The Association between Montreal Cognitive Assessment Memory Scores and Hippocampal Volume in a Neurodegenerative Disease Sample

Blood-brain barrier integrity is linked to cognitive function, but not to cerebral arterial pulsatility, among elderly

Blood-brain barrier (BBB) disruption may contribute to cognitive decline, but questions remain whether this association is more pronounced for certain brain regions, such as the hippocampus, or represents a whole-brain mechanism. Further, whether human BBB leakage is triggered by excessive vascular pulsatility, as suggested by animal studies, remains unknown. In a prospective cohort (N = 50; 68-84 years), we used contrast-enhanced MRI to estimate the permeability-surface area product (PS) and fractional plasma volume ( v p ), and 4D flow MRI to assess cerebral arterial pulsatility. Cognition was assessed by the Montreal Cognitive Assessment (MoCA) score. We hypothesized that high PS would be associated with high arterial pulsatility, and that links to cognition would be specific to hippocampal PS. For 15 brain regions, PS ranged from 0.38 to 0.85 (·10-3 min-1) and v p from 0.79 to 1.78%. Cognition was related to PS (·10-3 min-1) in hippocampus (β = - 2.9; p = 0.006), basal ganglia (β = - 2.3; p = 0.04), white matter (β = - 2.6; p = 0.04), whole-brain (β = - 2.7; p = 0.04) and borderline-related for cortex (β = - 2.7; p = 0.076). Pulsatility was unrelated to PS for all regions (p > 0.19). Our findings suggest PS-cognition links mainly reflect a whole-brain phenomenon with only slightly more pronounced links for the hippocampus, and provide no evidence of excessive pulsatility as a trigger of BBB disruption.

Cerebral microstructural alterations in Post-COVID-condition are related to cognitive impairment, olfactory dysfunction and fatigue

After contracting COVID-19, a substantial number of individuals develop a Post-COVID-Condition, marked by neurologic symptoms such as cognitive deficits, olfactory dysfunction, and fatigue. Despite this, biomarkers and pathophysiological understandings of this condition remain limited. Employing magnetic resonance imaging, we conduct a comparative analysis of cerebral microstructure among patients with Post-COVID-Condition, healthy controls, and individuals that contracted COVID-19 without long-term symptoms. We reveal widespread alterations in cerebral microstructure, attributed to a shift in volume from neuronal compartments to free fluid, associated with the severity of the initial infection. Correlating these alterations with cognition, olfaction, and fatigue unveils distinct affected networks, which are in close anatomical-functional relationship with the respective symptoms.

Memory impairment in Amyloidβ-status Alzheimer's disease is associated with a reduction in CA1 and dentate gyrus volume: In vivo MRI at 7T

INTRODUCTION

In Alzheimer's disease (AD), early diagnosis facilitates treatment options and leads to beneficial outcomes for patients, their carers and the healthcare system. The neuropsychological battery of the Uniform Data Set (UDSNB3.0) assesses cognition in ageing and dementia, by measuring scores across different cognitive domains such as attention, memory, processing speed, executive function and language. However, its neuroanatomical correlates have not been investigated using 7 Tesla MRI (7T MRI).

METHODS

We used 7T MRI to investigate the correlations between hippocampal subfield volumes and the UDSNB3.0 in 24 individuals with Amyloidβ-status AD and 18 age-matched controls, with respective age ranges of 60 (42-76) and 62 (52-79) years. AD participants with a Medial Temporal Atrophy scale of higher than 2 on 3T MRI were excluded from the study.

RESULTS

A significant difference in the entire hippocampal volume was observed in the AD group compared to healthy controls (HC), primarily influenced by CA1, the largest hippocampal subfield. Notably, no significant difference in whole brain volume between the groups implied that hippocampal volume loss was not merely reflective of overall brain atrophy. UDSNB3.0 cognitive scores showed significant differences between AD and HC, particularly in Memory, Language, and Visuospatial domains. The volume of the Dentate Gyrus (DG) showed a significant association with the Memory and Executive domain scores in AD patients as assessed by the UDSNB3.0.. The data also suggested a non-significant trend for CA1 volume associated with UDSNB3.0 Memory, Executive, and Language domain scores in AD. In a reassessment focusing on hippocampal subfields and MoCA memory subdomains in AD, associations were observed between the DG and Cued, Uncued, and Recognition Memory subscores, whereas CA1 and Tail showed associations only with Cued memory.

DISCUSSION

This study reveals differences in the hippocampal volumes measured using 7T MRI, between individuals with early symptomatic AD compared with healthy controls. This highlights the potential of 7T MRI as a valuable tool for early AD diagnosis and the real-time monitoring of AD progression and treatment efficacy.

CLINICALTRIALS

GOV: ID NCT04992975 (Clinicaltrial.gov 2023).

Translating phenotypic prediction models from big to small anatomical MRI data using meta-matching

Individualized phenotypic prediction based on structural MRI is an important goal in neuroscience. Prediction performance increases with larger samples, but small-scale datasets with fewer than 200 participants are often unavoidable. We have previously proposed a "meta-matching" framework to translate models trained from large datasets to improve the prediction of new unseen phenotypes in small collection efforts. Meta-matching exploits correlations between phenotypes, yielding large improvement over classical machine learning when applied to prediction models using resting-state functional connectivity as input features. Here, we adapt the two best performing meta-matching variants ("meta-matching finetune" and "meta-matching stacking") from our previous study to work with T1-weighted MRI data by changing the base neural network architecture to a 3D convolution neural network. We compare the two meta-matching variants with elastic net and classical transfer learning using the UK Biobank (N = 36,461), Human Connectome Project Young Adults (HCP-YA) dataset (N = 1,017) and HCP-Aging dataset (N = 656). We find that meta-matching outperforms elastic net and classical transfer learning by a large margin, both when translating models within the same dataset, as well as translating models across datasets with different MRI scanners, acquisition protocols and demographics. For example, when translating a UK Biobank model to 100 HCP-YA participants, meta-matching finetune yielded a 136% improvement in variance explained over transfer learning, with an average absolute gain of 2.6% (minimum = -0.9%, maximum = 17.6%) across 35 phenotypes. Overall, our results highlight the versatility of the meta-matching framework.

The Association between Kidney Function Biomarkers and Delayed Memory Impairments among Older Adults in the European North of Russia

The prevention of memory decline requires better knowledge of biological markers. We studied the associations between kidney function biomarkers and memory decline (assessed with the Mini-Mental State Examination-MMSE) in elderly individuals without dementia (MMSE 24-30, age 60-74 years, n = 643, Arkhangelsk, Russia). Participants were divided by sex and into three groups according to the delayed memory performance: recall of 0-1, 2, and 3 out of 3 words. The median of serum creatinine was 82 μmol/L in men who recalled 2 words and both medians in those recalling 3 and 0-1 words were 87 μmol/L. The 90th percentile for creatinine in men recalling 0-1 words (115.0 μmol/L) exceeded the upper limit of the normal range (110.5 μmol/L), while those who recalled 3 and 2 words had 90th percentiles within the normal range (109 and 101 μmol/L, respectively). Glomerular filtration rates were normal (≥60 mL/min/1.73 m2) with a median of 92.0 mL/min/1.73 m2 in men who recalled 2 words, 84.4 and 84.9 mL/min/1.73 m2 in men who recalled 3 and 0-1 words, respectively. None of these associations were observed in women. A reduced serum creatinine in older non-demented men may indicate the initial stages of memory decline, while the increased creatinine may reflect further stages of memory impairment.

FDG-PET-based neural correlates of Addenbrooke's cognitive examination III scores in Alzheimer's disease and frontotemporal degeneration

Introduction

The Addenbrooke's Cognitive Examination III (ACE-III) is a brief test useful for neuropsychological assessment. Several studies have validated the test for the diagnosis of Alzheimer's disease (AD) and frontotemporal dementia (FTD). In this study, we aimed to examine the metabolic correlates associated with the performance of ACE-III in AD and behavioral variant FTD.

Methods

We enrolled 300 participants in a cross-sectional study, including 180 patients with AD, 60 with behavioral FTD (bvFTD), and 60 controls. An 18F-Fluorodeoxyglucose positron emission tomography study was performed in all cases. Correlation between the ACE-III and its domains (attention, memory, fluency, language, and visuospatial) with the brain metabolism was estimated.

Results

The ACE-III showed distinct neural correlates in bvFTD and AD, effectively capturing the most relevant regions involved in these disorders. Neural correlates differed for each domain, especially in the case of bvFTD. Lower ACE-III scores were associated with more advanced stages in both disorders. The ACE-III exhibited high discrimination between bvFTD vs. HC, and between AD vs. HC. Additionally, it was sensitive to detect hypometabolism in brain regions associated with bvFTD and AD.

Conclusion

Our study contributes to the knowledge of the brain regions associated with ACE-III, thereby facilitating its interpretation, and highlighting its suitability for screening and monitoring. This study provides further validation of ACE-III in the context of AD and FTD.

FDA-approved machine learning algorithms in neuroradiology: A systematic review of the current evidence for approval

Over the past decade, machine learning (ML) and artificial intelligence (AI) have become increasingly prevalent in the medical field. In the United States, the Food and Drug Administration (FDA) is responsible for regulating AI algorithms as "medical devices" to ensure patient safety. However, recent work has shown that the FDA approval process may be deficient. In this study, we evaluate the evidence supporting FDA-approved neuroalgorithms, the subset of machine learning algorithms with applications in the central nervous system (CNS), through a systematic review of the primary literature. Articles covering the 53 FDA-approved algorithms with applications in the CNS published in PubMed, EMBASE, Google Scholar and Scopus between database inception and January 25, 2022 were queried. Initial searches identified 1505 studies, of which 92 articles met the criteria for extraction and inclusion. Studies were identified for 26 of the 53 neuroalgorithms, of which 10 algorithms had only a single peer-reviewed publication. Performance metrics were available for 15 algorithms, external validation studies were available for 24 algorithms, and studies exploring the use of algorithms in clinical practice were available for 7 algorithms. Papers studying the clinical utility of these algorithms focused on three domains: workflow efficiency, cost savings, and clinical outcomes. Our analysis suggests that there is a meaningful gap between the FDA approval of machine learning algorithms and their clinical utilization. There appears to be room for process improvement by implementation of the following recommendations: the provision of compelling evidence that algorithms perform as intended, mandating minimum sample sizes, reporting of a predefined set of performance metrics for all algorithms and clinical application of algorithms prior to widespread use. This work will serve as a baseline for future research into the ideal regulatory framework for AI applications worldwide.

Visual deep learning of unprocessed neuroimaging characterises dementia subtypes and generalises across non-stereotypic samples

BACKGROUND

Dementia's diagnostic protocols are mostly based on standardised neuroimaging data collected in the Global North from homogeneous samples. In other non-stereotypical samples (participants with diverse admixture, genetics, demographics, MRI signals, or cultural origins), classifications of disease are difficult due to demographic and region-specific sample heterogeneities, lower quality scanners, and non-harmonised pipelines.

METHODS

We implemented a fully automatic computer-vision classifier using deep learning neural networks. A DenseNet was applied on raw (unpreprocessed) data from 3000 participants (behavioural variant frontotemporal dementia-bvFTD, Alzheimer's disease-AD, and healthy controls; both male and female as self-reported by participants). We tested our results in demographically matched and unmatched samples to discard possible biases and performed multiple out-of-sample validations.

FINDINGS

Robust classification results across all groups were achieved from standardised 3T neuroimaging data from the Global North, which also generalised to standardised 3T neuroimaging data from Latin America. Moreover, DenseNet also generalised to non-standardised, routine 1.5T clinical images from Latin America. These generalisations were robust in samples with heterogenous MRI recordings and were not confounded by demographics (i.e., were robust in both matched and unmatched samples, and when incorporating demographic variables in a multifeatured model). Model interpretability analysis using occlusion sensitivity evidenced core pathophysiological regions for each disease (mainly the hippocampus in AD, and the insula in bvFTD) demonstrating biological specificity and plausibility.

INTERPRETATION

The generalisable approach outlined here could be used in the future to aid clinician decision-making in diverse samples.

FUNDING

The specific funding of this article is provided in the acknowledgements section.

Landmark-dependent Navigation Strategy Declines across the Human Life-Span: Evidence from Over 37,000 Participants

Humans show a remarkable capacity to navigate various environments using different navigation strategies, and we know that strategy changes across the life span. However, this observation has been based on studies of small sample sizes. To this end, we used a mobile app-based video game (Sea Hero Quest) to test virtual navigation strategies and memory performance within a distinct radial arm maze level in over 37,000 participants. Players were presented with six pathways (three open and three closed) and were required to navigate to the three open pathways to collect a target. Next, all six pathways were made available and the player was required to visit the pathways that were previously unavailable. Both reference memory and working memory errors were calculated. Crucially, at the end of the level, the player was asked a multiple-choice question about how they found the targets (i.e., a counting-dependent strategy vs. a landmark-dependent strategy). As predicted from previous laboratory studies, we found the use of landmarks declined linearly with age. Those using landmark-based strategies also performed better on reference memory than those using a counting-based strategy. These results extend previous observations in the laboratory showing a decreased use of landmark-dependent strategies with age.

Multi-feature computational framework for combined signatures of dementia in underrepresented settings

Objective.The differential diagnosis of behavioral variant frontotemporal dementia (bvFTD) and Alzheimer's disease (AD) remains challenging in underrepresented, underdiagnosed groups, including Latinos, as advanced biomarkers are rarely available. Recent guidelines for the study of dementia highlight the critical role of biomarkers. Thus, novel cost-effective complementary approaches are required in clinical settings.Approach. We developed a novel framework based on a gradient boosting machine learning classifier, tuned by Bayesian optimization, on a multi-feature multimodal approach (combining demographic, neuropsychological, magnetic resonance imaging (MRI), and electroencephalography/functional MRI connectivity data) to characterize neurodegeneration using site harmonization and sequential feature selection. We assessed 54 bvFTD and 76 AD patients and 152 healthy controls (HCs) from a Latin American consortium (ReDLat).Main results. The multimodal model yielded high area under the curve classification values (bvFTD patients vs HCs: 0.93 (±0.01); AD patients vs HCs: 0.95 (±0.01); bvFTD vs AD patients: 0.92 (±0.01)). The feature selection approach successfully filtered non-informative multimodal markers (from thousands to dozens).Results. Proved robust against multimodal heterogeneity, sociodemographic variability, and missing data.Significance. The model accurately identified dementia subtypes using measures readily available in underrepresented settings, with a similar performance than advanced biomarkers. This approach, if confirmed and replicated, may potentially complement clinical assessments in developing countries.

Updated Review of the Evidence Supporting the Medical and Legal Use of NeuroQuant® and NeuroGage® in Patients With Traumatic Brain Injury

Over 40 years of research have shown that traumatic brain injury affects brain volume. However, technical and practical limitations made it difficult to detect brain volume abnormalities in patients suffering from chronic effects of mild or moderate traumatic brain injury. This situation improved in 2006 with the FDA clearance of NeuroQuant®, a commercially available, computer-automated software program for measuring MRI brain volume in human subjects. More recent strides were made with the introduction of NeuroGage®, commercially available software that is based on NeuroQuant® and extends its utility in several ways. Studies using these and similar methods have found that most patients with chronic mild or moderate traumatic brain injury have brain volume abnormalities, and several of these studies found-surprisingly-more abnormal enlargement than atrophy. More generally, 102 peer-reviewed studies have supported the reliability and validity of NeuroQuant® and NeuroGage®. Furthermore, this updated version of a previous review addresses whether NeuroQuant® and NeuroGage® meet the Daubert standard for admissibility in court. It concludes that NeuroQuant® and NeuroGage® meet the Daubert standard based on their reliability, validity, and objectivity. Due to the improvements in technology over the years, these brain volumetric techniques are practical and readily available for clinical or forensic use, and thus they are important tools for detecting signs of brain injury.

Montreal Cognitive Assessment (MoCA) performance in Huntington's disease patients correlates with cortical and caudate atrophy

Huntington's Disease (HD) is an autosomal neurodegenerative disease characterized by motor, cognitive, and psychiatric symptoms. Cognitive impairment develops gradually in HD patients, progressing later into a severe cognitive dysfunction. The Montreal Cognitive Assessment (MoCA) is a brief screening test commonly employed to detect mild cognitive impairment, which has also been useful to assess cognitive decline in HD patients. However, the relationship between MoCA performance and brain structural integrity in HD patients remains unclear. Therefore, to explore this relationship we analyzed if cortical thinning and subcortical nuclei volume differences correlated with HD patients' MoCA performance. Twenty-two HD patients and twenty-two healthy subjects participated in this study. T1-weighted images were acquired to analyze cortical thickness and subcortical nuclei volumes. Group comparison analysis showed a significantly lower score in the MoCA global performance of HD patients. Also, the MoCA total score correlated with cortical thinning of fronto-parietal and temporo-occipital cortices, as well as with bilateral caudate volume differences in HD patients. These results provide new insights into the effectiveness of using the MoCA test to detect cognitive impairment and the brain atrophy pattern associated with the cognitive status of prodromal/early HD patients.

Amyloid-PET Levels in the Precuneus and Posterior Cingulate Cortices Are Associated with Executive Function Scores in Preclinical Alzheimer's Disease Prior to Overt Global Amyloid Positivity

BACKGROUND

Global amyloid-β (Aβ) deposition in the brain can be quantified by Aβ-PET scans to support or refute a diagnosis of preclinical Alzheimer's disease (pAD). Yet, Aβ-PET scans enable quantitative evaluation of regional Aβ elevations in pAD, potentially allowing even earlier detection of pAD, long before global positivity is achieved. It remains unclear as to whether such regional changes are clinically meaningful.

OBJECTIVE

Test the hypothesis that early focal regional amyloid deposition in the brain is associated with cognitive performance in specific cognitive domain scores in pAD.

METHODS

Global and regional standardized uptake value ratios (SUVr) from 18F-florbetapir PET/CT scanning were determined using the Siemens Syngo.via® Neurology software package across a sample of 99 clinically normal participants with Montreal Cognitive Assessment (MoCA) scores≥23. Relationships between regional SUVr and cognitive test scores were analyzed using linear regression models adjusted for age, sex, and education. Participants were divided into two groups based on SUVr in the posterior cingulate and precuneus gyri (SUVR≥1.17). Between group differences in cognitive test scores were analyzed using ANCOVA models.

RESULTS

Executive function performance was associated with increased regional SUVr in the precuneus and posterior cingulate regions only (p < 0.05). There were no significant associations between memory and Aβ-PET SUVr in any regions of the brain.

CONCLUSION

These data demonstrate that increased Aβ deposition in the precuneus and posterior cingulate (the earliest brain regions affected with Aβ pathology) is associated with changes in executive function that may precede memory decline in pAD.

Comparison of the Impact of Zika and Dengue Virus Infection, and Other Acute Illnesses of Unidentified Origin on Cognitive Functions in a Prospective Cohort in Chiapas Mexico

Zika has been associated with a variety of severe neurologic manifestations including meningitis and encephalitis. We hypothesized that it may also cause mild to subclinical neurocognitive alterations during acute infection or over the long term. In this observational cohort study, we explored whether Zika cause subclinical or mild neurocognitive alterations, estimate its frequency and duration, and compare it to other acute illnesses in a cohort of people with suspected Zika infection, in the region of Tapachula in Chiapas, Mexico during 2016-2018. We enrolled patients who were at least 12 years old with suspected Zika virus infection and followed them up for 6 months. During each visit participants underwent a complete clinical exam, including a screening test for neurocognitive dysfunction (Montreal Cognitive Assessment score). We enrolled 406 patients [37 with Zika, 73 with dengue and 296 with other acute illnesses of unidentified origin (AIUO)]. We observed a mild and transient impact over cognitive functions in patients with Zika, dengue and with other AIUO. The probability of having an abnormal MoCA score (<26 points) was significantly higher in patients with Zika and AIUO than in those with dengue. Patients with Zika and AIUO had lower memory scores than patients with dengue (Zika vs. Dengue: -0.378, 95% CI-0.678 to -0.078; p = 0.014: Zika vs. AIUO 0.264, 95% CI 0.059, 0.469; p = 0.012). The low memory performance in patients with Zika and AIUO accounts for most of the differences in the overall MoCA score when compared with patients with dengue. Our results show a decrease in cognitive function during acute illness and provides no evidence to support the hypothesis that Zika might cause neurocognitive alterations longer than the period of acute infection or different to other infectious diseases. While effects on memory or perhaps other cognitive functions over the long term are possible, larger studies using more refined tools for neurocognitive functioning assessment are needed to identify these. Trial Registration: NCT02831699.

Prevalence of mild cognitive impairment in surgical menopause: subtypes and associated factors

OBJECTIVE

The aim of this study was to determine the prevalence and associated factors of mild cognitive impairment (MCI) and subtypes, amnestic MCI (aMCI) and non-amnestic MCI (naMCI), in women with surgical menopause.

METHODS

We obtained the database containing information for 200 women with surgical menopause from our previous study. The Montreal Cognitive Assessment - total score, the Montreal Cognitive Assessment - memory index score (MoCA-MIS) and their age, years since menopause, education, medical and surgical history, hormone therapy use, exercise, sleep duration, alcohol use, smoking and family history of dementia were obtained. All participants without the MoCA-MIS were excluded.

RESULT

The average age of the 164 participants was 56.3 ± 6.9 years. The prevalence of MCI, aMCI and naMCI was 43.3%, 9.8% and 33.5%, respectively. The duration of education reduced MCI for 93% (95% confidence interval 0.03-0.20) of the women. In late postmenopause, hormone therapy >10 years showed 47% lower prevalence of MCI (age-adjusted odds ratio = 0.53, 95% confidence interval 0.22-1.28). Finally, length of education was the only independent factor associated with MCI and its subtypes.

CONCLUSION

We found a high prevalence of MCI and the non-amnestic subtype in women with surgical menopause. Further study is needed to clarify the long-term effects of surgical menopause on cognitive function.

Machine learning methods to predict amyloid positivity using domain scores from cognitive tests

Amyloid-[Formula: see text] (A[Formula: see text]) is the target in many clinical trials for Alzheimer's disease (AD). Preclinical AD patients are heterogeneous with regards to different backgrounds and diagnosis. Accurately predicting A[Formula: see text] status of participants by using machine learning (ML) models based on easily accessible data, could improve the effectiveness of AD clinical trials. We will develop optimal ML models for each subpopulation stratified by sex and disease stages using sub scores from screening neurological tests. Data from the AD Neuroimaging Initiative (ADNI) were used to build the ML models, for three groups: individuals with significant memory concern, early mild cognitive impairment (MCI), and late MCI. Data were further separated into 6 groups by disease stage (3 levels) and sex (2 categories). The outcome was defined as the A[Formula: see text] status confirmed by the PET imaging, and the features include demographic data, newly identified risk factors, screening tests, and the domain scores from screening tests. Monte Carlo simulation studies were used together with k-fold cross-validation technique to compute model performance metric. We also develop a new feature selection method based on the stochastic ordering to avoiding searching all possible combinations of features. Accuracy of the identified optimal model for SMC male was over 90% by using domain scores, and accuracy for LMCI female was above 86%. Domain scores can improve the ML model prediction as compared to the total scores. Accurate ML prediction models can identify the proper population for AD clinical trials.

The Use of Random Forests to Identify Brain Regions on Amyloid and FDG PET Associated With MoCA Score

PURPOSE

The aim of this study was to evaluate random forests (RFs) to identify ROIs on F-florbetapir and F-FDG PET associated with Montreal Cognitive Assessment (MoCA) score.

MATERIALS AND METHODS

Fifty-seven subjects with significant white matter disease presenting with either transient ischemic attack/lacunar stroke or mild cognitive impairment from early Alzheimer disease, enrolled in a multicenter prospective observational trial, had MoCA and F-florbetapir PET; 55 had F-FDG PET. Scans were processed using the MINC toolkit to generate SUV ratios, normalized to cerebellar gray matter (F-florbetapir PET), or pons (F-FDG PET). SUV ratio data and MoCA score were used for supervised training of RFs programmed in MATLAB.

RESULTS

F-Florbetapir PETs were randomly divided into 40 training and 17 testing scans; 100 RFs of 1000 trees, constructed from a random subset of 16 training scans and 20 ROIs, identified ROIs associated with MoCA score: right posterior cingulate gyrus, right anterior cingulate gyrus, left precuneus, left posterior cingulate gyrus, and right precuneus. Amyloid increased with decreasing MoCA score. F-FDG PETs were randomly divided into 40 training and 15 testing scans; 100 RFs of 1000 trees, each tree constructed from a random subset of 16 training scans and 20 ROIs, identified ROIs associated with MoCA score: left fusiform gyrus, left precuneus, left posterior cingulate gyrus, right precuneus, and left middle orbitofrontal gyrus. F-FDG decreased with decreasing MoCA score.

CONCLUSIONS

Random forests help pinpoint clinically relevant ROIs associated with MoCA score; amyloid increased and F-FDG decreased with decreasing MoCA score, most significantly in the posterior cingulate gyrus.

Brain volumes and dual-task performance correlates among individuals with cognitive impairment: a retrospective analysis

Cognitive impairment (CI) is a prevalent condition characterized by loss of brain volume and changes in cognition, motor function, and dual-tasking ability. To examine associations between brain volumes, dual-task performance, and gait and balance in those with CI to elucidate the mechanisms underlying loss of function. We performed a retrospective analysis of medical records of patients with CI and compared brain volumes, dual-task performance, and measures of gait and balance. Greater cognitive and combined dual-task effects (DTE) are associated with smaller brain volumes. In contrast, motor DTE is not associated with distinct pattern of brain volumes. As brain volumes decrease, dual-task performance becomes more motor prioritized. Cognitive DTE is more strongly associated with decreased performance on measures of gait and balance than motor DTE. Decreased gait and balance performance are also associated with increased motor task prioritization. Cognitive DTE appears to be more strongly associated with decreased automaticity and gait and balance ability than motor DTE and should be utilized as a clinical and research outcome measure in this population. The increased motor task prioritization associated with decreased brain volume and function indicates a potential for accommodative strategies to maximize function in those with CI. Counterintuitive correlations between motor brain volumes and motor DTE in our study suggest a complicated interaction between brain pathology and function.

Interindividual Differences in Cognitive Functioning Are Associated with Autobiographical Memory Retrieval Specificity in Older Adults

Abstract. We examined whether interindividual differences in cognitive functioning among older adults are related to episodic memory engagement during autobiographical memory retrieval. Older adults ( n = 49, 24 males; mean age = 69.93; mean education = 15.45) with different levels of cognitive functioning, estimated using the Montreal Cognitive Assessment (MoCA), retrieved multiple memories (generation task) and the details of a single memory (elaboration task) to cues representing thematic or event-specific autobiographical knowledge. We found that the MoCA score positively predicted the proportion of specific memories for generation and episodic details for elaboration, but only to cues that represented event-specific information. The results demonstrate that individuals with healthy, but not unhealthy, cognitive status can leverage contextual support from retrieval cues to improve autobiographical specificity.

Relationship Between the Japanese Version of the Montreal Cognitive Assessment and PET Imaging in Subjects with Mild Cognitive Impairment

BACKGROUND

The Montreal Cognitive Assessment (MoCA) test has high sensitivity and specificity for detecting mild cognitive impairment or early dementia. How the MoCA score relates to findings of positron emission tomography imaging, however, remains unclear.

OBJECTIVE

This prospective study examined the relationship between the Japanese version of the MoCA (MoCA-J) test and brain amyloid deposition or cerebral glucose metabolism among subjects with mild cognitive impairment.

METHODS

A total of 125 subjects with mild cognitive impairment underwent the MoCA-J test, and amyloid- and 18F-fluorodeoxyglucose- positron emission tomography. Linear correlation analysis and multiple linear regression analysis were conducted to investigate the relationship between the MoCA-J score and demographic characteristics, amyloid deposition, and cerebral glucose metabolism. Moreover, Statistical Parametric Mapping 8 was used for a voxel-wise regression analysis of the MoCA-J score and cerebral glucose metabolism.

RESULTS

The MoCA-J score significantly correlated with age, years of education, and the Mini-Mental State Examination score. After adjusting for age, sex, and education, the MoCA-J score significantly correlated negatively with amyloid retention (β= -0.174, p= 0.031) and positively with cerebral glucose metabolism (β= 0.183, p= 0.044). Statistical Parametric Mapping showed that Japanese version of MoCA score correlated with glucose metabolism in the bilateral frontal and parietal lobes, and the left precuneus.

CONCLUSION

The total MoCA-J score correlated with amyloid deposition and frontal and parietal glucose metabolism in subjects with mild cognitive impairment. Our findings support the usefulness of the MoCA-J test for screening subjects at high risk for Alzheimer's disease.

Nutritional ketosis for mild cognitive impairment in Parkinson's disease: A controlled pilot trial

INTRODUCTION

Glucose hypometabolism and insulin resistance increase risk for and accelerate progression in Parkinson's disease and neurocognitive disorders. We conducted a proof of concept trial to determine whether ketogenesis, a metabolic adaptation induced by dietary carbohydrate restriction, can improve cognitive performance in Parkinson's disease patients with mild cognitive impairment.

METHODS

We enrolled patients with mild cognitive impairment associated with Parkinson's disease in an eight-week nutritional intervention with random assignment to either high-carbohydrate consumption typical of the Western dietary pattern (n = 7) or to a low-carbohydrate, ketogenic regimen (n = 7). We assessed changes in cognitive performance as well as motor function, anthropometrics, and metabolic parameters.

RESULTS

Relative to the high-carbohydrate group, the low-carbohydrate group demonstrated improvements in lexical access (p = 0.02, Cohen's f effect size = 0.76) and memory (p = 0.01, f = 0.87) and as well as a trend for reduced interference in memory (p = 0.06, f = 0.60). The low-carbohydrate group also exhibited reduced body weight (p < 0.0001, f = 1.89) and increased circulation of beta-hydroxybutyrate (p = 0.01, f = 0.90). Change in body weight was strongly associated with memory performance (p = 0.001). Motor function was not affected by the intervention.

CONCLUSION

Nutritional ketosis enhanced cognitive performance in Parkinson's disease-associated mild cognitive impairment in this pilot study. This metabolic intervention and its mechanisms deserve further investigation in the context of neurodegeneration.

Recalling the firedog: Individual differences in associative memory for unitized and nonunitized associations among older adults

Memory deficits in aging are characterized by impaired hippocampus-mediated relational binding-the formation of links between items in memory. By reducing reliance on relational binding, unitization of two items into one concept enhances associative recognition among older adults. Can a similar enhancement be obtained when probing memory with recall? This question has yet to be examined, because recall has been assumed to rely predominantly on relational binding. Inspired by recent evidence challenging this assumption, we investigated individual differences in older adults' recall of unitized and nonunitized associations. Compared with successfully aging individuals, older adults with mild memory deficits, typically mediated by the hippocampus, were impaired in recall of paired-associates in a task which relies on relational binding (study: "PLAY-TUNNEL"; test: PLAY-T?). In stark contrast, the two groups showed similar performance when items were unitized into a novel compound word (study: "LOVEGIGGLE"; test: LOVEG?). Thus, boosting nonrelational aspects of recall enhances associative memory among aging individuals with subtle memory impairments to comparable levels as successfully aging older adults.

Normative data for the Montreal Cognitive Assessment (MoCA) and the Memory Index Score (MoCA-MIS) in Brazil: Adjusting the nonlinear effects of education with fractional polynomials

OBJECTIVE

To provide age-corrected and education-corrected norms for the Montreal Cognitive Assessment (MoCA) and the Memory Index Score (MoCA-MIS) in Brazil.

METHODS

Community-dwelling outpatients were enrolled if they had no history of neurologic or psychiatric diseases and were not taking any drugs with effects on the central nervous system. Dementia has been excluded with the Functional Activities Questionnaire. The final sample consisted of 597 cognitively healthy Brazilians aged 50 to 90 years. To account for nonlinear relationships, we have used fractional polynomials that provide a flexible parameterization for continuous variables.

RESULTS

According to the original proposed cutoff (≤25 points), 87% of our sample would be considered impaired. Even using a more conservative suggestion (≤22 points), 67% of our normative sample would be regarded as impaired. These data reinforce the need of adjusting cutoffs for schooling in populations with heterogeneous educational backgrounds. MoCA scores presented a nonlinear positive association with education tending to a plateau at higher levels (P < 0.001). On the other hand, MoCA-MIS scores presented a nonlinear negative relationship with age, with an accelerated pattern at higher age levels (P < 0.001).

CONCLUSIONS

We presented normative data for the MoCA and the MoCA-MIS that will facilitate the use of the test in Brazil and, potentially, in other populations with substantial proportions of low-educated individuals. Moreover, we described a systematic approach for adjusting the effects of age and education using fractional polynomials and provided suggestions on how to account for the nonlinear relationship that is frequently encountered between demographic factors and measures of cognitive performance.