Non-amnestic Mild Cognitive Impairment Research Articles

Syntactic comprehension abilities in aged people with mild cognitive impairment

ABSTRACT Background Language studies in mild cognitive impairment (MCI) and Alzheimer’s disease (AD) have been primarily focused on lexicosemantic abilities, with a paucity of data regarding syntactic processing. Aims We aimed to verify the sentence comprehension ability of older adults with amnestic MCI (aMCI), non-amnestic MCI (naMCI), and mild AD and compare it to the performance of cognitively healthy older adults. Methods & Procedures We evaluated 32 cognitively healthy older adults, 22 with aMCI, 43 with naMCI, and 12 with mild AD using the Test for Reception of Grammar Version 2 (TROG-2). Outcomes & Results There were significant differences between the control and MCI and control and AD groups in the total number of correct answers and among the four groups’ profiles according to the type of sentence (p < 0.05). Zero anaphor, pronoun gender/number, and centre-embedded sentences discriminated at least between two groups (p < 0.05). Conclusions Poorer performance in sentences structurally more complex was in line with the severity of the cognitive decline, which may point to the effect of increased demands on working memory and executive functions on syntactic processing.

Olfaction and thyroid hormones in patients with subjective cognitive decline, non-amnestic and amnestic mild cognitive impairment.

Thyroid hormones may affect olfaction in different stages of cognitive impairment: subjective cognitive decline (SCD), non-amnestic (naMCI) and amnestic mild cognitive impairment (aMCI). Additionally, biometric parameters, depression, and neuropsychological performance are considered as possible influencing factors. Aretrospective single-center data analysis was conducted during the observation period 2001-2023, with n = 495 (52.3% female) SCD, naMCI and aMCI subjects, aged ≥50years, at the General Hospital of Vienna. The criterion olfactory function was objectively measured by Sniffin' Sticks© odor identification and subjectively through the Assessment of Self-Reported Olfactory Functioning test. Serum thyroid hormone levels, mainly thyroid-stimulating hormone, as well as T3, T4, fT3, and fT4, were used to assess thyroid function. Statistical analyses using IBM SPSS® 29.0.0 covered adjusted multiple linear regression models with hierarchical blocks to predict olfactory performance considering β‑weights. Of the study participants, 4.2% had hypothyroidism and 2.4% had hyperthyroidism. The majority exhibited normal thyroid function. One third (33.5%; 95% confidence interval, CI 29.4-37.0%) were hyposmic. The results indicate no substantial association between thyroid and olfactory functions. Increasing age (β = 0.20), lower performance in the Neuropsychological Test Battery Vienna (NTBV) dimensions verbal memory (β = -0.33) and attention (β = -0.12) appear to be risk factors for lower olfaction. Adiscrepancy between subjective and objective olfaction was found. Thyroid and olfactory functions had no substantial relationship. Higher fT4 correlated weakly with lower odor identification. Increasing age and decreased performance in two out of six NTBV dimensions are relevant prognostic factors for olfactory dysfunction.

Depressive symptoms-Not apredictor for five-year mortality in patients with subjective cognitive decline, non-amnestic and amnestic mild cognitive impairment.

The main aim of the present study is to evaluate the influence of depressive symptoms on mortality in patients with SCD (subjective cognitive decline), naMCI (non-amnestic mild cognitive impairment), and aMCI (amnestic mild cognitive impairment). Additional factors (age, sex, years of school attendance, and neuropsychological performance) were considered to determine the impact on survival probability. Amonocentric retrospective data analysis based on adjusted patient protocols (n = 1221) from the observation period 1998-2021, using the Cox Proportional Hazards model, assessed whether depressivity had an explanatory value for survival, considering SCD as the reference level in relation to naMCI and aMCI. Covariates were included blockwise. Cox regression revealed that depressiveness (Beck Depression Inventory, Geriatric Depression Scale) did not make asignificant contribution as arisk factor for mortality in all five model blocks, BDI-II with HR 0.997 [0.978; 1.02] and GDS-15 with HR 1.03 [0.98; 1.08]. Increasing age with HR 1.09 [1.07; 1.11] and male sex with HR (inverted) 1.53 [1.17; 2.00] appeared as risk factors for increased mortality across all five model blocks. aMCI (vs. SCD) with HR 1.91 [1.33; 2.76] showed asignificant explanatory value only up to the fourth model block. By adding the six dimensions of the Neuropsychological Test Battery Vienna in the fifth model block, the domains attention and perceptual speed with HR 1.34 [1.18; 1.53], and executive functions with HR 1.24 [1.11; 1.39], showed substantial explanatory values for survival. Accordingly, no tendency can be attributed to depressiveness as arisk factor on the probability of survival, whereas the influence of certain cognitive dimensions, especially attention and perceptual speed, and executive functions, can be seen as protective for survival.

Label-guided low-rank Approximation for functional brain network learning in identifying subcortical vascular cognitive impairment

Background and ObjectiveFunctional brain network (FBN) has played a pivotal role in unraveling the inherent mechanism of cognition/behavior and investigating neuropsychological disorders. Particularly, growing evidence suggests that FBNs have shown great potential in classifying brain disorders such as subcortical vascular cognitive impairment (SVCI). However, learning a high-quality FBN is still challenging since there is no ground truth. Most traditional methods tend to focus on learning FBNs independently of the downstream task. This practice neglects the valuable label information crucial for accurate classification. Besides, the methodology of constructing brain networks in an isolated, individualistic manner sidesteps the common information among individuals. MethodsTo address these issues, we developed a new FBN joint learning strategy named Label-Guided Low-rank Approximation (LGLA). LGLA integrates label information from training subjects and uses unlabeled testing subjects for auxiliary training, enhancing the discriminative power of FBN features tailored to testing subjects. By enforcing class-specific similarities and differences, and applying a low-rank constraint to capture shared information, LGLA presents an optimization framework that can be effectively solved. ResultsExperimental results demonstrate the effectiveness of our proposed FBN learning method for identifying SVCI. The proposed method achieved an accuracy of 75.70% and an area under the receiver operating characteristic curve (AUC) of 0.8233 in the task of identifying patients with amnestic mild cognitive impairment (aMCI). For identifying patients with non-amnestic mild cognitive impairment (naMCI), it achieved an accuracy of 63.64% and an AUC of 0.7857, while the task of identifying patients with no cognitive impairment (NCI), it achieved an accuracy of 63.64% and an AUC of 0.7917. Additionally, we further explored the brain network features and discovered potential biomarkers for personalized diagnosis. ConclusionThe LGLA method enhances FBN construction and classification accuracy for SVCI diagnosis by effectively integrating the label information and shared structure among subjects.

The Relationships of Specific Cognitive Control Abilities with Objective and Subjective Sleep Parameters in Mild Cognitive Impairment: Revealing the Association between Cognitive Planning and Sleep Duration.

This study aimed to examine the associations between specific sleep parameters and specific aspects of cognitive functioning in individuals diagnosed with mild cognitive impairment (MCI), compared with healthy controls (HCs) by using cognitive, subjective, and objective sleep measures. A total of 179 participants were enrolled, all aged ≥ 65 years (mean age = 70.23; SD = 4.74) and with a minimum of six years of education (mean = 12.35; SD = 3.22). The sample included 46 HCs (36 females), 75 individuals with amnestic MCI (aMCI) (51 females), and 58 individuals with non-amnestic MCI (naMCI) (39 females). Inhibition, cognitive flexibility as a combined application of inhibitory control and set shifting or task/rule switching, and planning were examined. The following D-KEFS subtests were administered for their evaluation: Verbal Fluency Test, Color-Word Interference Test, and Tower Test. Self-reported sleep questionnaires (Athens Insomnia Scale, Stop-Bang questionnaire, and Pittsburg Sleep Quality Index) were used for subjective sleep assessments. Actigraphy was used for objective sleep measurements. Mixed-measures ANOVA, MANOVA, and one-way ANOVA, as well as the Scheffe post hoc test, were applied to the data. The results showed that the three groups exhibited statistically significant differences in the Tower Test (total achievement score, total number of administered problems, and total rule violations). As regards objective sleep measurements, the total sleep time (TST) was measured using actigraphy, and indicated that there are significant differences, with the HC group having a significantly higher mean TST compared to the naMCI group. The relationships evaluated in the TST Tower Test were found to be statistically significant. The findings are discussed in the context of potential parameters that can support the connection between sleep duration, measured as TST, and cognitive planning, as measured using the Tower Test.

Effect of APOE ɛ4 Status on Brain Amyloid‐β and Cognitive Function in Amnestic and Nonamnestic Mild Cognitive Impairment: A [18F] Florbetapir PET‐CT Study

AbstractMild cognitive impairment (MCI) is recognized as a predementia syndrome caused by multiple etiologies and nonmemory symptoms in MCI have recently gained increasing attention. However, the pattern of Aβ deposition and the effect of APOE (apolipoprotein E, APOE) ε4 on cognitive impairment in amnestic MCI (aMCI) and nonamnestic MCI (naMCI) patients has not been demonstrated. In this work, the amyloid‐β (Aβ) load by [18F]florbetapir PET imaging and cognitive performance is compared by comprehensive neuropsychological scales in participants with different MCI types or different APOE ε4 carriage status. According to the Aβ positivity and results of voxel‐wise analysis, higher Aβ loads are observed in aMCI patients than naMCI patients, especially aMCI patients with APOE ε4. Additionally, it is observed that memory domain Z scores show a strong negative correlation with global florbetapir SUVR in the aMCI group (r = – 0.352, p &lt; 0.001) but not in the naMCI group (r = –0.016, p = 0.924). Moreover, this correlation is independent of APOE e4 carriage status. This study aims to identify high‐risk groups at an early stage of AD(Alzheimer's Disease, AD) through cognitive performance and APOE ε4 carrier status, which can be important for guiding clinical intervention trials.

Prolonged ventricular repolarization associated with mild cognitive impairment and white matter hyperintensities: a cross-sectional study

Prolonged ventricular repolarization has been associated with cardiovascular disease. We sought to investigate the association of prolonged ventricular repolarization with mild cognitive impairment (MCI) and the potential underlying neuropathological mechanisms in older adults. This cross-sectional study included 4328 dementia-free participants (age ≥ 65 years; 56.8% female) in the baseline examination of the Multidomain INterventions to delay dementia and Disability in rural China; of these, 989 undertook structural brain magnetic resonance imaging (MRI) scans. QT, QTc, JT, JTc, and QRS intervals were derived from 12-lead electrocardiograph. MCI, amnestic MCI (aMCI), and non-amnestic MCI (naMCI) were defined following the Petersen’s criteria. Volumes of gray matter (GM), white matter, cerebrospinal fluid, total white matter hyperintensities (WMH), periventricular WMH (PWMH), and deep WMH (DWMH) were automatically estimated. Data were analyzed using logistic and general linear regression models. Prolonged QT, QTc, JT, and JTc intervals were significantly associated with an increased likelihood of MCI and aMCI, but not naMCI (p < 0.05). In the MRI subsample, QT, QTc, JT, and JTc intervals were significantly associated with larger total WMH and PWMH volumes (p < 0.05), but not with DWMH volume. Statistical interactions were detected, such that prolonged QT and JT intervals were significantly associated with reduced GM volume only among participants with coronary heart disease or without APOE ε4 allele (p < 0.05). Prolonged ventricular repolarization is associated with MCI and cerebral microvascular lesions in a general population of older adults. This underlies the importance of cognitive assessments and brain MRI examination among older adults with prolonged QT interval.

Machine Learning Classification of Patients with Amnestic Mild Cognitive Impairment and Non-Amnestic Mild Cognitive Impairment from Written Picture Description Tasks.

Individuals with Mild Cognitive Impairment (MCI), a transitional stage between cognitively healthy aging and dementia, are characterized by subtle neurocognitive changes. Clinically, they can be grouped into two main variants, namely patients with amnestic MCI (aMCI) and non-amnestic MCI (naMCI). The distinction of the two variants is known to be clinically significant as they exhibit different progression rates to dementia. However, it has been particularly challenging to classify the two variants robustly. Recent research indicates that linguistic changes may manifest as one of the early indicators of pathology. Therefore, we focused on MCI's discourse-level writing samples in this study. We hypothesized that a written picture description task can provide information that can be used as an ecological, cost-effective classification system between the two variants. We included one hundred sixty-nine individuals diagnosed with either aMCI or naMCI who received neurophysiological evaluations in addition to a short, written picture description task. Natural Language Processing (NLP) and a BERT pre-trained language model were utilized to analyze the writing samples. We showed that the written picture description task provided 90% overall classification accuracy for the best classification models, which performed better than cognitive measures. Written discourses analyzed by AI models can automatically assess individuals with aMCI and naMCI and facilitate diagnosis, prognosis, therapy planning, and evaluation.

The protective role of cognitive reserve: an empirical study in mild cognitive impairment

BackgroundMild cognitive impairment (MCI) describes an aging profile characterized by a cognitive decline that is worse than expected in normal aging but less pervasive and critical than full-blown dementia. In the absence of an effective treatment strategy, it is important to identify factors that can protect against progression to dementia. In this field, it is hypothesized that one aspect that may be a protective factor against the neurotypical outcome of dementia is cognitive reserve (CR). Cognitive reserve is the ability to maintain cognitive functionality despite accumulating brain pathology.ObjectivesThe present study aimed to identify and analyze the differences in CR between healthy adults and patients with MCI. Specifically, it is hypothesized that (i) healthy older adult people have higher CR than older adult people diagnosed with MCI, and (II) CR could predict the classification of subjects into people with or without MCI.MethodsTwo hundred forty-three adults (mean age = 60.4, SD = 7.4) participated in the present study and were classified into three groups based on Petersen’s MCI criteria: healthy controls (HC), amnestic MCI (aMCI), and non-amnestic MCI (naMCI). The Cognitive Reserve Index questionnaire (CRIq) was administered to assess the level of CR,FindingsResults showed that HC had significantly higher CR scores than participants diagnosed with aMCI and naMCI. Moreover, a binomial logistic regression suggested that low CR was a significant risk factor for the MCI diagnosis.ConclusionsThe clinical picture that emerged from the results showed that lower CR could be considered a characteristic of pathological aging, such as MCI.Public significance statement, Since the brain attempts to cope with life-related changes or pathologies, it is fundamental for both clinicians and researchers to investigate further the factors that contribute to brain resilience. As an indirect expression of brain reserve, cognitive reserve may be both a marker and a predictor of adaptive aging.

FNIRS as a biomarker for individuals with subjective memory complaints and MCI.

Identifying individuals at risk of developing dementia is crucial for early intervention. Mild cognitive impairment (MCI) and subjective memory complaints (SMCs) are considered its preceding stages. This study aimed to assess the utility of functional near-infrared spectroscopy (fNIRS) in identifying individuals with MCI and SMC. One hundred fifty-one participants were categorized into normal cognition (NC); amnestic MCI (aMCI); non-amnestic MCI (naMCI); and mild, moderate, and severe SMC groups. Task-related prefrontal hemodynamics were measured using fNIRS during a visual memory span task. Results showed significantly lower oxyhemoglobin (HbO) levels in aMCI, but not in naMCI, compared to the NC. In addition, severe SMC had lower HbO levels than the NC, mild, and moderate SMC. Receiver operating characteristic analysis demonstrated 69.23% and 69.70% accuracy in differentiating aMCI and severe SMC from NC, respectively. FNIRS may serve as a potential non-invasive biomarker for early detection of dementia. Only amnestic mild cognitive impairment (aMCI), but not non-amnestic MCI, showed lower oxyhemoglobin (HbO) than normal individuals. Reduced HbO was observed in those with severe subjective memory complaints (SMCs) compared to normal cognition (NC), mild, and moderate SMCs. Functional near-infrared spectroscopy measures were associated with performance in memory assessments. Prefrontal hemodynamics could distinguish aMCI and severe SMC from NC.

High plasma homocysteine levels predict the progression from mild cognitive impairment to dementia

High levels of blood homocysteine (HCy), a well-known cardiovascular risk factor and promoter of oxidative stress, have been associated with the incidence of cognitive impairment and dementia. Nonetheless, contrasting data are still present on its involvement in the progression from Mild Cognitive Impairment (MCI) to overt dementia.In this study we aimed to observe whether blood HCy level are associated with the evolution from MCI, divided into amnestic MCI (aMCI) and non-amnestic MCI (naMCI), to dementia.Blood HCy was measured in 311 MCI subjects (aMCI: 64%, naMCI: 36%) followed-up for a median of 33 months (range 10–155 months). At follow-up, 137 individuals converted to dementia (naMCI, n = 34; aMCI, n = 103). Based on HCy distribution, subjects in the highest tertile had a greater risk to convert to dementia compared to tertile I (Hazard Ratio (95% confidence interval): 2.25 (1.05–4.86); p = 0.04). aMCI subjects did not show increased risk to convert to dementia with increasing HCy concentration, but was significant in naMCI (p = 0.04). We observed a non-significant increase in the risk of progression to dementia from naMCI/low HCy (reference group, HCy cutoff value = 16 μmol/L) to naMCI/high HCy, but it was significant from aMCI/low HCy (HR: 2.73; 95%CI: 1.06–7.0; p:0.03), to aMCI/high HCy (HR: 3.24; 95%CI: 1.17–8.47; p:0.02).Our results suggest that HCy levels are associated with the progression from MCI to dementia. This association seems significant only for the naMCI group, indirectly supporting the notion that hyperhomocysteinemia damages the nervous system through its role as a vascular risk factor.

The Effectiveness of Cognitive Rehabilitation Software on the Cognitive Functions of Patients with Non-Amnestic Mild Cognitive Impairment

Background and Aims Mild cognitive impairment (MCI) is one of the cognitive profiles of senility. It is classified into amnestic and nonamnestic MCI depending on the involvement of different cognitive functions. This research aims to design a cognitive rehabilitation software based on the attention process model and investigate its effect on the attention and executive functions of older people with nonamnestic mild cognitive impairment. Methods This quasi-experimental research employed a pretest-posttest and follow-up design. After designing the software program, 30 older people over 60 who were diagnosed with nonamnestic mild cognitive impairment through NUCOG (Neuropsychiatry Unit Cognitive Assessment Tool) screening and a psychiatrist who met the inclusion criteria were randomly assigned to the experimental or control group (each with 15 people). To perform the rehabilitation intervention, a software system was designed based on Mateer and Sohlberg attention process training, whose validity and reliability have been confirmed in Iranian older adults. After the pretest, the experimental group received the rehabilitation intervention with the software, and the control group did not receive anything. Three months after the completion of the sessions, both groups were assessed as the posttest, and the results were compared using an analysis of covariance and the Mann-Whitney U test using SPSS software, version 26. Results The results indicated significant differences between the posttest scores of the experimental and control groups in the mean score of errors in congruent and incongruent selective attention, executive function score, time and error in alternating attention in the colors trail test A form (CTT-A) and time in alternating attention in CTT-B and also time and error in separated attention (P&lt;0.05). However, there were no significant differences between the two groups posttest mean scores in selective attention time, time and error in sustained attention, and error in CTT-B alternating attention (P&gt;0.05). The intervention did not cause any significant improvement in these domains. Also, the results were sustained after 3 months. Conclusion The results confirmed the efficacy of cognitive rehabilitation interventions. The designed cognitive rehabilitation software in this research can cause a significant improvement in attention and executive functions of patients with nonamnestic mild cognitive impairment. It can be used as a clinical intervention.

Association of objective sleep duration with cognition and brain aging biomarkers in older adults.

The neuropathological mechanisms underlying the association between sleep duration and mild cognitive impairment remain poorly understood. This population-based study included 2032 dementia-free people (age ≥ 60 years; 55.1% women) derived from participants in the Multimodal Interventions to Delay Dementia and Disability in Rural China; of these, data were available in 841 participants for Alzheimer's plasma biomarkers (e.g. amyloid-β, total tau and neurofilament light chain), 1044 for serum microvascular biomarkers (e.g. soluble adhesion molecules) and 834 for brain MRI biomarkers (e.g. whiter matter, grey matter, hippocampus, lacunes, enlarged perivascular spaces and white matter hyperintensity WMH). We used electrocardiogram-based cardiopulmonary coupling analysis to measure sleep duration, a neuropsychological test battery to assess cognitive function and the Petersen's criteria to define mild cognitive impairment. Data were analysed with multivariable logistic and general linear models. In the total sample (n = 2032), 510 participants were defined with mild cognitive impairment, including 438 with amnestic mild cognitive impairment and 72 with non-amnestic mild cognitive impairment. Long sleep duration (>8 versus 6-8 h) was significantly associated with increased likelihoods of mild cognitive impairment and non-amnestic mild cognitive impairment and lower scores in global cognition, verbal fluency, attention and executive function (Bonferroni-corrected P < 0.05). In the subsamples, long sleep duration was associated with higher plasma amyloid-β40 and total tau, a lower amyloid-β42/amyloid-β40 ratio and smaller grey matter volume (Bonferroni-corrected P < 0.05). Sleep duration was not significantly associated with serum-soluble adhesion molecules, white matter hyperintensity volume, global enlarged perivascular spaces and lacunes (P > 0.05). Alzheimer's and neurodegenerative pathologies may represent common pathways linking long sleep duration with mild cognitive impairment and low cognition in older adults.

News event memory in amnestic and non-amnestic MCI, heritable risk for dementia, and subjective memory complaints

Robust and sensitive clinical measures are needed for more accurate and earlier detection of Alzheimer's disease (AD), for staging preclinical AD, and for gauging the efficacy of treatments. Mild impairment on episodic memory tests is thought to indicate a cognitive risk of developing AD and mild cognitive impairment (MCI), considered to be a transitional stage between normal aging and AD. Novel tests of semantic memory, such as memory for news events, are also impaired early on but have received little clinical attention even though they may provide a novel way to assess cognitive risk for AD. We examined memory for news events in older adults with normal cognition (NC, N = 34), amnestic MCI (aMCI, N = 27), or non-aMCI (N = 10) using the Retrograde Memory News Events Test (RM-NET). We asked if news event memory was sensitive to 1) aMCI and also non-aMCI, which has rarely been examined, 2) genetic risk for dementia (positive family history of any type of dementia, presence of an APOE-4 allele, or polygenic risk for AD), and 3) subjective memory functioning judgments about the past. We found that both MCI subgroups exhibited impaired RM-NET Lifespan accuracy scores together with temporally-limited retrograde amnesia. For the aMCI group amnesia extended back 45 years prior to testing, but not beyond that time frame. The extent of retrograde amnesia could not be reliably estimated in the small non-aMCI group. The effect sizes of having MCI on the RM-NET were medium for the non-aMCI group and large for the aMCI group, whereas the effect sizes of participant characteristics on RM-NET accuracy scores were small. For the combined MCI group (N = 37), news event memory was significantly related to positive family history of dementia but was not related to the more specific genetic markers of AD risk. For the NC group, news event memory was not related to any measure of genetic risk. Objective measures of past memory from the RM-NET were not related to subjective memory judgements about the present or the recent past in either group. By contrast, when individuals subjectively compared their present versus past memory abilities, there was a significant association between this judgment and objective measures of the past from the RM-NET (direct association for the NC group and inverse for the MCI group). The RM-NET holds significant promise for early identification of those with cognitive and genetic risk factors for AD and non-AD dementias.

Low Functional network integrity in cognitively unimpaired and MCI subjects with depressive symptoms: results from a multi-center fMRI study

Evidence suggests that depressive symptomatology is a consequence of network dysfunction rather than lesion pathology. We studied whole-brain functional connectivity using a Minimum Spanning Tree as a graph-theoretical approach. Furthermore, we examined functional connectivity in the Default Mode Network, the Frontolimbic Network (FLN), the Salience Network, and the Cognitive Control Network. All 183 elderly subjects underwent a comprehensive neuropsychological evaluation and a 3 Tesla brain MRI scan. To assess the potential presence of depressive symptoms, the 13-item version of the Beck Depression Inventory (BDI) or the Geriatric Depression Scale (GDS) was utilized. Participants were assigned into three groups based on their cognitive status: amnestic mild cognitive impairment (MCI), non-amnestic MCI, and healthy controls. Regarding affective symptoms, subjects were categorized into depressed and non-depressed groups. An increased mean eccentricity and network diameter were found in patients with depressive symptoms relative to non-depressed ones, and both measures showed correlations with depressive symptom severity. In patients with depressive symptoms, a functional hypoconnectivity was detected between the Anterior Cingulate Cortex (ACC) and the right amygdala in the FLN, which impairment correlated with depressive symptom severity. While no structural difference was found in subjects with depressive symptoms, the volume of the hippocampus and the thickness of the precuneus and the entorhinal cortex were decreased in subjects with MCI, especially in amnestic MCI. The increase in eccentricity and diameter indicates a more path-like functional network configuration that may lead to an impaired functional integration in depression, a possible cause of depressive symptomatology in the elderly.

Data-driven classification of cognitively normal and mild cognitive impairment subtypes predicts progression in the NACC dataset.

Data-driven neuropsychological methods can identify mild cognitive impairment (MCI) subtypes with stronger associations to dementia risk factors than conventional diagnostic methods. Cluster analysis used neuropsychological data from participants without dementia (mean age=71.6 years) in the National Alzheimer's Coordinating Center (NACC) Uniform Data Set (n=26,255) and the "normal cognition" subsample (n=16,005). Survival analyses examined MCI or dementia progression. Five clusters were identified: "Optimal" cognitively normal (oCN; 13.2%), "Typical" CN (tCN; 28.0%), Amnestic MCI (aMCI; 25.3%), Mixed MCI-Mild (mMCI-Mild; 20.4%), and Mixed MCI-Severe (mMCI-Severe; 13.0%). Progression to dementia differed across clusters (oCN<tCN<aMCI<mMCI-Mild<mMCI-Severe). Cluster analysis identified more MCI cases than consensus diagnosis. In the "normal cognition" subsample, five clusters emerged: High-All Domains (High-All; 16.7%), Low-Attention/Working Memory (Low-WM; 22.1%), Low-Memory (36.3%), Amnestic MCI (16.7%), and Non-amnestic MCI (naMCI; 8.3%), with differing progression rates (High-All<Low-WM=Low-Memory<aMCI<naMCI). Our data-driven methods outperformed consensus diagnosis by providing more precise information about progression risk and revealing heterogeneity in cognition and progression risk within the NACC "normal cognition" group.

Reversal of the concreteness effect can be detected in the natural speech of older adults with amnestic, but not non-amnestic, mild cognitive impairment.

Patients with Alzheimer's disease present with difficulty in lexical retrieval and reversal of the concreteness effect in nouns. Little is known about the phenomena before the onset of symptoms. We anticipate early linguistic signs in the speech of people who suffer from amnestic mild cognitive impairment (MCI). Here, we report the results of a corpus-linguistic approach to the early detection of cognitive impairment. One hundred forty-eight English-speaking Singaporeans provided natural speech data, on topics of their choice; 74 were diagnosed with single-domain MCI (38 amnestic, 36 non-amnestic), 74 cognitively healthy. The recordings yield 267,310 words, which are tagged for parts of speech. We calculate the per-minute word counts and concreteness scores of all tagged words, nouns, and verbs in the dataset. Compared to controls, subjects with amnestic MCI produce fewer but more abstract nouns. Verbs are not affected. Slower retrieval of nouns and the reversal of the concreteness effect in nouns are manifested in natural speech and can be detected early through corpus-based analysis. Reversal of the concreteness effect is manifested in patients with Alzheimer's disease (AD) and semantic dementia.The paper reports a corpus-based analysis of natural speech by people with amnestic and non-amnestic mild cognitive impairment (MCI) and cognitively healthy controls.People with amnestic MCI produce fewer and more abstract nouns than people with non-amnestic MCI and healthy controls. Verbs appear to be unaffected.The imageability problem can be detected in natural everyday speech by people with amnestic MCI, which carries a higher risk of conversion to AD.

Strategic Lacunes Associated With Mild Cognitive Impairment in Rural Chinese Older Adults: A Population-Based Study.

Lacunes are associated with cognitive impairment. We sought to identify strategic lacune locations associated with mild cognitive impairment (MCI) and subtypes of MCI among older adults, and further to examine the role of white matter hyperintensities and perivascular spaces in the association. This population-based cross-sectional study included 1230 dementia-free participants in the brain magnetic resonance imaging substudy (2018-2020) in MIND-China (Multimodal Interventions to Delay Dementia and Disability in Rural China). Lacunes were visually identified in frontal lobe, parieto-occipital lobe, temporal lobe, insula, basal ganglia, thalamus, cerebellum, and brainstem. MCI, amnestic MCI (aMCI), and nonamnestic MCI (naMCI) were defined following the Petersen's criteria. Data were analyzed using logistic regression models. Of the 1230 participants (age, ≥60 years; mean age, 69.40; SD, 4.30 years; 58.5% women), lacunes were detected in 357 people and MCI was defined in 286 individuals, including 243 with aMCI and 43 with naMCI. Lacunes in the supratentorial area, internal capsula, putamen/pallidum, and insula was significantly associated with increased odds ratio of MCI (multivariable-adjusted odds ratio ranged 1.40-3.21; P<0.05) and aMCI (multivariable-adjusted odds ratio ranged 1.46-3.36; P<0.05), whereas lacunes in the infratentorial area and brainstem were significantly associated with naMCI (multivariable-adjusted odds ratio ranged 2.68-3.46; P<0.01). Furthermore, the associations of lacunes in insula and internal capsula with MCI and aMCI, as well as the associations of lacunes in infratentorial area and brainstem with naMCI were present independent of white matter hyperintensities volume and perivascular spaces number. Lacunes in the internal capsula, putamen/pallidum, insula, and brainstem may represent the strategic lacunes that are independently associated with MCI, aMCI, or naMCI in Chinese older adults. URL: https://www.chictr.org.cn; Unique identifier: ChiCTR1800017758.

Electroencephalography-based classification of Alzheimer’s disease spectrum during computer-based cognitive testing

Alzheimer’s disease (AD) is a progressive disease leading to cognitive decline, and to prevent it, researchers seek to diagnose mild cognitive impairment (MCI) early. Particularly, non-amnestic MCI (naMCI) is often mistaken for normal aging as the representative symptom of AD, memory decline, is absent. Subjective cognitive decline (SCD), an intermediate step between normal aging and MCI, is crucial for prediction or early detection of MCI, which determines the presence of AD spectrum pathology. We developed a computer-based cognitive task to classify the presence or absence of AD pathology and stage within the AD spectrum, and attempted to perform multi-stage classification through electroencephalography (EEG) during resting and memory encoding state. The resting and memory-encoding states of 58 patients (20 with SCD, 10 with naMCI, 18 with aMCI, and 10 with AD) were measured and classified into four groups. We extracted features that could reflect the phase, spectral, and temporal characteristics of the resting and memory-encoding states. For the classification, we compared nine machine learning models and three deep learning models using Leave-one-subject-out strategy. Significant correlations were found between the existing neurophysiological test scores and performance of our computer-based cognitive task for all cognitive domains. In all models used, the memory-encoding states realized a higher classification performance than resting states. The best model for the 4-class classification was cKNN. The highest accuracy using resting state data was 67.24%, while it was 93.10% using memory encoding state data. This study involving participants with SCD, naMCI, aMCI, and AD focused on early Alzheimer’s diagnosis. The research used EEG data during resting and memory encoding states to classify these groups, demonstrating the significance of cognitive process-related brain waves for diagnosis. The computer-based cognitive task introduced in the study offers a time-efficient alternative to traditional neuropsychological tests, showing a strong correlation with their results and serving as a valuable tool to assess cognitive impairment with reduced bias.

Electroencephalographic slowing during REM sleep in older adults with subjective cognitive impairment and mild cognitive impairment.

In older adults with Alzheimer's disease, slowing of electroencephalographic (EEG) activity during REM sleep has been observed. Few studies have examined EEG slowing during REM in those with mild cognitive impairment (MCI) and none have examined its relationship with cognition in this at-risk population. Two hundred and ten older adults (mean age = 67.0, SD = 8.2 years) underwent comprehensive neuropsychological, medical, and psychiatric assessment and overnight polysomnography. Participants were classified as subjective cognitive impairment (SCI; n = 75), non-amnestic MCI (naMCI, n = 85), and amnestic MCI (aMCI, n = 50). REM EEG slowing was defined as (δ + θ)/(α + σ + β) power and calculated for frontal, central, parietal, and occipital regions. Analysis of variance compared REM EEG slowing between groups. Correlations between REM EEG slowing and cognition, including learning and memory, visuospatial and executive functions, were examined within each subgroup. The aMCI group had significantly greater REM EEG slowing in the parietal and occipital regions compared to the naMCI and SCI groups (partial η2 = 0.06, p < 0.05 and 0.06, p < 0.05, respectively), and greater EEG slowing in the central region compared to SCI group (partial η2 = 0.03, p < 0.05). Greater REM EEG slowing in parietal (r = -0.49) and occipital regions (r = -0.38 [O1/M2] and -0.33 [O2/M1]) were associated with poorer visuospatial performance in naMCI. REM EEG slowing may differentiate older adults with memory impairment from those without. Longitudinal studies are now warranted to examine the prognostic utility of REM EEG slowing for cognitive and dementia trajectories.