Deep insights into MCI diagnosis: A comparative deep learning analysis of EEG time series

BACKGROUND

Individuals in the early stages of Alzheimer's Disease (AD) are typically diagnosed with Mild Cognitive Impairment (MCI). MCI represents a transitional phase between normal cognitive function and AD. Electroencephalography (EEG) records carry valuable insights into cerebral cortex brain activities to analyze neuronal degeneration. To enhance the precision of dementia diagnosis, automatic and intelligent methods are required for the analysis and processing of EEG signals.

NEW METHODS

This paper aims to address the challenges associated with MCI diagnosis by leveraging EEG signals and deep learning techniques. The analysis in this study focuses on processing the information embedded within the sequence of raw EEG time series data. EEG recordings are collected from 10 Healthy Controls (HC) and 10 MCI participants using 19 electrodes during a 30 min eyes-closed session. EEG time series are transformed into 2 separate formats of input tensors and applied to deep neural network architectures. Convolutional Neural Network (CNN) and ResNet from scratch are performed with 2D time series with different segment lengths. Furthermore, EEGNet and DeepConvNet architectures are utilized for 1D time series.

RESULTS

ResNet demonstrates superior effectiveness in detecting MCI when compared to CNN architecture. Complete discrimination is achieved using EEGNet and DeepConvNet for noisy segments.

COMPARISON WITH EXISTING METHODS

ResNet has yielded a 3 % higher accuracy rate compared to CNN. None of the architectures in the literature have achieved 100 % accuracy except proposed EEGNet and DeepConvnet.

CONCLUSION

Deep learning architectures hold great promise in enhancing the accuracy of early MCI detection.

The analysis of gestural and verbal pragmatic markers produced by Mild Cognitive Impaired participants during longitudinal and autobiographical interviews

CONTEXT

This corpus-based study presents a multimodal analysis of verbal pragmatic markers and non-verbal pragmatic markers in elderly people with Mild Cognitive Impairment aged over 75 years.

METHODS

The corpus collection and analysis methodology has been described in the Belgian CorpAGEst transversal study and the French VintAGE longitudinal and transversal oriented pilot studies. The protocols are available online in both English and French.

RESULTS & CONCLUSION

Our general findings indicate that with ageing, verbal pragmatic markers acquire an interactive function that allows people with MCI to maintain intersubjective relationships with their interlocutor. Furthermore, at the non-verbal level, gestural manifestations are increasingly used over time with a preference for non-verbal pragmatic markers with a referential function and an adaptive function. We aim to show the benefits of linguistic and interactional scientific investigation methods through cognitive impaired ageing for clinicians and family caregivers.

Cognitive and Neuropathophysiological Outcomes of Gamma-tACS in Dementia: A Systematic Review

Despite the numerous pharmacological interventions targeting dementia, no disease-modifying therapy is available, and the prognosis remains unfavorable. A promising perspective involves tackling high-frequency gamma-band (> 30 Hz) oscillations involved in hippocampal-mediated memory processes, which are impaired from the early stages of typical Alzheimer's Disease (AD). Particularly, the positive effects of gamma-band entrainment on mouse models of AD have prompted researchers to translate such findings into humans using transcranial alternating current stimulation (tACS), a methodology that allows the entrainment of endogenous cortical oscillations in a frequency-specific manner. This systematic review examines the state-of-the-art on the use of gamma-tACS in Mild Cognitive Impairment (MCI) and dementia patients to shed light on its feasibility, therapeutic impact, and clinical effectiveness. A systematic search from two databases yielded 499 records resulting in 10 included studies and a total of 273 patients. The results were arranged in single-session and multi-session protocols. Most of the studies demonstrated cognitive improvement following gamma-tACS, and some studies showed promising effects of gamma-tACS on neuropathological markers, suggesting the feasibility of gamma-tACS in these patients anyhow far from the strong evidence available for mouse models. Nonetheless, the small number of studies and their wide variability in terms of aims, parameters, and measures, make it difficult to draw firm conclusions. We discuss results and methodological limitations of the studies, proposing possible solutions and future avenues to improve research on the effects of gamma-tACS on dementia.

The Effects of Music-Based Auditory Training on Hearing-Impaired Older Adults With Mild Cognitive Impairment

OBJECTIVES

The present study aimed to determine the effect of music-based auditory training on older adults with hearing loss and decreased cognitive ability, which are common conditions in the older population.

METHODS

In total, 20 older adults diagnosed with both mild-to-moderately severe hearing loss and mild cognitive impairment (MCI) participated. Half of this group were randomly assigned to the auditory training group (ATG), and the other half were designated as the control group (CG). For the ATG, a 40-minute training session (10 minutes for singing a song, 15 minutes for playing instruments, and 15 minutes for playing games with music discrimination) was conducted twice a week for 8 weeks (for a total of 16 sessions). To confirm the training effects, all participants were given tests pre- and post-training, and then a follow-up test was administered 2 weeks after the training, using various auditory and cognitive tests and a self-reporting questionnaire.

RESULTS

The ATG demonstrated significant improvement in all auditory test scores compared to the CG. Additionally, there was a notable enhancement in cognitive test scores post-training, except for the digit span tests. However, there was no statistically significant difference in the questionnaire scores between the two groups, although the ATG did score higher post-training.

CONCLUSION

The music-based auditory training resulted in a significant improvement in auditory function and a partial enhancement in cognitive ability among elderly patients with hearing loss and MCI. We anticipate that this music-based approach will be adopted for auditory training in clinical settings due to its engaging and easy-to-follow nature.

Unsupervised Online Paired Associates Learning Task from the Cambridge Neuropsychological Test Automated Battery (CANTAB®) in the Brain Health Registry

BACKGROUND

Unsupervised online cognitive assessments have demonstrated promise as an efficient and scalable approach for evaluating cognition in aging, and Alzheimer's disease and related dementias.

OBJECTIVES

The aim of this study was to evaluate the feasibility, usability, and construct validity of the Paired Associates Learning task from the Cambridge Neuropsychological Test Automated Battery® in adults enrolled in the Brain Health Registry.

DESIGN, SETTING, PARTICIPANTS, MEASUREMENTS

The Paired Associates Learning task was administered to Brain Health Registry participants in a remote, unsupervised, online setting. In this cross-sectional analysis, we 1) evaluated construct validity by analyzing associations between Paired Associates Learning performance and additional participant registry data, including demographics, self- and study partner-reported subjective cognitive change (Everyday Cognition scale), self-reported memory concern, and depressive symptom severity (Patient Health Questionnaire-9) using multivariable linear regression models; 2) determined the predictive value of Paired Associates Learning and other registry variables for identifying participants who self-report Mild Cognitive Impairment by employing multivariable binomial logistic regressions and calculating the area under the receiver operator curve; 3) investigated feasibility by looking at task completion rates and statistically comparing characteristics of task completers and non-completers; and 4) evaluated usability in terms of participant requests for support from BHR related to the assessment.

RESULTS

In terms of construct validity, in participants who took the Paired Associates Learning for the first time (N=14,528), worse performance was associated with being older, being male, lower educational attainment, higher levels of self- and study partner-reported decline, more self-reported memory concerns, greater depressive symptom severity, and self-report of Mild Cognitive Impairment. Paired Associates Learning performance and Brain Health Registry variables together identified those with self-reported Mild Cognitive Impairment with moderate accuracy (areas under the curve: 0.66-0.68). In terms of feasibility, in a sub-sample of 29,176 participants who had the opportunity to complete Paired Associates Learning for the first time in the registry, 14,417 started the task. 11,647 (80.9% of those who started) completed the task. Compared to those who did not complete the task at their first opportunity, those who completed were older, had more years of education, more likely to self-identify as White, less likely to self-identify as Latino, less likely to have a subjective memory concern, and more likely to report a family history of Alzheimer's disease. In terms of usability, out of 8,395 received requests for support from BHR staff via email, 4.4% (n=374) were related to PAL. Of those, 82% were related to technical difficulties.

CONCLUSIONS

Our findings support moderate feasibility, good usability, and construct validity of cross-sectional Paired Associates Learning in an unsupervised online registry, but also highlight the need to make the assessment more inclusive and accessible to individuals from ethnoculturally and socioeconomically diverse communities. A future, improved version could be a scalable, efficient method to assess cognition in many different settings, including clinical trials, observational studies, healthcare, and public health.

A Deep Learning-Based Ensemble Method for Early Diagnosis of Alzheimer's Disease using MRI Images

Recently, the early diagnosis of Alzheimer's disease has gained major attention due to the growing prevalence of the disease and the resulting costs imposed on individuals and society. The main objective of this study was to propose an ensemble method based on deep learning for the early diagnosis of AD using MRI images. The methodology of this study consisted of collecting the dataset, preprocessing, creating the individual and ensemble models, evaluating the models based on ADNI data, and validating the trained model based on the local dataset. The proposed method was an ensemble approach selected through a comparative analysis of various ensemble scenarios. Finally, the six best individual CNN-based classifiers were selected to combine and constitute the ensemble model. The evaluation showed an accuracy rate of 98.57, 96.37, 94.22, 99.83, 93.88, and 93.92 for NC/AD, NC/EMCI, EMCI/LMCI, LMCI/AD, four-way and three-way classification groups, respectively. The validation results on the local dataset revealed an accuracy of 88.46 for three-way classification. Our performance results were higher than most reviewed studies and comparable with others. Although comparative analysis showed superior results of ensemble methods against individual architectures, there were no significant differences among various ensemble approaches. The validation results revealed the low performance of individual models in practice. In contrast, the ensemble method showed promising results. However, further studies on various and larger datasets are required to validate the generalizability of the model.

A digital health home intervention for people within the Alzheimer's disease continuum: results from the Ability-TelerehABILITation pilot randomized controlled trial

PURPOSE

This study tested the efficacy of digital-health home intervention for people within the Alzheimer's disease (AD)-continuum.

METHODS

Thirty people within the AD continuum were randomly assigned to a telerehabilitation (ABILITY; 6 males, M_age=78.2 ± 3.95) or treatment as usual (TAU; 8 males, M_age=77.13 ± 6.38), performing cognitive and physical activities at home for six weeks. The ABILITY intervention additionally included a digital platform enabling communication between the hospital and the patient's home. Efficiency, such as adherence, perceived fit of demands and skills, usability, and effectiveness measures, including neuropsychological level, neuropsychiatric symptoms, and autonomy in daily living, were collected before (T0), after the treatment (T1), and at the 1-year-follow-up (T2).

RESULTS

The ABILITY program was efficient, with a higher adherence (81% vs. 62%), a higher perceived fit of demands and skills than TAU (p<.05), and a good level of technology usability. In terms of effectiveness, a treatment effect (ABILITY > TAU) emerged on the global cognitive level, especially in language, executive functions, and memory domains. Moreover, a treatment carry-over effect (1-year follow-up) was observed in global cognitive functions (especially language) (ABILITY > TAU), behavioral symptoms, and caregiver distress (TAU > ABILITY).

CONCLUSIONS

Our preliminary findings suggest that ABILITY is a promising eHealth intervention to improve at-home treatment adherence and to preserve cognitive and behavioral abilities.

Functional connectivity changes in mild cognitive impairment: A meta-analysis of M/EEG studies

OBJECTIVE

Early synchrony alterations have been observed through electrophysiological techniques in Mild Cognitive Impairment (MCI), which is considered the intermediate phase between healthy aging (HC) and Alzheimer's disease (AD). However, the documented direction (hyper/hypo-synchronization), regions and frequency bands affected are inconsistent. This meta-analysis intended to elucidate existing evidence linked to potential neurophysiological biomarkers of AD.

METHODS

We conducted a random-effects meta-analysis that entailed the unbiased inclusion of Non-statistically Significant Unreported Effect Sizes ("MetaNSUE") of electroencephalogram (EEG) and magnetoencephalogram (MEG) studies investigating functional connectivity changes at rest along the healthy-pathological aging continuum, searched through PubMed, Scopus, Web of Science and PsycINFO databases until June 2023.

RESULTS

Of the 3852 articles extracted, we analyzed 12 papers, and we found an alpha synchrony decrease in MCI compared to HC, specifically between temporal-parietal (d = -0.26) and frontal-parietal areas (d = -0.25).

CONCLUSIONS

Alterations of alpha synchrony are present even at MCI stage.

SIGNIFICANCE

Synchrony measures may be promising for the detection of the first hallmarks of connectivity alterations, even at the prodromal stages of the AD, before clinical symptoms occur.

Neuropsychiatric disturbances in mild cognitive impairment: A scientometric analysis

Behavioral and psychological symptoms of dementia (BPSD) have been extensively studied in dementia than its prodromal stage, known as mild cognitive impairment (MCI). A scientometric study on BPSD in MCI would be valuable in synthesizing the existing body of research and providing insights into the trends, networks, and influencers within this area. We searched for related literature in the Web of Science database and extracted complete text and citation records of each publication. The primary objective was to map the research evolution of BPSD in MCI and highlight dominant research themes. The secondary objective was to identify research network characteristics (authors, journals, countries, and institutions) and abundances. A total of 12,369 studies published between 1980 and 2022 were included in the analysis. We found 51 distinct clusters from the co-cited reference network that were highly credible with significant modularity (Q = 0.856) and silhouette scores (S = 0.932). Five major research domains were identified: symptoms, diagnosis, brain substrates, biochemical pathways, and interventions. In recent years, the research focus in this area has been on gut microbiota, e-health, COVID-19, cognition, and delirium. Collectively, findings from this scientometric analysis can help clarify the scope and direction of future research and clinical practices.

Novel fluid biomarkers for mild cognitive impairment: A systematic review and meta-analysis

Mild cognitive impairment (MCI) is a well-established prodromal stage of dementia (e.g., Alzheimer's disease) that is often accompanied by early signs of neurodegeneration. To facilitate a better characterization of the underlying pathophysiology, we assessed the available literature to evaluate potential fluid biomarkers in MCI. Peer-reviewed articles that measured cerebrospinal fluid (CSF) and/or peripheral biomarkers of neuronal injury (total-tau [T-tau], neurofilament light chain [NfL], heart-type fatty acid binding protein [HFABP], neuron-specific enolase, ubiquitin C-terminal hydrolase L1) and/or astroglial pathology (glial fibrillary acidic protein [GFAP], S100 calcium-binding protein B) in MCI and healthy controls were assessed. Group differences were summarized by standardized mean differences (SMDs) and 95% confidence intervals calculated using a random-effects model. Heterogeneity was quantified using I2. A total of 107 studies were included in the meta-analysis and 10 studies were qualitatively reviewed. In CSF, concentrations of NfL (SMD = 0.69 [0.56, 0.83]), GFAP (SMD = 0.41 [0.07, 0.75]), and HFABP (SMD = 0.57 [0.26, 0.89]) were elevated in MCI. In blood, increased concentrations of T-tau (SMD = 0.19 [0.09, 0.29]), NfL (SMD = 0.41 [0.32, 0.49]), and GFAP (SMD = 0.39 [0.23, 0.55]) were found in MCI. Heterogeneity that was identified in all comparisons was explored using meta-regression and subgroup analysis. Elevated NfL and GFAP can be detected in both CSF and peripheral blood. Monitoring these biomarkers in clinical settings may provide important insight into underlying neurodegenerative processes in MCI.

Class-Balanced Deep Learning with Adaptive Vector Scaling Loss for Dementia Stage Detection

Alzheimer's disease (AD) leads to irreversible cognitive decline, with Mild Cognitive Impairment (MCI) as its prodromal stage. Early detection of AD and related dementia is crucial for timely treatment and slowing disease progression. However, classifying cognitive normal (CN), MCI, and AD subjects using machine learning models faces class imbalance, necessitating the use of balanced accuracy as a suitable metric. To enhance model performance and balanced accuracy, we introduce a novel method called VS-Opt-Net. This approach incorporates the recently developed vector-scaling (VS) loss into a machine learning pipeline named STREAMLINE. Moreover, it employs Bayesian optimization for hyperparameter learning of both the model and loss function. VS-Opt-Net not only amplifies the contribution of minority examples in proportion to the imbalance level but also addresses the challenge of generalization in training deep networks. In our empirical study, we use MRI-based brain regional measurements as features to conduct the CN vs MCI and AD vs MCI binary classifications. We compare the balanced accuracy of our model with other machine learning models and deep neural network loss functions that also employ class-balanced strategies. Our findings demonstrate that after hyperparameter optimization, the deep neural network using the VS loss function substantially improves balanced accuracy. It also surpasses other models in performance on the AD dataset. Moreover, our feature importance analysis highlights VS-Opt-Net's ability to elucidate biomarker differences across dementia stages.

A Correlative Relationship Between Heart Failure and Cognitive Impairment: A Narrative Review

Heart failure (HF) is a chronic condition affecting millions of people worldwide. While the cardinal manifestations of HF are related to the cardiovascular system, it has become progressively evident that mild cognitive impairment (MCI) is also a significant complication of the disease. In fact, a significant number of patients with HF may experience MCI, which can manifest as deficits in attention, memory, executive function, and processing speed. The mechanisms responsible for cognitive dysfunction in HF are intricate and multifactorial. Possible factors contributing to this condition include decreased cerebral blood flow, thrombogenicity associated with HF, systemic inflammatory conditions, and proteotoxicity. MCI in HF has significant clinical implications, as it is linked to poorer quality of life, increased morbidity and mortality, and higher healthcare costs. Additionally, MCI can disrupt self-care behaviors, adherence to medication, and decision-making abilities, all of which are crucial for effectively managing HF. However, there is currently no gold standard diagnostic tool and follow-up strategy for MCI in HF patients. There is limited knowledge on the prevention and treatment of MCI. In conclusion, MCI is a common and clinically important complication of HF. Considering the substantial influence of MCI on patient outcomes, it is imperative for healthcare providers to be cognizant of this issue and integrate cognitive screening and management strategies into the care of HF patients.

Effect of Tablet-based Cognitive Intervention on Cognition in Patients With Mild Cognitive Impairment: A Pilot Study

Background and Purpose

Growing evidence has shown that cognitive interventions can mitigate cognitive decline in patients with mild cognitive impairment (MCI). However, most previous cognitive interventions have been group-based programs. Due to their intrinsic limitations, group-based programs are not widely used in clinical practice. Therefore, we have developed a tablet-based cognitive intervention program. This preliminary study investigated the feasibility and effects of a 12-week structured tablet-based program on cognitive function in patients with MCI.

Methods

We performed a single-arm study on 24 patients with MCI. The participants underwent a tablet-based cognitive intervention program 5 times a week over a 12-week period. The primary outcome was changes in cognitive function, measured using the Korean version of the Consortium to Establish a Registry for Alzheimer's Disease Assessment Packet (CERAD-K). Outcomes were evaluated at baseline, within two weeks of the last program (post-intervention), and at the six-month follow-up session.

Results

The completion rate of the tablet-based program was 83.3% in patients with MCI. The program improved cognitive function based on the CERAD-K total score (p=0.026), which was maintained for at least three months (p=0.004). There was also an improvement in the depression scale score (p=0.002), which persisted for three months (p=0.027).

Conclusions

Our 12-week structured tablet-based program is feasible for patients with MCI. Furthermore, although further studies with a double-arm design are required, the program appears to be an effective strategy to prevent cognitive decline in patients with MCI.

REM sleep is associated with the volume of the cholinergic basal forebrain in aMCI individuals

BACKGROUND

Rapid-eye movement (REM) sleep highly depends on the activity of cholinergic basal forebrain (BF) neurons and is reduced in Alzheimer's disease. Here, we investigated the associations between the volume of BF nuclei and REM sleep characteristics, and the impact of cognitive status on these links, in late middle-aged and older participants.

METHODS

Thirty-one cognitively healthy controls (66.8 ± 7.2 years old, 13 women) and 31 participants with amnestic Mild Cognitive Impairment (aMCI) (68.3 ± 8.8 years old, 7 women) were included in this cross-sectional study. All participants underwent polysomnography, a comprehensive neuropsychological assessment and Magnetic Resonance Imaging examination. REM sleep characteristics (i.e., percentage, latency and efficiency) were derived from polysomnographic recordings. T1-weighted images were preprocessed using CAT12 and the DARTEL algorithm, and we extracted the gray matter volume of BF regions of interest using a probabilistic atlas implemented in the JuBrain Anatomy Toolbox. Multiple linear regressions were performed between the volume of BF nuclei and REM sleep characteristics controlling for age, sex and total intracranial volume, in the whole cohort and in subgroups stratified by cognitive status.

RESULTS

In the whole sample, lower REM sleep percentage was significantly associated to lower nucleus basalis of Meynert (Ch4) volume (β = 0.32, p = 0.009). When stratifying the cohort according to cognitive status, lower REM sleep percentage was significantly associated to both lower Ch4 (β = 0.48, p = 0.012) and total BF volumes (β = 0.44, p = 0.014) in aMCI individuals, but not in cognitively unimpaired participants. No significant associations were observed between the volume of the BF and wake after sleep onset or non-REM sleep variables.

DISCUSSION

These results suggest that REM sleep disturbances may be an early manifestation of the degeneration of the BF cholinergic system before the onset of dementia, especially in participants with mild memory deficits.

Safety and feasibility of transcutaneous vagus nerve stimulation in mild cognitive impairment: VINCI-AD study protocol

BACKGROUND

Over 55 million adults are living with dementia globally, which is projected to reach 157 million by 2050. Mild cognitive impairment (MCI), a syndrome of memory impairment with intact activities of daily living, may precede dementia by several years. Around 5-15% of individuals with MCI convert to dementia annually. Novel treatments which delay progression of MCI to dementia are urgently needed. Transcutaneous vagal nerve stimulation (tVNS) is a non-invasive neuromodulation technique that targets the vagus nerve. Importantly, tVNS has been shown to improve cognition in healthy volunteers, but has not been extensively examined as a potential therapeutic approach in MCI. VINCI-AD will examine the safety and feasibility of tVNS in older adults with MCI.

DESIGN

VINCI-AD is an investigator-led, single-site, single-blind, sham-controlled crossover pilot study which aims to assess the safety and feasibility of tVNS in 40 participants with amnestic MCI. All participants will attend for three consecutive study visits during which they will be randomised to receive no stimulation (baseline), active tVNS stimulation (stimulation at cymba conchae of left ear) or sham tVNS stimulation (at earlobe). Safety will be primarily assessed by ascertainment of adverse events. Further safety assessment will examine the impact of acute tVNS on subjective (orthostatic symptoms), peripheral (finometry-based blood pressure) and central (assessed via Near Infrared Spectroscopy [NIRS]) haemodynamic responses to active stand. Feasibility will be determined using a custom-designed occupational assessment of device usability. Exploratory secondary analysis in VINCI-AD will examine the potential impact of acute tVNS on associative memory, spatial memory and inhibitory control to inform sample size estimates for future trials of tVNS in older adults with MCI.

DISCUSSION

VINCI-AD will report on the safety (adverse events/haemodynamic responses to active stand) and feasibility of tVNS as a potential therapeutic option in MCI. Detailed reporting of study eligibility and completion rates will be reported. Exploratory analysis will examine the potential cognitive benefits of acute tVNS on cognitive function in MCI to report potential effect sizes that may inform future clinical trials in this cohort.

TRIAL REGISTRATION

https://clinicaltrials.gov/ct2/show/NCT05514756 . Trial Registration Number NCT05514756 (24th August 2022 for this protocol, version 1.0.).

A Feasibility Study of AlzLife 40 Hz Sensory Therapy in Patients with MCI and Early AD

Alzheimer's Disease (AD) and Mild Cognitive Impairment (MCI) are debilitating diseases that affect millions of individuals and have notoriously limited treatment options. One emerging therapy, non-invasive 40 Hz sensory therapy delivered through light and sound has previously shown promise in improving cognition in Alzheimer Disease (AD) rodent models. Small studies in humans have proven safe and tolerable, however exploration of feasibility and utility is limited. The purpose of this study is to examine the feasibility of this treatment in a human population through a smart tablet application that emits light and sound waves at 40 Hz to the user over the span of 1 h a day. Confirmation of entrainment of 40 Hz stimulation in the cerebral cortex was performed via EEG. 27 preliminary subjects with subjective cognitive complaints, Mild Cognitive Impairment, or AD were enrolled in the study; 11 participants completed 6 months of therapy. Of those that discontinued treatment, other health issues and difficulties with compliance were the most common causes. Participants were followed with Montreal Cognitive Assessment (MOCA) and Boston Cognitive Assessment (BOCA). For participants with subjective cognitive complaints, 2 of the 4 had improved MOCA score and 1 of 4 had improved BOCA score. For the participant with MCI, his MOCA score improved. For AD participants, 2 out of 6 had improved MOCA score and 3 of the 6 stayed stable, while 3 of 6 BOCA score improved. 4 of 11 participants specifically increased their MOCA scores in the Memory Index section. Of the 8 participants/caregivers able to speak to perceived usefulness of the study, 6 spoke to at least some level of benefit. Of these 6, 2 enrolled with subjective cognitive complaint, 1 had MCI, and 3 had AD. The therapy did not have reported side effects. However, those who did not finish the study experienced issues obtaining and operating a smart tablet independently as well as complying with the therapy. Overall, further exploration of this treatment modalities efficacy is warranted.

Results from the SYNERGIC trial

Changes in functional brain connectivity (FBC) may indicate how lifestyle modifications can prevent the progression to dementia; FBC identifies areas that are spatially separate but temporally synchronized in their activation and is altered in those with mild cognitive impairment (MCI), a prodromal state between healthy cognitive aging and dementia. Participants with MCI were randomly assigned to one of five study arms. Three times per week for 20-weeks, participants performed 30-min of (control) cognitive training, followed by 60-min of (control) physical exercise. Additionally, a vitamin D₃ (10,000 IU/pill) or a placebo capsule was ingested three times per week for 20-weeks. Using the CONN toolbox, we measured FBC change (Post-Pre) across four statistical models that collapsed for and/or included some or all study arms. We conducted Pearson correlations between FBC change and changes in physical and cognitive functioning. Our sample included 120 participants (mean age: 73.89 ± 6.50). Compared to the pure control, physical exercise (model one; p-False Discovery Rate (FDR) < 0.01 & < 0.05) with cognitive training (model two; p-FDR =  < 0.001), and all three interventions combined (model four; p-FDR =  < 0.01) demonstrated an increase in FBC between regions of the Default-Mode Network (i.e., hippocampus and angular gyrus). After controlling for false discovery rate, there were no significant correlations between change in connectivity and change in cognitive or physical function. Physical exercise alone appears to be as efficacious as combined interventional strategies in altering FBC, but implications for behavioral outcomes remain unclear.

Sex and gender differences in Alzheimer's disease, Parkinson's disease, and Amyotrophic Lateral Sclerosis: a narrative review

Neurodegenerative diseases (NDs), including Alzheimer's disease (AD), Parkinson's disease (PD), and amyotrophic lateral sclerosis (ALS), exhibit high phenotypic variability and they are very common in the general population. These diseases are associated with poor prognosis and a significant burden on patients and their caregivers. Although increasing evidence suggests that biological sex is an important factor for the development and phenotypical expression of some NDs, the role of sex and gender in the diagnosis and prognosis of NDs has been poorly explored. Current knowledge relating to sex- and gender-related differences in the epidemiology, clinical features, biomarkers, and treatment of AD, PD, and ALS will be summarized in this narrative review. The cumulative evidence hitherto collected suggests that sex and gender are factors to be considered in explaining the heterogeneity of these NDs. Clarifying the role of sex and gender in AD, PD, and ALS is a key topic in precision medicine, which will facilitate sex-specific prevention and treatment strategies to be implemented in the near future.

Sleep movements and respiratory coupling as a biobehavioral metric for early Alzheimer's disease in independently dwelling adults

INTRODUCTION

Sleep disorder is often the first symptom of age-related cognitive decline associated with Alzheimer's disease (AD) observed in primary care. The relationship between sleep and early AD was examined using a patented sleep mattress designed to record respiration and high frequency movement arousals. A machine learning algorithm was developed to classify sleep features associated with early AD.

METHOD

Community-dwelling older adults (N = 95; 62-90 years) were recruited in a 3-h catchment area. Study participants were tested on the mattress device in the home bed for 2 days, wore a wrist actigraph for 7 days, and provided sleep diary and sleep disorder self-reports during the 1-week study period. Neurocognitive testing was completed in the home within 30-days of the sleep study. Participant performance on executive and memory tasks, health history and demographics were reviewed by a geriatric clinical team yielding Normal Cognition (n = 45) and amnestic MCI-Consensus (n = 33) groups. A diagnosed MCI group (n = 17) was recruited from a hospital memory clinic following diagnostic series of neuroimaging biomarker assessment and cognitive criteria for AD.

RESULTS

In cohort analyses, sleep fragmentation and wake after sleep onset duration predicted poorer executive function, particularly memory performance. Group analyses showed increased sleep fragmentation and total sleep time in the diagnosed MCI group compared to the Normal Cognition group. Machine learning algorithm showed that the time latency between movement arousals and coupled respiratory upregulation could be used as a classifier of diagnosed MCI vs. Normal Cognition cases. ROC diagnostics identified MCI with 87% sensitivity; 89% specificity; and 88% positive predictive value.

DISCUSSION

AD sleep phenotype was detected with a novel sleep biometric, time latency, associated with the tight gap between sleep movements and respiratory coupling, which is proposed as a corollary of sleep quality/loss that affects the autonomic regulation of respiration during sleep. Diagnosed MCI was associated with sleep fragmentation and arousal intrusion.

Whole blood transcript and protein abundance of the vascular endothelial growth factor family relate to cognitive performance

The vascular endothelial growth factor (VEGF) family of genes has been implicated in the clinical development of Alzheimer's Disease (AD). A previous study identified associations between gene expression of VEGF family members in the prefrontal cortex and cognitive performance and AD pathology. This study explored if those associations were also observed in the blood. Consistent with previous observations in brain tissue, higher blood gene expression of placental growth factor (PGF) was associated with a faster rate of memory decline (p=0.04). Higher protein abundance of FMS-related receptor tyrosine kinase 4 (FLT4) in blood was associated with biomarker levels indicative of lower amyloid and tau pathology, opposite the direction observed in brain. Also, higher gene expression of VEGFB in blood was associated with better baseline memory (p=0.008). Notably, we observed that higher gene expression of VEGFB in blood was associated with lower expression of VEGFB in the brain (r=-0.19, p=0.02). Together, these results suggest that the VEGFB, FLT4, and PGF alterations in the AD brain may be detectable in the blood compartment.

Psychosocial profiles within community-dwelling older adults with Mild Cognitive Impairment: A prevalence and latent profile analysis study

OBJECTIVES

Mild Cognitive Impairment (MCI) is an at-risk stage for dementia and accurate prevalence studies are lacking in Singapore. From the literature, it is evident that psychosocial factors increase the risk of conversion to dementia. In this study, we sought to establish the prevalence of MCI in Singapore and study the associated psychosocial factors using latent profile analysis.

METHOD

902 community-dwelling older adults, aged between 60 and 99 years old (Mage = 70.48 years), were recruited as part of the Community Health and Intergenerational Study (CHI). They completed neurocognitive assessments and questionnaires on depression and anxiety symptoms, quality of life, social support, satisfaction with life, and social connectivity. Petersen's criteria was used to diagnose MCI. Within the MCI sample, 166 subjects' psychosocial scores were entered into a latent profile analysis to identify profiles of psychosocial functioning.

RESULTS

The prevalence of MCI in our sample was 21.5%. They had significantly lower years of education and perceived social support and higher depressive symptoms than the normal ageing group. Three distinct profiles emerged within the MCI group corresponding to a positive (45.2%), neutral (38.5%), and negative (16.3%) pattern of psychosocial scores. These profiles did not differ significantly in terms of demographic or cognitive variables.

DISCUSSION

The three psychosocial profiles might reflect the differing implications of MCI on a person's well-being and the negative psychosocial profile might likely be most at risk of conversion to dementia. Future longitudinal studies are required to confirm these implications.

The Potential Role of Vitamin D Supplementation In Cognitive Impairment Prevention

Background Vitamin D is implicated in many processes in the central nervous system (CNS), such as neurogenesis, neurotransmitter synthesis, synaptogenesis and protection against oxidative stress, thereby exerting a neuroprotective effect. Objective In the present review, we aimed to evaluate the potential benefit(s) of vitamin D supplementation for CNS aging in different clinical contexts. Methods We performed a literature search, looking for clinical trials and randomized clinical trials evaluating the effect of vitamin D supplementation on different endpoints related to cognitive outcomes. Results Firstly, we identified 16 papers dealing with the impact of vitamin D supplementation on cognitive function in healthy subjects; the current literature suggests a real role for vitamin D supplementation in the prevention of cognitive decay in this clinical setting. Conversely, two papers suggest that vitamin D supplementation may be beneficial in patients with mild cognitive impairment (MCI). Finally, current data on vitamin D in Alzheimer's disease are contradictory. Conclusion Vitamin D supplementation may improve the cognitive outcomes of patients with MCI, whereas there is no evidence that it may prevent dementia or modulate the course of Alzheimer's disease.

Psychometric properties of the Alzheimer's Disease Cooperative Study - Activities of Daily Living for Mild Cognitive Impairment (ADCS-MCI-ADL) scale: a post hoc analysis of the ADCS ADC-008 trial

BACKGROUND

The Alzheimer's Disease Cooperative Study - Activities of Daily Living Scale for use in Mild Cognitive Impairment (MCI), the ADCS-ADL-MCI, is an evaluation scale with information provided by an informant/caregiver to describe the functional impairment of patients with MCI. As the ADCS-ADL-MCI has yet to undergo a full psychometric evaluation, this study aimed to evaluate the measurement properties of the ADCS-ADL-MCI in subjects with amnestic MCI.

METHODS

Measurement properties, including item-level analysis, internal consistency reliability, test-retest reliability, construct validity (convergent/discriminant, known-groups validity), and responsiveness were evaluated using data from the ADCS ADC-008 trial, a 36-month, multicenter, placebo-controlled study in 769 subjects with amnestic MCI (defined by clinical criteria and a global clinical dementia rating, CDR, score of 0.5). Due to most subjects' mild condition at baseline and resulting low variance in scores, psychometric properties were assessed using both baseline and 36-month data.

RESULTS

Ceiling effects were not apparent at the total score level, with 3% of the cohort reaching the maximum score of 53, despite most subjects having a relatively high score at baseline (mean score = 46.0 [standard deviation = 4.8]). Item-total correlations were overall weak at baseline, most likely due to low variability in responses; however, at month 36, good item homogeneity was found. Cronbach's alpha values ranged from acceptable (0.64 at baseline) to good (0.87 at month 36), indicating overall very good internal consistency reliability. Further, moderate to good test-retest reliability was found (intraclass correlation coefficients ranging from 0.62-0.73). The analyses also largely supported convergent/discriminant validity, especially at month 36. Finally, the ADCS-ADL-MCI discriminated well between groups showing good known-groups validity, and was responsive in patients who indicated a longitudinal change in other instruments.

CONCLUSIONS

This study provides a comprehensive psychometric evaluation of the ADCS-ADL-MCI. Findings suggest that the ADCS-ADL-MCI is a reliable, valid and responsive measure capable of capturing functional abilities in patients with amnestic MCI.

TRIAL REGISTRATION

ClinicalTrials.gov Identifier: NCT00000173.

Based on Tau PET Radiomics Analysis for the Classification of Alzheimer's Disease and Mild Cognitive Impairment

Alzheimer's Disease (AD) and Mild Cognitive Impairment (MCI) are closely associated with Tau proteins accumulation. In this study, we aimed to implement radiomics analysis to discover high-order features from pathological biomarker and improve the classification accuracy based on Tau PET images. Two cross-racial independent cohorts from the ADNI database (121 AD patients, 197 MCI patients and 211 normal control (NC) subjects) and Huashan hospital (44 AD patients, 33 MCI patients and 36 NC subjects) were enrolled. The radiomics features of Tau PET imaging of AD related brain regions were computed for classification using a support vector machine (SVM) model. The radiomics model was trained and validated in the ADNI cohort and tested in the Huashan hospital cohort. The standard uptake value ratio (SUVR) and clinical scores model were also performed to compared with radiomics analysis. Additionally, we explored the possibility of using Tau PET radiomics features as a good biomarker to make binary identification of Tau-negative MCI versus Tau-positive MCI or apolipoprotein E (ApoE) ε4 carrier versus ApoE ε4 non-carrier. We found that the radiomics model demonstrated best classification performance in differentiating AD/MCI patients and NC in comparison to SUVR and clinical scores models, with an accuracy of 84.8 ± 4.5%, 73.1 ± 3.6% in the ANDI cohort. Moreover, the radiomics model also demonstrated greater performance in diagnosing AD than other methods in the Huashan hospital cohort, with an accuracy of 81.9 ± 6.1%. In addition, the radiomics model also showed the satisfactory classification performance in the MCI-tau subgroup experiment (72.3 ± 3.5%, 71.9 ± 3.6% and 63.7 ± 5.9%) and in the MCI-ApoE subgroup experiment (73.5 ± 4.3%, 70.1 ± 3.9% and 62.5 ± 5.4%). In conclusion, our study showed that based on Tau PET radiomics analysis has the potential to guide and facilitate clinical diagnosis, further providing evidence for identifying the risk factors in MCI patients.

Cognitive impairment with Type 2 Diabetes Mellitus among community-dwelling older adults in Chile: Prevalence, risk factors and cognitive characteristics

Introduction

The aim of this study is to determine prevalence and risk factors of Cognitive Impairment (CI) and its association with Type 2 Diabetes Mellitus (T2DM) in subjects aged 65 years and above. Additionally, we attempt to provide a cognitive profile for T2DM group.

Methodology

A cross-sectional analytical study to assess CI was carried out. We evaluated a sample of community-dwelling residents from Chile. All participants underwent a general interview, lifestyle questionnaires and a comprehensive neuropsychological battery. Regression analyses were performed to evaluate risk of CI with T2DM and influencing factors. Results between groups in the different domains of the neuropsychological assessment were compared by Student's t-tests and MANOVA.

Results

Among all 358 subjects, overall T2DM prevalence were 17.3%. The prevalence of CI was higher in T2DM group compared to the healthy participants (30.7%, p < 0.001). The risk of CI was 2.8 times higher in older people with T2DM compared to older people without the diagnosis. Multiple regression analysis, adjusted for age and gender, demonstrated that age, education, presence of dyslipidemia, and T2DM duration were the predictor variables significantly associated with CI. T2DM group performed worse on global cognitive performance, attention, language, verbal memory, visual memory, visual constructional ability, and executive function. After adjusting for significant covariates from multiple regression analysis, a relationship between "cognition" and T2DM is still observed. Amnesic multi-domain impairment was the specific cognitive identified pattern for T2DM group.

Conclusion

The present study confirms the high prevalence of CI with T2DM among Chilean older adults in a community-based population. T2DM is significantly associated with a higher risk of CI, and age, education, presence of dyslipidemia, and duration of T2DM are risk factors. T2DM patients with CI are impaired in multiple cognitive domains, even after adjusting covariables, resulting in an amnesic multi-domain cognitive profile.

Magnetic resonance imaging Locus Coeruleus abnormality in amnestic Mild Cognitive Impairment is associated with future progression to dementia

BACKGROUND AND PURPOSE

Human neuropathological studies indicate that the pontine nucleus Locus Coeruleus (LC) undergoes significant and early degeneration in Alzheimer's disease. This line of evidence alongside experimental data suggests that the LC functional/structural decay may represent a critical factor for Alzheimer's disease pathophysiological and clinical progression. In the present prospective study, we used Magnetic Resonance Imaging (MRI) with LC-sensitive sequence (LC-MRI) to investigate in vivo the LC involvement in Alzheimer's disease progression, and whether specific LC-MRI features at baseline are associated with prognosis and cognitive performance in amnestic Mild Cognitive Impairment.

METHODS

LC-MRI parameters were measured at baseline by a template-based method on 3.0-T magnetic resonance images in 34 patients with Alzheimer's disease dementia, 73 patients with amnestic Mild Cognitive Impairment, and 53 cognitively intact individuals. A thorough neurological and neuropsychological assessment was performed at baseline and 2.5-year follow-up.

RESULTS

In subjects with Mild Cognitive Impairment who converted to dementia (n = 32), the LC intensity and number of LC-related voxels were significantly lower than in cognitively intact individuals, resembling those observed in demented patients. Such a reduction was not detected in Mild Cognitive Impairment individuals, who remained stable at follow-up. In Mild Cognitive Impairment subjects converting to dementia, LC-MRI parameter reduction was maximal in the rostral part of the left nucleus. Structural equation modeling analysis showed that LC-MRI parameters positively correlate with cognitive performance.

CONCLUSIONS

Our findings highlight a potential role of LC-MRI for predicting clinical progression in Mild Cognitive Impairment and support the key role of LC degeneration in the Alzheimer clinical continuum.

An explainable Artificial Intelligence approach to study MCI to AD conversion via HD-EEG processing

An explainable Artificial Intelligence (xAI) approach is proposed to longitudinally monitor subjects affected by Mild Cognitive Impairment (MCI) by using high-density electroencephalography (HD-EEG). To this end, a group of MCI patients was enrolled at IRCCS Centro Neurolesi Bonino Pulejo of Messina (Italy) within a follow-up protocol that included two evaluations steps: T0 (first evaluation) and T1 (three months later). At T1, four MCI patients converted to Alzheimer's Disease (AD) and were included in the analysis as the goal of this work was to use xAI to detect individual changes in EEGs possibly related to the degeneration from MCI to AD. The proposed methodology consists in mapping segments of HD-EEG into channel-frequency maps by means of the power spectral density. Such maps are used as input to a Convolutional Neural Network (CNN), trained to label the maps as "T0" (MCI state) or "T1" (AD state). Experimental results reported high intra-subject classification performance (accuracy rate up to 98.97% (95% confidence interval: 98.68-99.26)). Subsequently, the explainability of the proposed CNN is explored via a Grad-CAM approach. The procedure detected which EEG-channels (i.e., head region) and range of frequencies (i.e., sub-bands) were more active in the progression to AD. The xAI analysis showed that the main information is included in the delta sub-band and that, limited to the analyzed dataset, the highest relevant areas are: the left-temporal and central-frontal lobe for Sb01, the parietal lobe for Sb02, the left-frontal lobe for Sb03 and the left-frontotemporal region for Sb04.

Repeatable battery for the assessment of neuropsychological status and its relationship to biomarkers of Alzheimer's disease

The Repeatable Battery for the Assessment of Neuropsychological Status (RBANS) has been associated with commonly used biomarkers of Alzheimer's disease (AD). However, prior studies have typically utilized small and poorly characterized samples, and they have not analyzed the subtests of the RBANS. The current study sought to expand on prior work by examining the relationship between the Indexes and subtest scores of the RBANS and three AD biomarkers: amyloid deposition via positron emission tomography, hippocampal volume via magnetic resonance imaging, and APOE ε4 status.

One-hundred twenty-one older adults across the AD continuum (intact, amnestic Mild Cognitive Impairment, mild AD), who were mostly Caucasian and well-educated, underwent assessment with the RBANS and collection of the three biomarkers.

Greater amyloid deposition was significantly related to lower scores on all five Indexes and the Total Scale score of the RBANS, as well as 11 of 12 subtests. For bilateral hippocampal volume, significant correlations were observed for 4 of the 5 Indexes, Total Scale score, and 9 of 12 subtests, with smaller hippocampi being related to lower RBANS scores. Participants with at least one APOE ε4 allele had significantly lower scores on 3 of the 5 Indexes, Total Scale score, and 8 of the 12 subtests.

In this sample of participants across the dementia spectrum, most RBANS Indexes and subtests showed relationships with the amyloid deposition, hippocampal volumes, and APOE status, with poorer performance on the RBANS being associated with biomarker positivity. Although memory scores on the RBANS have traditionally been linked to biomarkers in AD, other Index and subtest scores also hold promise as indicators of AD. Replication in a more diverse sample is needed.

Optimal MoCA cutoffs for detecting biologically-defined patients with MCI and early dementia

OBJECTIVE

In this phase II psychometric study on the Montreal cognitive assessment (MoCA), we tested the clinicometric properties of Italian norms for patients with mild cognitive impairment (PwMCI) and early dementia (PwD) and provided optimal cutoffs for diagnostic purposes.

METHODS

Retrospective data collection was performed for consecutive patients with clinically and biologically defined MCI and early dementia. Forty-five patients (24 PwMCI and 21 PwD) and 25 healthy controls were included. Raw MoCA scores were adjusted according to the conventional 1-point correction (Nasreddine) and Italian norms (Conti, Santangelo, Aiello). The diagnostic properties of the original cutoff (< 26) and normative cutoffs, namely, the upper limits (uLs) of equivalent scores (ES) 1, 2, and 3, were evaluated. ROC curve analysis was performed to obtain optimal cutoffs.

RESULTS

The original cutoff demonstrated high sensitivity (0.93 [95% CI 0.84-0.98]) but low specificity (0.44 [0.32-0.56]) in discriminating between patients and controls. Nominal normative cutoffs (ES0 uLs) showed excellent specificity (SP range = 0.96-1.00 [0.88-1.00]) but poor sensitivity (SE range = 0.09-0.24 [0.04-0.36]). The optimal cutoff for Nasreddine's method was 23.50 (SE = 0.82 [0.71-0.90]; SP = 0.72 [0.60-0.82]). Optimal cutoffs were 20.97, 22.85, and 22.29 (SE range = 0.69-0.73 [0.57-0.83], SP range = 0.88-0.92 [0.77-0.97]) for Conti's, Santangelo's, and Aiello's methods, respectively.

CONCLUSION

Using the 1-point correction, combined with a cutoff of 23.50, might be useful in ambulatory settings with a large turnout. Our optimal cutoffs can offset the poor sensitivity of Italian cutoffs.

Hippocampal subfield viscoelasticity in amnestic mild cognitive impairment evaluated with MR elastography

Hippocampal subfields (HCsf) are brain regions important for memory function that are vulnerable to decline with amnestic mild cognitive impairment (aMCI), which is often a preclinical stage of Alzheimer's disease. Studies in aMCI patients often assess HCsf tissue integrity using measures of volume, which has little specificity to microstructure and pathology. We use magnetic resonance elastography (MRE) to examine the viscoelastic mechanical properties of HCsf tissue, which is related to structural integrity, and sensitively detect differences in older adults with aMCI compared to an age-matched control group. Group comparisons revealed HCsf viscoelasticity is differentially affected in aMCI, with CA1-CA2 and DG-CA3 exhibiting lower stiffness and CA1-CA2 exhibiting higher damping ratio, both indicating poorer tissue integrity in aMCI. Including HCsf stiffness in a logistic regression improves classification of aMCI beyond measures of volume alone. Additionally, lower DG-CA3 stiffness predicted aMCI status regardless of DG-CA3 volume. These findings showcase the benefit of using MRE in detecting subtle pathological tissue changes in individuals with aMCI via the HCsf particularly affected in the disease.

MASCoD-Multidimensional Assessment of Subjective Cognitive Decline

Subjective cognitive decline (SCD) is a subclinical cognitive impairment that is complained by the individual without being objectively supported at clinical, diagnostic, and neuropsychological levels. It can negatively impact on patient's frailty and quality of life, as well as on the caregiver's burden. Moreover, it can be prodromal to Mild Cognitive Impairment or dementia. Although the clinical manifestations of SCD can differ along with several cognitive domains, to date there are only screening tools to investigate subjective memory complaints. Thus, the first aim of this paper is to propose a preliminary English and Italian version of a new screening tool called MASCoD (Multidimensional Assessment of Subjective Cognitive Decline); the second aim is to propose its preliminary adoption on a pilot sample. This schedule is a brief test derived from the review of the literature and the clinical experience provided by an experts panelist. From pilot tests, it seems promising as it can help the professional to make differential diagnosis and to predict the risk of developing severe cognitive impairment over time, developing a personalized care path. This screening tool is brief, easily embeddable in usual clinical assessment, and administrable by different professionals. Furthermore, following validation, it will allow to collect manifold cognitive manifestations of SCD, addressing the shortage of previous validated instruments globally assessing cognition affected by this condition.

Affective Theory of Mind as a residual ability to preserve mentalizing in amnestic Mild Cognitive Impairment: A 12-months longitudinal study

INTRODUCTION

Theory of Mind (ToM) decline has been outlined in people with amnestic Mild Cognitive Impairment (aMCI), but evidence from longitudinal studies is lacking. This longitudinal study aims to investigate changes in cognitive and affective ToM performance in an aMCI sample (n = 28; 14 females, mean age = 76.54 ± 4.35).

METHOD

Participants underwent two steps of neurocognitive evaluation, at the baseline (T1) and 12-month follow-up (T2), to obtain their global cognitive level and both affective (Reading the Mind in the Eyes test, ET) and cognitive (Strange Stories, SS) ToM profile. Then, participants were categorized into two groups based on ToM changes: people who worsened (ETΔ < 0; SSΔ < 0) and people who did not (ETΔ≥0; SSΔ≥0) at follow-up. Differences between groups in cognitive functions and ToM profiles at baseline have been investigated.

RESULTS

Our results showed that 46% of subjects worsened in affective (ET) and 28% in cognitive (SS) ToM at follow-up. People who worsened in ET reported a statistically significantly higher performance in ET at baseline (p = 0.002) but not at follow-up than people who did not worsen. In contrast, subjects who worsened in SS showed a lower Immediate Free Recall (IFR, p = 0.026) and Delayed Free Recall (DFR, p = 0.028) score of the Free and Cued Selective Reminding test at baseline and at follow-up, a lower ET (p = 0.020) baseline score, a lower SS and MMSE level at follow-up than people who not worsened. About 71% of MCI subjects showed the same trend of evolution of the Mini-Mental State Examination and SS. Variables that significantly differed between groups have been inserted in a stepwise logistic regression to pilot explore predictors of affective and cognitive ToM evolution. Logistic regression showed ET at baseline (p = 0.015) as the only significant predictor of affective ToM evolution (R2 = 0.450), while both ET (p = 0.044) and memory performance (p = 0.045) at baseline significantly predicted cognitive ToM evolution (R2 = 0.746).

DISCUSSION

In conclusion, our results support the role of affective ToM as a residual mentalizing ability in preserving the mentalizing level in people with aMCI.

DMapp: a developing promising approach to monitor symptoms progression and stimulate memory in Italian people with cognitive impairments

BACKGROUND

Based on recent researches on the use of natural language processing techniques for very early detection of cognitive decline and the benefits of cognitive stimulation for people with cognitive impairments, the Dementia Monitoring application (DMapp) is developed inside the Memento project.

AIMS

The aims of this work are: (1) to present DMapp; (2) to report the results of two preliminary studies on DMapp; (3) to describe the clinical and experimental potentiality of DMapp.

METHODS

Italian people with the diagnosis of mild cognitive impairment due to Alzheimer's disease or dementia due to Alzheimer's Disease with a Mini-Mental-State-Examination between 24 and 28 (inclusive) were involved in the DMapp development prototype during the Lab Trial (4 subjects) and Filed Trial (5 subjects) of the Memento project. Qualitative and quantitative data were collected to evaluate participants' opinions, the DMapp ability to perform the automatic analysis of the speech and participants' visible emotional state effective. Ad hoc interviews, the Observed Emotion Rating Scale and performance metrics to solve different tasks were used. The relation between cognitive measures (global cognitive measures) and linguistic indexes values was considered using Euclidean distances between the participants.

RESULTS

Linguistic indexes were calculated and seemed to classify the participants' performance as expected from cognitive measures. The DMapp was appreciated by people with cognitive impairment. Positive emotions were present.

CONCLUSION

DMapp seems an interesting approach to monitor dementia symptoms progression and stimulate memory. Possible developments and open questions are discussed.

Semantic intrusion errors as a function of age, amyloid, and volumetric loss: a confirmatory path analysis

OBJECTIVE

To examine the direct and indirect effects of age, APOE ϵ4 genotype, amyloid positivity, and volumetric reductions in AD-prone brain regions as it relates to semantic intrusion errors reflecting proactive semantic interference (PSI) and the failure to recover from proactive semantic interference (frPSI) on the Loewenstein-Acevedo Scales of Semantic Interference and Learning (LASSI-L), a cognitive stress test that has been consistently more predictive of preclinical and prodromal Alzheimer's disease (AD) than traditional list-learning tests.

DESIGN

Cross-sectional study.

SETTING

1Florida Alzheimer's Disease Research Center baseline study.

PARTICIPANTS

Two-hundred and twelve participants with Mini-Mental State Examination (MMSE) score above 16 and a broad array of cognitive diagnoses ranging from cognitively normal (CN) to dementia, of whom 58% were female, mean age of 72.1 (SD 7.9).

MEASURES

Participants underwent extensive clinical and neuropsychological evaluations, MR and amyloid Positron Emission Tomography/Computer/Computer Tomography (PET/CT) imaging, and analyses of APOE ϵ4 genotype. Confirmatory path analyses were conducted in the structural equation modeling framework that estimated multiple equations simultaneously while controlling for important covariates such as sex, education, language of evaluation, and global cognitive impairment.

RESULTS

Both amyloid positivity and decreased brain volumes in AD-prone regions were directly related to LASSI-L Cued B1 and Cued B2 intrusions (sensitive to PSI and frPSI effects) even after controlling for covariates. APOE ϵ4 status did not evidence direct effects on these LASSI-L cognitive markers, but rather exerted their effects on amyloid positivity, which in turn related to PSI and frPSI. Similarly, age did not have a direct relationship with LASSI-L scores, but exerted its effects indirectly through amyloid positivity and volumes of AD-prone brain regions.

CONCLUSIONS

Our study provides insight into the relationships among age, APOE ϵ4, amyloid, and brain volumetric reductions as it relates to semantic intrusion errors. The investigation expands our understanding of the underpinnings of PSI and frPSI intrusions in a large cohort.

Prevalence and predictors of Motoric Cognitive Risk syndrome in a community-dwelling older Scottish population: A longitudinal observational study

OBJECTIVES

Motoric Cognitive Risk (MCR) is a gait-based predementia syndrome that is easy to measure and prognostic of dementia and falls. We aimed to examine the prevalence and risk factors for MCR, and assess its overlap with Mild Cognitive Impairment, Prefrailty, and Frailty, in a cohort of older Scottish adults without dementia.

METHODS

In this longitudinal prospective study, we classified 690 participants (mean [SD] age 76.3 [0.8] years; wave 3) of the Lothian Birth Cohort 1936 (LBC1936) into non-MCR or MCR groups. We examined their baseline (age 69.5 [0.8] years; wave 1) risk factors for MCR at waves 3, 4, and 5 (6, 9, and 12 years later respectively).

RESULTS

MCR prevalence rate ranged from 5.3% to 5.7% across the three waves. The presence of MCR was associated with older baseline age (6 and 9 years later), lower occupational socioeconomic status (6 years later), and worse scores in a range of tests of executive function (6, 9 and 12 years later). Approximately 46% of the MCR group also had Mild Cognitive Impairment, and almost everyone in the MCR group had either Prefrailty or Frailty.

CONCLUSIONS

The prevalence of MCR in this Scottish cohort is lower than the pooled global average, possibly reflecting the general good health of the LBC cohort. However, it is higher than the prevalence in two neighbouring countries' cohorts, which may reflect the younger average ages of those cohorts. Future LBC1936 research should assess the risk factors associated with MCR to validate previous findings and analyse novel predictive factors, particularly socioeconomic status.

Effects of Oxidative Damage during Ruesi Dadton Exercise in Mild Cognitive Impairment: Randomized Controlled Trial

This study aimed to investigate the effect of biomarkers of oxidative stress (OS) in 8-isoprostane (8-iso) and 8-hydroxy-2'-deoxyguanosine (8-OH-dG) on mild cognitive impairment (MCI) during a 12-week Ruesi Dadton (RD) exercise. A total of 274 enrolled participants were classified into blocks based on age and formal educational years, and randomly assigned into two groups: RD and control (CON). The participants' cognitive functions were tested using Mini-Mental State Examination and Montreal Cognitive Assessment (MoCA) scores to screen for MCI. Urine samples of approximately 30 mL were collected from both groups pre- and post-intervention. All participants signed consent forms before participating in the program. Participants in the RD group were instructed to perform 15 postures of RD exercise in 60 min, three times a week for 12 weeks. A 2 × 2 (group × time) repeated multivariate analysis, with MoCA score, 8-iso, and 8-OH-dG as covariates, was performed to analyze the between-subject differences across group [V = 0.143, F(2,60) = 5.020, p = 0.010, d = 0.209] and within-subject differences across interaction between group [V = 0.143, F(2,60) = 5.020, p = 0.010, d = 0.408]. There were significant differences from univariate data regarding both 8-iso (F1,61 = 10.081, P = 0.002, d = 0.406) and 8-OH-dG (F(1,61) = 5.965, P = 0.018, d = 0.312) levels. Moreover, results from both biomarkers in the RD group revealed significant improvements in 8-iso (p < 0.001) and 8-OH-dG (p = 0.003), whereas there were no improvements in the CON group. In conclusion, RD decreased biomarkers of OS during 12 weeks of RD exercise in MCI. These results indicate that in MCI, RD could improve lipid peroxidation and DNA oxidation by 8-iso and 8-OH-dG, respectively.

The physician's Alzheimer's disease management guide: Early detection and diagnosis of cognitive impairment, Alzheimer's disease and related dementia

Primary care professionals play a critical role in the care of their patients. In clinical practice, early detection and diagnosis of Mild Cognitive Impairment, Alzheimer's disease and related dementia are often missed or delayed. Disclosure of diagnosis is not timely or not revealed. Though the methods that could improve early detection and diagnosis have remained the same over the decades with little change, they provide opportunities for early intervention, treatment and improvement in patient care. Emerging research suggests that though the disease process begins years prior to the clinical diagnosis, the healthcare system and health care professionals remain distant and reluctant to provide the service of annual cognitive assessment, which has been recommended by the Medicare program for older adults aged 65 years and older. Findings support that Alzheimer's disease and related cognitive impairments have gone under detected, underdiagnosed and undertreated. This article seeks to provide valuable and equitable information in the form of a clinician's guide for removing the barriers to early detection and diagnosis of cognitive impairments and offers an unprecedented opportunity to improve the clinical outcomes and care of older adults with various levels of cognitive decline, including mild cognitive impairment, Alzheimer's disease, and related dementias. This article provides information on understanding and addressing the challenges faced by health care professionals, including primary care clinicians; removing the barriers to cognitive assessments; educating this professional group on the importance of brain health, early detection, and diagnosis for their older adult patients; and providing these professionals with the ability to transfer their knowledge into more defined care planning. Until cognitive screening has been fully accepted and implemented for the optimal the care of older adults, health-related efforts should include the promotion and education of brain health, early detection, and diagnosis in the education of health care providers.

Associations Between Country where Education is Obtained and Cognitive Functioning Among South American and Caribbean Older Adults Living in the U.S

The increasing prevalence of AD among Hispanics calls for a need for examining factors that affect cognitive functioning and risk of AD among Hispanic older adults. The current study examined cognitive functioning among older Hispanic adults living in the U.S. from two Hispanic regions, South America and the Caribbean, in relation to the country where education was obtained. Participants (n = 139) were stratified into groups based on Hispanic education region and diagnostic categories: cognitively normal and amnestic MCI (aMCI). Results of Pearson correlations showed that among Hispanic Americans in general, there were significant positive correlations between the country of education to performance on measures of episodic, verbal, and word list tests. When examined separately by region and diagnosis, only cognitively normal (CN) South Americans showed significant relationships between country of education and cognitive functioning in these areas. Results of general linear models controlling for education identified differences in neuropsychological performance between groups with the CN groups demonstrating better performance than the aMCI groups within each region. Overall, it was evident that relationships between years of education obtained outside of the U.S. and cognitive functioning were not similar among individuals from these two disparate Spanish speaking regions. This is the first study to examine the country where education was obtained among individuals from countries located in different regions with different cultures that may influence their education and cognitive development throughout life. Findings contribute to the cross-cultural neuropsychological literature in understanding factors that are unique to Hispanic older adults at risk for developing AD.

Biological determinants of blood-based cytokines in the Alzheimer's Disease clinical continuum

Converging translational and clinical research strongly indicates that altered immune and inflammatory homeostasis (neuroinflammation) plays a critical pathophysiological role in Alzheimer's disease (AD), across the clinical continuum. A dualistic role of neuroinflammation may account for a complex biological phenomenon, representing a potential pharmacological target. Emerging blood-based pathophysiological biomarkers, such as cytokines (Cyt) and interleukins (ILs) have been studied as indicators of neuroinflammation in AD. However, inconsistent results have been reported, probably due to lack of standardization of assays with methodological and analytical differences. We used machine-learning and a cross-validation-based statical workflow to explore and analyze the potential impact of key biological factors, such as age, sex, apolipoproteinE (APOE) genotype (the major genetic risk factor for late-onset AD) on Cyt. A set of Cyt was selected based on previous literature, and we investigated any potential association in a pooled cohort of cognitively healthy, mild cognitive impairment (MCI), and AD-like dementia patients. We also performed explorative analyses to extrapolate preliminary clinical insights. We found a robust sex effect on IL12 and an APOE-related difference in IL10, with the latter being also related to the presence of advanced cognitive decline. IL1β was the variable most significantly associated with MCI-to-dementia conversion over a 2.5 year-clinical follow-up. Albeit preliminary, our data support further clinical research to understand whether plasma Cyt may represent reliable and non-invasive tools serving the investigation of neuroimmune and inflammatory dynamics in AD and to foster biomarker-guided pathway-based therapeutic approaches, within the precision medicine development framework.

A robust framework to investigate the reliability and stability of explainable artificial intelligence markers of Mild Cognitive Impairment and Alzheimer's Disease

In clinical practice, several standardized neuropsychological tests have been designed to assess and monitor the neurocognitive status of patients with neurodegenerative diseases such as Alzheimer’s disease. Important research efforts have been devoted so far to the development of multivariate machine learning models that combine the different test indexes to predict the diagnosis and prognosis of cognitive decline with remarkable results. However, less attention has been devoted to the explainability of these models. In this work, we present a robust framework to (i) perform a threefold classification between healthy control subjects, individuals with cognitive impairment, and subjects with dementia using different cognitive indexes and (ii) analyze the variability of the explainability SHAP values associated with the decisions taken by the predictive models. We demonstrate that the SHAP values can accurately characterize how each index affects a patient’s cognitive status. Furthermore, we show that a longitudinal analysis of SHAP values can provide effective information on Alzheimer’s disease progression.

Explainable Optimized LightGBM Based Differentiation of Mild Cognitive Impairment Using MR Radiomic Features

In this study, an explainable Bayesian Optimized (BO) LightGBM model is employed to differentiate the Corpus Callosal (CC) image features of Healthy Controls (HC) and Mild Cognitive Impairment (MCI). For this, Magnetic Resonance (MR) brain images obtained from a public database are pre-processed and CC is segmented using spatial fuzzy clustering-based level set. Radiomic features are extracted from the segmented CC, which are further fed to BO-LightGBM classifier. SHapley Additive exPlanations (SHAP) technique is used to evaluate the interpretability of the model. The results indicate that radiomics based BO-LightGBM is able to differentiate MCI from HC. An area under curve of 0.83 is achieved by the model. SHAP values suggest that out of 56 radiomic features, texture descriptors possess the highest discriminative power in MCI diagnosis. The performance of adopted approach indicates that radiomics based BO-LightGBM aid in the automated diagnosis of early Alzheimer's Disease stages.

Health-Related Predictors of Changes in Cognitive Status in Community-Dwelling Older Individuals

Given the rising numbers of older people living with dementia, this study focuses on identifying modifiable health-related factors associated with changes in cognitive status. The predictors of 1-year conversion from Preserved Cognitive Health (PCH) and Mild Cognitive Impairment (MCI) in older adults were evaluated. Two logistic regression models were performed on data from an Italian multicenter population-based study; both included sociodemographic factors, family history of dementia (FHD), risk behaviors, and depressive symptoms. The first model considered also disease clusters, while the second one included diseases' number and biochemical parameters. The sample involved 459 participants (61.4% women, median age 75 years). Of the 80 PCH individuals at baseline, after 1 year 35 (43.8%) were stable, 44 (55.0%) progressed to MCI, none to dementia, and one to unclassified status. Of the 379 MCI participants at baseline, after 1 year 281 (74.1%) remained stable, 38 (10.0%) reverted to PCH, 15 (4.0%) progressed to dementia, and 45 (11.9%) become unclassifiable. Hypertension/bone and joint diseases cluster was the only predictor of PCH progression to MCI; age and depression were associated with MCI progression to dementia; FHD was associated with MCI reversion to PCH. More diseases and fewer white blood cells were associated with MCI progression to dementia; more diseases and lower platelets were associated with the transition from MCI to unclassifiable; higher Na and lower TSH levels were associated with MCI reversion. The treatment or management of some chronic conditions and electrolyte imbalances may help attenuate cognitive deterioration in older adults with no or MCI.

A systematic literature review and meta-analysis on digital health interventions for people living with dementia and Mild Cognitive Impairment

OBJECTIVES

Digital health interventions enable services to support people living with dementia and Mild Cognitive Impairment (MCI) remotely. This literature review gathers evidence on the effectiveness of digital health interventions on physical, cognitive, behavioural and psychological outcomes, and Activities of Daily Living in people living with dementia and MCI.

METHODS/DESIGN

Searches, using nine databases, were run in November 2021. Two authors carried out study selection/appraisal using the Critical Appraisal Skills Programme checklist. Study characteristics were extracted through the Cochrane handbook for systematic reviews of interventions data extraction form. Data on digital health interventions were extracted through the template for intervention description and replication (TIDieR) checklist and guide. Intervention effectiveness was determined through effect sizes. Meta-analyses were performed to pool data on intervention effectiveness.

RESULTS

Twenty studies were included in the review, with a diverse range of interventions, modes of delivery, activities, duration, length, frequency, and intensity. Compared to controls, the interventions produced a moderate effect on cognitive abilities (SMD = 0.36; 95% CI = -0.03 to 0.76; I2  = 61%), and a negative moderate effect on basic ADLs (SMD = -0.40; 95% CI = -0.86 to 0.05; I2  = 69%). Stepping exergames generated the largest effect sizes on physical and cognitive abilities. Supervised training produced larger effect sizes than unsupervised interventions.

CONCLUSION

Supervised intervention delivery is linked to greatest benefits. A mix of remote and face-to-face delivery could maximise benefits and optimise costs. Accessibility, acceptability and sustainability of digital interventions for end-users must be pre-requisites for the development of future successful services.

Hand movements in Mild Cognitive Impairment: clinical implications and insights for future research

Decreased upper-extremity/visuomotor abilities are frequently encountered in healthy aging. However, few studies have assessed hand movements in the prodromal stage of dementia. The evaluation of visuomotor skills in patients with Mild Cognitive Impairment (PwMCI) may have non-negligible clinical relevance both in diagnostic and prognostic terms, given the strong relationships with executive functioning and functional autonomies. In the present review paper, these issues will be disclosed by describing general pathophysiological and neuropsychological mechanisms responsible for visuomotor deficits, and by reporting the available experimental results on differences in visuomotor functioning between PwMCI, healthy controls and/or patients with dementia. Moreover, the relationships binding visuomotor and executive domains to functional autonomies will be then addressed. Finally, we will propose insights for future research.

Plasma neurofilament light chain as a biomarker of Alzheimer's disease in Subjective Cognitive Decline and Mild Cognitive Impairment

INTRODUCTION

Neurofilament light chain (NfL) is becoming increasingly notable in neurological diseases including AD, and it has been suggested as a new peripherical biomarker of neurodegeneration. We aimed to compare plasma NfL levels among Subjective Cognitive Decline (SCD), Mild Cognitive Impairment (MCI), and AD patients and to evaluate relationships between NfL and CSF biomarkers and neuropsychological scores.

MATERIALS AND METHODS

We enrolled 110 patients (34 SCD, 53 MCI, and 23 AD), who underwent clinical and neuropsychological evaluation, APOE genotyping, and plasma NfL analysis. Ninety-one patients underwent at least one amyloid burden biomarker (CSF and/or amyloid PET); 86 patients also underwent CSF phosphorylated-tau (p-tau) and total-tau (t-tau) measurement. Patients were classified as A + if they presented at least one positive amyloid biomarker or A- if not.

RESULTS

NfL levels were significantly increased in AD and MCI compared to SCD patients. These differences depend on A status, e.g., SCD A + had lower NfLs than MCI A + but comparable with MCI A-. Similarly, MCI A + had higher NfL levels than MCI A-, but comparable with AD. NfL levels correlated with p-tau in SCD, with all CSF biomarkers in MCI patients. No correlations were found in AD subgroup. In SCD, NfL levels were negatively correlated with memory test scores.

CONCLUSIONS

Plasma NfL levels might be a promising biomarker for neurodegeneration to discriminate cognitive decline due to AD from other conditions causing cognitive impairment in prodromal stages. Considering correlations with CSF p-tau and memory tests in SCD, NfL might be a useful peripheral biomarker also in preclinical phases of AD.

Moving in Semantic Space in Prodromal and Very Early Alzheimer's Disease: An Item-Level Characterization of the Semantic Fluency Task

The semantic fluency task is a widely used clinical tool in the diagnostic process of Alzheimer's disease. The task requires efficient mapping of the semantic space to produce as many items as possible within a semantic category. We examined whether healthy volunteers (n = 42) and patients with early Alzheimer's disease (24 diagnosed with amnestic Mild Cognitive Impairment and 18 with early Alzheimer's dementia) take advantage of and travel in the semantic space differently. With focus on the animal fluency task, we sought to emulate the detailed structure of the multidimensional semantic space by utilizing word2vec-method from the natural language processing domain. To render the resulting multidimensional semantic space visually comprehensible, we applied a dimensionality reduction algorithm (t-SNE), which enabled a straightforward division of the semantic space into sub-categories. Moving in semantic space was quantified with the number of items created, sub-categories visited, and switches and returns to these sub-categories. Multinomial logistic regression models were used to predict the diagnostic group with these independent variables. We found that returning to a sub-category provided additional information, besides the number of words produced in the task, to differentiate patients with Alzheimer's dementia from both amnestic Mild Cognitive Impairment patients and healthy controls. The results suggest that the frequency of returning to a sub-category may serve as an additional aid for clinicians in diagnosing early Alzheimer's disease. Moreover, our results imply that the combination of word2vec and subsequent t-SNE-visualization may offer a valuable tool for examining the semantic space and its sub-categories.

Different MMSE domains are associated to cognitive decline and education

The Mini-Mental State Examination (MMSE) is a long-established test to screen for dementia, estimate the severity and monitor the progression of cognitive impairment. The MMSE total score is dependent upon demographic factors, particularly education, but little is known about how education influences the 6 distinct MMSE cognitive domains. The present study aims to understand how the performances in the MMSE cognitive domains reflect clinical diagnosis and educational level. The study recruited 1043 participants, comprising 388 healthy controls, 360 patients with Mild Cognitive Impairment (MCI) and 295 patients with dementia. The association of the MMSE cognitive domains scores with clinical diagnosis (healthy, MCI, dementia) and educational level (primary education, middle school, high school and university/college) was analyzed with a multivariate ordinal regression model. The scores in all MMSE domains were generally higher in healthy controls as compared to patients with MCI, and higher in these as compared to patients with dementia. The MMSE domain Constructional ability was associated to the education level, the domains Orientation, Recall and Language were associated to diagnosis, Attention and calculation was associated to both education level and diagnosis, and Registration was not associated to either education or diagnosis. In conclusion, impairment in specific MMSE domains pinpoints cognitive decline, probably indicating brain areas affected by neurodegeneration, and impairment in others reflects lower education levels and the lack of acquisition of relevant schooling abilities.

Higher-Level Executive Functions in Healthy Elderly and Mild Cognitive Impairment: A Systematic Review

Mild Cognitive Impairment (MCI) is a clinical syndrome characterized by a moderate decline in one or more cognitive functions with a preserved autonomy in daily life activities. MCI exhibits cognitive, behavioral, psychological symptoms. The executive functions (EFs) are key functions for everyday life and physical and mental health and allow for the behavior to adapt to external changes. Higher-level executive functions develop from basic EFs (inhibition, working memory, attentional control, and cognitive flexibility). They are planning, reasoning, problem solving, and fluid intelligence (Gf). This systematic review investigates the relationship between higher-level executive functions and healthy and pathological aging, assuming the role of executive functions deficits as a predictor of cognitive decline. The systematic review was conducted according to the PRISMA Statement. A total of 73 studies were identified. The results indicate that 65.8% of the studies confirm significant EFs alterations in MCI (56.8% planning, 50% reasoning, 100% problem solving, 71.4% fluid intelligence). These results seem to highlight a strong prevalence of higher-level executive functions deficits in MCI elderly than in healthy elderly.

The discriminant validity of Rey Complex Figure Test (RCFT) in subjective cognitive decline, mild cognitive impairment (multiple domain) and Alzheimer's disease dementia (ADD; mild stage) in Greek older adults

Aim: The goal of this study was to determine the discriminant potential of the Rey Complex Figure Test (RCFT) in older adults with Mild Cognitive Impairment multiple domain (mdMCI) and Alzheimer's Disease Dementia (ADD; mild subtype) as compared to older adults with Subjective Cognitive Decline (SCD).Materials and methods: We administered RCFT in 608 older adults, dividing them in three groups (217 individuals with SCD; 304 mdMCI population; 106 people with mild ADD, aged 50-90 years; M = 66.9, SD = 8.4) and a mean education of 10.20 (SD 4.3) years.Results: RCFT subtests have excellent discriminant validity, mainly between people with SCD and those with mild ADD. However, its discriminant validity in detecting older adults with SCD among mdMCI population is still questionable.Discussion: The use of RFCT in discriminating older adults with SCD from those with mild ADD both in research as well as in clinical practice is highly recommended.