive to the presence of MCI and, in particular, of a preclinical AD condition in patients with MCI. 99 patients with amnesic MCI were given the Digit Span Forward (DSF) and Digit Span Backward (DSB) tests and the Corsi span task (CS) at baseline and were followed up for two years. 32 MCI patients converted to Alzheimer's disease (MCIc), but 67 patients did not deteriorate to meet the criteria for AD (MCIs). Results showed that although performance on DSF did not differ between groups, performance on DSB and CS and ratio indexes indicative of a performance decline passing from DSF to DSB and from DSF to CS significantly discriminated between a group of matched healthy controls and the overall group of MCI patients. Moreover, the ratio indexes significantly discriminated between MCIc and MCIs individuals. These data are consistent with the hypothesis that individuals with MCI, particularly those destined to convert to AD, are affected by reduced central executive resources even though the phonological loop is still functioning normally.

Synergistic Association between Plasma Aβ1-42 and p-tau in Alzheimer's Disease but Not in Parkinson's Disease or Frontotemporal Dementia.

Beta-amyloid (Aβ1–42) triggers the phosphorylation of tau protein in Alzheimer’s disease (AD), but the relationship between phosphorylated tau (p-tau) and Aβ1–42 in the blood is not elucidated. We investigated the association in individuals with AD (n = 62, including amnesic mild cognitive impairment and dementia), Parkinson’s disease (n = 30), frontotemporal dementia (n = 25), and cognitively unimpaired controls (n = 41) using immunomagnetic reduction assays to measure plasma Aβ1–42 and p-tau181 concentrations. Correlation and regression analyses were performed to examine the relation between plasma levels, demographic factors, and clinical severity. Both plasma Aβ1–42 and p-tau concentrations were significantly higher in AD and frontotemporal dementia than in the controls and Parkinson’s disease. A significant positive association was found between plasma p-tau and Aβ1–42 in controls (r = 0.579, P < 0.001) and AD (r = 0.699, P < 0.001) but not in frontotemporal dementia or Parkinson’s disease. Plasma p-tau was significantly associated with clinical severity in the AD in terms of scores of clinical dementia rating (r = 0.288, P = 0.025) and mini-mental state examination (r = −0.253, P = 0.049). Regression analysis showed that plasma Aβ1–42 levels explain approximately 47.7% of the plasma p-tau levels in the AD after controlling age, gender, and clinical severity. While in non-AD participants, the clinical dementia rating explained about 47.5% of the plasma p-tau levels. The disease-specific association between plasma Aβ1–42 and p-tau levels in AD implies a possible synergic effect in mechanisms involving these two pathological proteins’ genesis.

The Smart Aging Platform for Assessing Early Phases of Cognitive Impairment in Patients With Neurodegenerative Diseases.

Background: Smart Aging is a serious game (SG) platform that generates a 3D virtual reality environment in which users perform a set of screening tasks designed to allow evaluation of global cognition. Each task replicates activities of daily living performed in a familiar environment. The main goal of the present study was to ascertain whether Smart Aging could differentiate between different types and levels of cognitive impairment in patients with neurodegenerative disease.Methods: Ninety-one subjects (mean age = 70.29 ± 7.70 years)—healthy older adults (HCs, n = 23), patients with single-domain amnesic mild cognitive impairment (aMCI, n = 23), patients with single-domain executive Parkinson's disease MCI (PD-MCI, n = 20), and patients with mild Alzheimer's disease (mild AD, n = 25)—were enrolled in the study. All participants underwent cognitive evaluations performed using both traditional neuropsychological assessment tools, including the Mini-Mental State Examination (MMSE), Montreal Overall Cognitive Assessment (MoCA), and the Smart Aging platform. We analyzed global scores on Smart Aging indices (i.e., accuracy, time, distance) as well as the Smart Aging total score, looking for differences between the four groups.Results: The findings revealed significant between-group differences in all the Smart Aging indices: accuracy (p < 0.001), time (p < 0.001), distance (p < 0.001), and total Smart Aging score (p < 0.001). The HCs outperformed the mild AD, aMCI, and PD-MCI patients in terms of accuracy, time, distance, and Smart Aging total score. In addition, the mild AD group was outperformed both by the HCs and by the aMCI and PD-MCI patients on accuracy and distance. No significant differences were found between aMCI and PD-MCI patients. Finally, the Smart Aging scores significantly correlated with the results of the neuropsychological assessments used.Conclusion: These findings, although preliminary due to the small sample size, suggest the validity of Smart Aging as a screening tool for the detection of cognitive impairment in patients with neurodegenerative diseases.

Brain Resources: How Semantic Cueing Works in Mild Cognitive Impairment due to Alzheimer's Disease (MCI-AD).

Semantic cues in the Free and Cued Selective Reminding Test (FCRST) play a key role in the neuropsychological diagnosis of Amnesic Mild Cognitive Impairment due to Alzheimer’s Disease (MCI-AD); however, the neural bases of their impact of recall abilities are only partially understood. Here, we thus decided to investigate the relationships between brain metabolism and the FCSRT Index of Sensitivity of Cueing (ISC) in patients with MCI-AD and in healthy controls (HC). Materials: Thirty MCI-AD patients (age: 74.7 ± 5.7 years; education: 9.6 ± 4.6 years, MMSE score: 24.8 ± 3.3, 23 females) and seventeen HC (age: 66.5 ± 11.1 years; education: 11.53 ± 4.2 years, MMSE score: 28.4 ± 1.14, 10 females) who underwent neuropsychological evaluation and brain F-18 fluorodeoxyglucose Positron Emission Tomography (FDG-PET) were included in the study. Results: ISC was able to differentiate HC from MCI-AD subjects as shown by a ROC analysis (AUC of 0.978, effect size Hedges’s g = 2.89). MCI-AD subjects showed significant hypometabolism in posterior cortices, including bilateral inferior Parietal Lobule and Precuneus and Middle Temporal gyrus in the left hemisphere (VOI-1) compared to HC. ISC was positively correlated with brain metabolism in a single cluster (VOI-2) spanning the left prefrontal cortex (superior frontal gyrus) and anterior cingulate cortex (ACC) in the patient group (R2 = 0.526, p < 0.001), but not in HC. Mean uptake values of VOI-2 did not differ between HC and MCI-AD. The structural connectivity analysis showed that VOI-2 is connected with the temporal pole, the cingulate gyrus and the posterior temporal cortices in the left hemisphere. Conclusion: In MCI-AD, the relative preservation of frontal cortex metabolic levels and their correlation with the ISC suggest that the left frontal cortices play a significant role in maintaining a relatively good memory performance despite the presence of posterior hypometabolism in MCI-AD.

Towards Effective Classification of aMCI Based on Resting‐State Multiscale Brain Features and Machine Learning Approaches

Smart healthcare has undergone new opportunities and challenges with the arrival of the Industry 4.0 era. The intelligent imaging diagnosis system is a staple part of smart healthcare, helping doctors make clinical decisions. Nevertheless, intelligent diagnosis analysis is still confronted with the issue that it is challenging to extract effective features from the limited and high‐dimensional data, particularly in resting‐state data of amnesic mild cognitive impairment (aMCI). Furthermore, the intelligent imaging diagnosis system for aMCI is conductive to make timely predicting groups that may convert to Alzheimer’s disease (AD). To improve the system’s detection performance and reduce its data redundancy, we first develop an adaptive structure feature generation strategy (ASFGS) based on the Laplacian matrix and sparse autoencoder to obtain the structural features of brain functional network (BFN). Concurrently, we present a multiscale local feature detection strategy (MLFDS) to overcome the low utilization of local features of BFN. And finally, multiscale features, including structural features and multiscale local features, are fused by concatenation method to further improve the detection performance of aMCI system. Support vector machine based on radial basis function (RBF‐SVM) for small data learning is adopted to evaluate the effectiveness of the proposed features. Besides, we employ leave‐one‐out cross‐validation strategy to avoid the overfitting problem of classifier training process. The experiment results elucidate that the accuracy (ACC) and the area under the curve (AUC) in this work provide 86.57% and 86.36%, respectively, which outperforms the traditional methods and offers new insights for accuracy requirements of the aMCI system.

Episodic Memory–Related Imaging Features as Valuable Biomarkers for the Diagnosis of Alzheimer’s Disease: A Multicenter Study Based on Machine Learning

BackgroundIndividualized and reliable biomarkers are crucial for diagnosing Alzheimer’s disease (AD). However, lack of accessibility and neurobiological correlation are the main obstacles to their clinical application. Machine learning algorithms can effectively identify personalized biomarkers based on the prominent symptoms of AD. MethodsEpisodic memory–related magnetic resonance imaging (MRI) features of 143 patients with amnesic mild cognitive impairment (MCI) were identified using a multivariate relevance vector regression algorithm. The support vector machine classification model was constructed using these MRI features and verified in 2 independent datasets (N = 994). The neurobiological basis was also investigated based on cognitive assessments, neuropathologic biomarkers of cerebrospinal fluid, and positron emission tomography images of amyloid-β plaques. ResultsThe combination of gray matter volume and amplitude of low-frequency fluctuation MRI features accurately predicted episodic memory impairment in individual patients with amnesic MCI (r = 0.638) when measured using an episodic memory assessment panel. The MRI features that contributed to episodic memory prediction were primarily distributed across the default mode network and limbic network. The classification model based on these features distinguished patients with AD from normal control subjects with more than 86% accuracy. Furthermore, most identified episodic memory–related regions showed significantly different amyloid-β positron emission tomography measurements among the AD, MCI, and normal control groups. Moreover, the classification outputs significantly correlated with cognitive assessment scores and cerebrospinal fluid pathological biomarkers' levels in the MCI and AD groups. ConclusionsNeuroimaging features can reflect individual episodic memory function and serve as potential diagnostic biomarkers of AD.

Prevalence and Risk of Mild Cognitive Impairment in Low and Middle-Income Countries: A Systematic Review.

Mild cognitive impairment (MCI) is a cognitive state associated with increased risk of dementia. Little research on MCI exists from low-and middle-income countries (LMICs), despite high prevalence of dementia in these settings. This systematic review aimed to review epidemiological reports to determine the prevalence of MCI and its associated risk factors in LMICs. Medline, Embase, and PsycINFO were searched from inception until November 2019. Eligible articles reported on MCI in population or community-based studies from LMICs and were included as long as MCI was clearly defined. 5,568 articles were screened, and 78 retained. In total, n = 23 different LMICs were represented; mostly from China (n = 55 studies). Few studies were from countries defined as lower-middle income (n = 14), low income (n = 4), or from population representative samples (n = 4). There was large heterogeneity in how MCI was diagnosed; with Petersen criteria the most commonly applied (n = 26). Prevalence of amnesic MCI (aMCI) (Petersen criteria) ranged from 0.6%to 22.3%. Similar variability existed across studies using the International Working Group Criteria for aMCI (range 4.5%to 18.3%) and all-MCI (range 6.1%to 30.4%). Risk of MCI was associated with demographic (e.g., age), health (e.g., cardio-metabolic disease), and lifestyle (e.g., social isolation, smoking, diet and physical activity) factors. Outside of China, few MCI studies have been conducted in LMIC settings. There is an urgent need for population representative epidemiological studies to determine MCI prevalence in LMICs. MCI diagnostic methodology also needs to be standardized. This will allow for cross-study comparison and future resource planning.

The Destiny of Multiple Domain Amnesic Mild Cognitive Impairment: Effect of Alternative Neuropsychological Definitions and Their Adjunctive Role in Respect of Memory Impairment.

Mild cognitive impairment is the main risk factor of dementia. Previous evidence has claimed that subjects with memory disturbances associated with impairment of other cognitive domains (multiple domain amnesic MCI) are at the highest risk of developing dementia. To date, a shared definition of amnesic MCI multiple domain (aMCI-MD) is still lacking. 163 subjects with aMCI were enrolled and followed-up for 2 years. They underwent a baseline comprehensive neuropsychological battery. The cut-off point for each test was set at 1, 1.5, and 2 SD below the mean obtained in normative studies; aMCI-MD was defined as the occurrence of abnormal scores on at least one, two, or three tests not assessing memory. The Episodic Memory Score (EMS), that measures the severity of memory impairment, was determined. Logistic regressionand Cox's proportional hazard risk models were carried out. The adjunctive effect of the definitions of aMCI-MD on the severity of memory impairment was assessed. Fifty-four subjects progressed to dementia. Only restrictive definitions of aMCI-MD (at least three tests below 1.5 SD; at least two tests below 2 SD) predicted conversion to dementia in both logistic regression and survival analysis. None of the conditions showed a significant adjunctive effect on the EMS. The predictive effect of impairment in tests assessing cognitive domains other than memory depends on its psychometric definition. The use of a restrictive definition would be of some usefulness, but the adjunctive effect of such a definition on an integrated analysis of memory impairment may be questionable.

Semantic impairment in very early Alzheimer disease

AbstractBackgroundComparing to episodic memory, semantic memory is less likely to be impaired in normal aging. Investigation of semantic memory may give us a better chance on detecting Alzheimer disease in early stage.MethodIn 2019, we collected 20 patients from our memory clinic. Half of them were diagnosed as amnesic MCI (mild cognitive impairment), half of them were their spouse. All of them received amyloid PET (florbetaben), brain MRI, ERP (evoked related potential) studies and detailed language evaluation. According to their clinical symptoms and status of amyloid deposition, they were grouping as normal, preclinical and prodromal stage.ResultIn picture description test, participants of prodromal group expressed fewer semantic contents and more filler words compared to others. No significant difference was found between preclinical and normal group. However, N400 (component of ERP, indicating semantic mismatch) showed difference between preclinical and normal group.ConclusionSemantic network impairment begins from preclinical stage of AD. Through detailed spoken language analysis, we could use it as early biomarker and trace disease progression.

Abnormalities of Cortical Sources of Resting State Alpha Electroencephalographic Rhythms are Related to Education Attainment in Cognitively Unimpaired Seniors and Patients with Alzheimer's Disease and Amnesic Mild Cognitive Impairment.

In normal old (Nold) and Alzheimer's disease (AD) persons, a high cognitive reserve (CR) makes them more resistant and resilient to brain neuropathology and neurodegeneration. Here, we tested whether these effects may affect neurophysiological oscillatory mechanisms generating dominant resting state electroencephalographic (rsEEG) alpha rhythms in Nold and patients with mild cognitive impairment (MCI) due to AD (ADMCI). Data in 60 Nold and 70 ADMCI participants, stratified in higher (Edu+) and lower (Edu-) educational attainment subgroups, were available in an Italian-Turkish archive. The subgroups were matched for age, gender, and education. RsEEG cortical sources were estimated by eLORETA freeware. As compared to the Nold-Edu- subgroup, the Nold-Edu+ subgroup showed greater alpha source activations topographically widespread. On the contrary, in relation to the ADMCI-Edu- subgroup, the ADMCI-Edu+ subgroup displayed lower alpha source activations topographically widespread. Furthermore, the 2 ADMCI subgroups had matched cerebrospinal AD diagnostic biomarkers, brain gray-white matter measures, and neuropsychological scores. The current findings suggest that a high CR may be related to changes in rsEEG alpha rhythms in Nold and ADMCI persons. These changes may underlie neuroprotective effects in Nold seniors and subtend functional compensatory mechanisms unrelated to brain structure alterations in ADMCI patients.

Abnormalities of Cortical Sources of Resting State Delta Electroencephalographic Rhythms Are Related to Epileptiform Activity in Patients With Amnesic Mild Cognitive Impairment Not Due to Alzheimer's Disease.

In the present exploratory and retrospective study, we hypothesized that cortical sources of resting state eyes-closed electroencephalographic (rsEEG) rhythms might be more abnormal in patients with epileptiform EEG activity (spike-sharp wave discharges, giant spikes) and amnesic mild cognitive impairment not due to Alzheimer's disease (noADMCI-EEA) than matched noADMCI patients without EEA (noADMCI-noEEA). Clinical, neuroimaging, neuropsychological, and rsEEG data in 32 noADMCI and 30 normal elderly (Nold) subjects were available in a national archive. Age, gender, and education were carefully matched among them. No subject had received a clinical diagnosis of epilepsy. Individual alpha frequency peak (IAF) was used to determine the delta, theta, and alpha frequency bands of rsEEG rhythms. Fixed beta and gamma bands were also considered. Regional rsEEG cortical sources were estimated by eLORETA freeware. Area under receiver operating characteristic (AUROC) curves indexed the accuracy of eLORETA solutions in the classification between noADMCI-EEA and noADMCI-noEEA individuals. As novel findings, EEA was observed in 41% of noADMCI patients. Furthermore, these noADMCI-EEA patients showed higher temporal delta source activities as compared to noADMCI-no EEA patients and Nold subjects. Those activities discriminated individuals of the two NoADMCI groups with an accuracy of about 70%. The significant percentage of noADMCI-EEA patients showing EEA and marked abnormalities in temporal rsEEG rhythms at delta frequencies suggest a substantial role of underlying neural hypersynchronization mechanisms in their brain dysfunctions.

Confabulations in Cases of Dementia: Atypical Early Sign of Alzheimer's Disease or Misleading Feature in Dementia Diagnosis?

Confabulations, also known as false memories, have been associated with various diseases involving mainly the frontal areas, such as Wernicke–Korsakoff syndrome or frontal epilepsy. The neuropsychological dysfunctions underlying mechanisms of confabulation are not well known. We describe two patients with memory impairment and confabulations at the onset speculating about neuropsychological correlates of confabulations and self-awareness. Both patients, a 77-year-old woman and a 57-years-old man, exhibited confabulations as first symptom of cognitive decline. She later developed memory impairment without awareness of her memory deficits and her cognitive and imaging profile suggested an amnesic mild cognitive impairment due to Alzheimer’s disease (AD). Unlike her, he developed a prevalent involvement of frontal functions despite a clear consciousness of his cognitive deficits. However, the clinical diagnostic hypothesis of behavioral variant of frontotemporal dementia was not supported by imaging findings, which suggested AD. Both patients underwent neuropsychological evaluation including the Confabulation Battery. Despite that the exact anatomical correlation of confabulations is still not defined, imaging data shown by our patients is consistent with recent theories according to which at the origin of confabulatory tendency in AD there is an impairment of the connections between crucial hubs in frontal and mediotemporal areas, mainly involving the right hemisphere. Besides, it would be reasonable to hypothesize that self-awareness and confabulations should not be considered as necessarily associated dimensions.

Association between sleep structure and amnesic mild cognitive impairment in patients with insomnia disorder: a case-control study.

To examine the association between sleep structure and amnesic mild cognitive impairment (aMCI) in patients with insomnia disorder. A total of 256 patients with insomnia disorder were diagnosed by neurologists, 45 of whom were diagnosed with aMCI according to the Petersen criteria, and 45 participants with intact cognition were chosen as controls matched for age and education. A case-control study was conducted to compare sleep structure between aMCI and control patients with insomnia disorder. We evaluated self-reported sleep problems by the Insomnia Severity Index and objective sleep features by polysomnography. Logistic regression models were used to estimate the associations between sleep parameters and aMCI in patients with insomnia disorder. There was no significant difference in Insomnia Severity Index scores between the aMCI and control groups. In the logistic regression after adjustment for covariates, people with a longer sleep duration (adjusted odds ratio [aOR] = 0.56, 95% confidence interval [CI]: 0.36-0.89), greater sleep efficiency (aOR = 0.50, 95% CI: 0.32-0.77), and a higher percentage of total sleep time in stage 3 of non-rapid eye movement sleep (N3%) (aOR = 0.02, 95% CI: 0.01-0.15) have a lower relative probability of having aMCI. By contrast, higher N1% (aOR = 2.28, 95% CI: 1.36-3.82) and wake after sleep onset (aOR = 1.31, 95% CI: 1.11-1.55) may be risk factors for aMCI in patients with insomnia. In patients with insomnia disorder, sleep duration, sleep fragmentation, sleep efficiency, N1% and N3% were independently associated with the presence of aMCI. In the clinical setting, if patients with insomnia show much more serious abnormalities in these sleep indices, clinicians should pay attention to their cognitive function. In-depth research would also be worthwhile to elaborate the causality between sleep and cognitive decline.

Neuropsychiatric symptoms and quality of life in Spanish patients with Alzheimer's disease during the COVID-19 lockdown.

Background and purposeThe COVID‐19 epidemic is affecting almost all individuals worldwide, and patients with Alzheimer’s disease (AD) and amnesic mild cognitive impairment (MCI) are particularly at risk due to their characteristics and age. We analysed the impact of the pandemic on these patients’ neuropsychiatric symptoms and their quality of life after 5 weeks of lockdown in Spain.MethodsA total of 40 patients with a diagnosis of MCI (n = 20) or mild AD (n = 20) from the Cognitive Stimulation Program of the Cognitive Disorders Unit were evaluated. All patients had undergone a previous evaluation during the month before the lockdown, and were re‐evaluated after 5 weeks of lockdown. The Neuropsychiatric Inventory (NPI) and EuroQol‐5D questionnaire (EQ‐5D) were used to assess neuropsychiatric symptoms in patients and the quality of life in patients as well in caregivers.ResultsThe mean (SD) total baseline NPI score was 33.75 (22.28), compared with 39.05 (27.96) after confinement (P = 0.028). The most frequently affected neuropsychiatric symptoms were apathy [4.15 (3.78) vs. 5.75 (4.02); P = 0.002] and anxiety [3.95 (3.73) vs. 5.30 (4.01); P = 0.006] in patients with MCI, and apathy [2.35 (2.70) vs. 3.75 (3.78); P = 0.036], agitation [0.45 (1.14) vs. 1.50 (2.66); P = 0.029] and aberrant motor behaviour [1.25 (2.86) vs. 2.00 (2.93); P = 0.044] in patients with AD. We did not observe differences in EQ‐5D scores during the re‐evaluation. The 30% of patients and 40% of caregivers reported a worsening of the patients' health status during confinement.ConclusionsThe results of this study show the worsening of neuropsychiatric symptoms in patients with AD and MCI during 5 weeks of lockdown, with agitation, apathy and aberrant motor activity being the most affected symptoms.

Spect-neuropsychology correlations in very mild Alzheimer's disease and amnesic mild cognitive impairment

BackgroundThe purpose of this study was to explore the clinical and brain functional abnormalities in patients with mild Alzheimer’s Disease (AD) and patients with amnesic Mild Cognitive Impairment (aMCI). Methodswe used resting spect-neuropsychology correlations method. ResultsWe found that parieto-temporal associative cortex, mainly involving the inferior parietal lobule, posterior cingulate and middle temporal gyrus, is compromised early in AD. These results suggest that the dysfunction in these areas contributes to cognitive decline in the storage of verbal information, drawing abilities and non-verbal abstract reasoning in AD. The aMCI group showed hypoperfusion primarily involving the frontal areas bilaterally, and this correlated with the impairment in free delayed recall on a verbal memory task. ConclusionOur results underlie the clinical differences between AD and aMCI patients that might reflect the involvement of different degenerative mechanisms in these groups.

Semantic Relations in a Categorical Verbal Fluency Test: An Exploratory Investigation in Mild Cognitive Impairment.

Categorical verbal fluency tests (CFT) are commonly used to assess the integrity of semantic memory in individuals with brain damage. Persons with Dementia of the Alzheimer’s Type display a reduced output on CFT, and a similar pattern has been reported in persons with amnesic Mild Cognitive Impairment (aMCI). The aims of the present study were to assess whether the semantic relations between lexical entries produced on a categorical fluency test were different between healthy persons and those with aMCI, and whether this difference was more pronounced in individuals who converted to dementia during a 3-year follow-up period.MethodsWe recruited 34 individuals with aMCI and 29 matched healthy persons. During the follow-up period, 10 individuals converted to Dementia (aMCI-conv). Two measures assessing semantic relations between consecutively produced word pairs (Path length and Extended Gloss Overlap) were obtained from the Wordnet database.ResultsThe number of word pairs analyzed among the healthy participants (HP) and persons with aMCI were 498 (birds: 262; pieces of furniture: 236) and 395 (birds: 174; pieces of furniture: 221), respectively. Path length was lower in aMCI-conv than in HP (p = 0.035), but no differences were found between stable aMCI and HP, and between aMCI-stable and aMCI-conv. The ANOVA for lexical entries belonging to the “birds” category showed a significant effect of group (F = 5.630; p = 0.004); the post hoc analysis showed a significant difference between HP and aMCI-conv (p = 0.003). The “pieces of furniture” category was significantly affected by group (F = 4.107; p = 0.017); the post hoc test showed significant differences between aMCI-conv and healthy individuals (p = 0.049), and between aMCI-conv and stable aMCI (p = 0.001).DiscussionIndividuals with aMCI who convert to dementia show a deterioration in the semantic relations between lexical entries, produced on a CFT. This phenomenon may be interpreted as a marker of a very early disruption of semantic memory.

Selective impairment of musical emotion recognition in patients with amnesic mild cognitive impairment and mild to moderate Alzheimer disease.

BackgroundPatients with Alzheimer disease (AD) and amnesic mild cognitive impairment (aMCI) have deficits in emotion recognition. However, it has not yet been determined whether patients with AD and aMCI also experience difficulty in recognizing the emotions conveyed by music. This study was conducted to investigate whether musical emotion recognition is impaired or retained in patients with AD and aMCI.MethodsAll patients were recruited from the First Affiliated Hospital of Anhui Medical University between March 1, 2015 and January 31, 2017. Using the musical emotion recognition test, patients with AD (n = 16), patients with aMCI (n = 19), and healthy controls (HCs, n = 16) were required to choose one of four emotional labels (happy, sad, peaceful, and fearful) that matched each musical excerpt. Emotion recognition scores in three groups were compared using one-way analysis of variance (ANOVA) test. We also investigated the relationship between the emotion recognition scores and Mini-Mental State Examination (MMSE) using Pearson's correlation analysis test in patients with AD and aMCI.ResultsCompared to the HC group, both of the patient groups showed deficits in the recognition of fearful musical emotions (HC: 7.88 ± 1.36; aMCI: 5.05 ± 2.34; AD: 3.69 ± 2.02), with results of a one-way ANOVA confirming a significant main effect of group (F(2,50) = 18.70, P < 0.001). No significant differences were present among the three groups for the happy (F(2,50)=2.57, P = 0.09), peaceful (F(2,50) = 0.38, P = 0.09), or sad (F(2,50) = 2.50, P = 0.09) musical emotions. The recognition of fearful musical emotion was positively associated with general cognition, which was evaluated by MMSE in patients with AD and aMCI (r = 0.578, P < 0.001). The correlations between the MMSE scores and recognition of the remaining emotions were not significant (happy, r = 0.228, P = 0.11; peaceful, r = 0.047, P = 0.74; sad, r = 0.207, P = 0.15).ConclusionThis study showed that both patients with AD and aMCI had decreased ability to distinguish fearful emotions, which might be correlated with diminished cognitive function.

White Matter Microstructural Change Contributes to Worse Cognitive Function in Patients With Type 2 Diabetes.

Patients with type 2 diabetes mellitus (T2DM) have a considerably high risk of developing dementia, especially for those with mild cognitive impairment (MCI). The investigation of the microstructural change of white matter (WM) between T2DM with amnesic MCI (T2DM-aMCI) and T2DM with normal cognition (T2DM-NC) and their relationships to cognitive performances can help to understand the brain variations in T2DM-related amnesic cognitive impairment. In the current study, 36 T2DM-aMCI patients, 40 T2DM-NC patients, and 40 healthy control (HC) individuals underwent diffusion tensor image and T1-weighted MRI scans and comprehensive cognition assessments. All of these cognitive functions exhibited intergroup ranking differences in patients. The T2DM-NC patients and HC individuals did not reveal any significant differences in WM integrity. The T2DM-aMCI patients showed disrupted integrity in multiple WM tracts compared with HC and T2DM-NC. Specifically, the damaged WM integrity of the right inferior fronto-occipital fasciculus and the right inferior longitudinal fasciculus exhibited significant correlations with episodic memory and attention function impairment in T2DM patients. Furthermore, cognitive impairment-related WM microstructural damage was associated with the degeneration of cortex connected to the affected WM tract. These findings indicate that degeneration exists extensively in WM tracts in T2DM-aMCI, whereas no brain WM damage is evident in T2DM-NC.

Risk Factors and Neuropsychological Assessments of Subjective Cognitive Decline (plus) in Chinese Memory Clinic.

BackgroundSince subjective cognitive decline (SCD) was standardized in 2014, many studies have investigated its features. However, the risk of SCD (plus) progressing to AD is much higher, and yet there have been few studies reporting the risk factors and neuropsychological assessment characteristics of SCD (plus).ObjectiveTo characterize SCD (plus) by comparing it with normal control (NC), amnesic mild cognitive impairment (aMCI), and Alzheimer Disease (AD) regarding their demographics, lifestyle, family history of dementia, multimorbidity and the neuropsychological assessments.MethodsA total of 135 participants were recruited, including 23 NC, 30 SCD (plus), 45 aMCI and 37 AD. Descriptive statistics were provided. A logistic regression model was used to analyze the affecting factors of SCD (plus), and finally the Receiver Operating Characteristic (ROC) analysis was applied to distinguish between SCD (plus) and NC.Results(1) SCD (plus) group was younger than both the aMCI group and AD group. It consisted of more participants with mental work and higher body mass index (BMI) than the AD group. (2) Scores of Auditory Verbal Learning Test - Immediate recall (AVLT-IR) and AVLT-Long delayed recall (AVLT-LR) decreased in the following order: NC→SCD (plus)→aMCI→AD. (3) The Area Under Curve (AUC) for discriminating SCD (plus) and NC group was from 0.673 to 0.838.ConclusionAging is an important risk factor of both NC progressing to SCD (plus), and SCD (plus) progressing to aMCI or AD. In addition to aging, lower education level and lower BMI were significantly associated with greater odds of SCD (plus) progressing to aMCI or AD patients, whereas mental work was a protective factor of SCD (plus) progressing to AD. Finally, AVLT is a sensitive indicator of the cognitive decline and impairment in SCD (plus) in relative to normal controls.