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.

Cross-sectional study.

1Florida Alzheimer’s Disease Research Center baseline study.

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).

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.

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.

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.

Dopaminergic imaging is an established biomarker for dementia with Lewy bodies, but its diagnostic accuracy at the mild cognitive impairment (MCI) stage remains uncertain.

To provide robust prospective evidence of the diagnostic accuracy of dopaminergic imaging at the MCI stage to either support or refute its inclusion as a biomarker for the diagnosis of MCI with Lewy bodies.

We conducted a prospective diagnostic accuracy study of baseline dopaminergic imaging with [123I]N-ω-fluoropropyl-2β-carbomethoxy-3β-(4-iodophenyl)nortropane single-photon emission computerised tomography (123I-FP-CIT SPECT) in 144 patients with MCI. Images were rated as normal or abnormal by a panel of experts with access to striatal binding ratio results. Follow-up consensus diagnosis based on the presence of core features of Lewy body disease was used as the reference standard.

At latest assessment (mean 2 years) 61 patients had probable MCI with Lewy bodies, 26 possible MCI with Lewy bodies and 57 MCI due to Alzheimer's disease. The sensitivity of baseline FP-CIT visual rating for probable MCI with Lewy bodies was 66% (95% CI 52–77%), specificity 88% (76–95%) and accuracy 76% (68–84%), with positive likelihood ratio 5.3.

It is over five times as likely for an abnormal scan to be found in probable MCI with Lewy bodies than MCI due to Alzheimer's disease. Dopaminergic imaging appears to be useful at the MCI stage in cases where Lewy body disease is suspected clinically.

To compare cognitive phenotypes of participants with subjective cognitive decline (SCD) and amnestic mild cognitive impairment (aMCI), estimate progression to MCI/dementia by phenotype and assess classification error with machine learning.

Dataset consisted of 163 participants with SCD and 282 participants with aMCI from the Czech Brain Aging Study. Cognitive assessment included the Uniform Data Set battery and additional tests to ascertain executive function, language, immediate and delayed memory, visuospatial skills, and processing speed. Latent profile analyses were used to develop cognitive profiles, and Cox proportional hazards models were used to estimate risk of progression. Random forest machine learning algorithms reported cognitive phenotype classification error.

Latent profile analysis identified three phenotypes for SCD, with one phenotype performing worse across all domains but not progressing more quickly to MCI/dementia after controlling for age, sex, and education. Three aMCI phenotypes were characterized by mild deficits, memory and language impairment (dysnomic aMCI), and severe multi-domain aMCI (i.e., deficits across all domains). A dose–response relationship between baseline level of impairment and subsequent risk of progression to dementia was evident for aMCI profiles after controlling for age, sex, and education. Machine learning more easily classified participants with aMCI in comparison to SCD (8% vs. 21% misclassified).

Cognitive performance follows distinct patterns, especially within aMCI. The patterns map onto risk of progression to dementia.

Rey’s Auditory Verbal Learning Test (AVLT) is a widely used word list memory test. We update normative data to include adjustment for verbal memory performance differences between men and women and illustrate the effect of this sex adjustment and the importance of excluding participants with mild cognitive impairment (MCI) from normative samples.

This study advances the Mayo’s Older Americans Normative Studies (MOANS) by using a new population-based sample through the Mayo Clinic Study of Aging, which randomly samples residents of Olmsted County, Minnesota, from age- and sex-stratified groups. Regression-based normative T-score formulas were derived from 4428 cognitively unimpaired adults aged 30–91 years. Fully adjusted T-scores correct for age, sex, and education. We also derived T-scores that correct for (1) age or (2) age and sex. Test-retest reliability data are provided.

From raw score analyses, sex explained a significant amount of variance in performance above and beyond age (8–10%). Applying original age-adjusted MOANS norms to the current sample resulted in significantly fewer-than-expected participants with low delayed recall performance, particularly in women. After application of new T-scores adjusted only for age, even in normative data derived from this sample, these age-adjusted T-scores showed scores <40 T occurred more frequently among men and less frequently among women relative to T-scores that also adjusted for sex.

Our findings highlight the importance of using normative data that adjust for sex with measures of verbal memory and provide new normative data that allow for this adjustment for the AVLT.

Patients with mild Alzheimer’s disease dementia are more susceptible to false memories than healthy older adults. Evidence that these patients can use cognitive strategies to reduce false memory is inconsistent.

In the present study, we examined the effectiveness of conservative responding and item-specific deep encoding strategies, alone and in combination, to reduce false memory in a categorized word list paradigm among participants with mild Alzheimer’s disease dementia (AD), amnestic single-domain mild cognitive impairment (MCI), and healthy age-matched older controls (OCs). A battery of clinical neuropsychological measures was also administered.

Although use of conservative responding alone tended to reduce performance in the MCI and OC groups, both deep encoding alone and deep encoding combined with conservative strategies led to improved discrimination for both gist memory and item-specific recollection for these two groups. In the AD group, only gist memory benefited from the use of strategies, boosted equally by deep encoding alone and deep encoding combined with conservative strategies; item-specific recollection was not improved. No correlation between the use of these strategies and performance on neuropsychological measures was found.

These results suggest that further evaluation of these strategies is warranted as they have the potential to reduce related and unrelated memory errors and increase both gist memory and item-specific recollection in healthy older adults and individuals with amnestic MCI. Patients with AD were less able to benefit from such strategies, yet were still able to use them to reduce unrelated memory errors and increase gist memory.

Previous research on art therapy (AT) in cognitive aging has been lacking. AT can potentially engender significant cognitive gains, due to its rigorous cognitive involvement, making it useful to tackle age-related cognitive decline. Along with these cognitive gains, associated neuroplastic changes are hypothesized to arise from AT as well. The current intervention examined the effects of an AT intervention on cognitive outcomes and cortical thickness (CT) among participants with mild cognitive impairment.

Participants were assigned to AT (n = 22) and an active control group (n = 27). In both, weekly 45-min sessions were carried out across 3 months. Cognitive assessments and structural magnetic resonance imaging scans were carried out at baseline and 3-month follow-up. Whole brain analyses on CT were carried out. Cognitive outcomes were analyzed using hierarchical linear models.

Significant gains in immediate memory and working memory span were observed in the AT group, relative to the control group. Significantly increased CT in the AT group, relative to controls, was observed in a right middle frontal gyrus (MFG) cluster. Furthermore, CT changes in this cluster were significantly and positively correlated with changes in immediate memory.

These findings highlighted the role of MFG neuroplasticity in enhancing certain cognitive functions in AT. AT is a neuroplastic intervention capable of engendering significant cognitive gains and associated cortical changes in the context of age-related cognitive decline, even when executed as a low-intensity intervention across 3 months. Given the preliminary nature of these findings, future larger sampled studies are needed.

Given a large number of community-based older adults with mild cognitive impairment, it is essential to better understand the relationship between unmet palliative care (PC) needs and mild cognitive impairment in community-based samples.

Participants consisted of adults ages 60+ receiving services at senior centers located in New York City. The Montreal Cognitive Assessment (MoCA) and the Unmet Palliative Care Needs screening tool were used to assess participants’ cognitive status and PC needs.

Our results revealed a quadratic relationship between unmet PC needs and mild cognitive impairment, controlling for gender, living status, and age. Participants with either low or high MoCA scores reported lower PC needs than participants with average MoCA scores, mean difference of the contrast (low and high vs. middle) = 2.15, P = 0.08.

This study is a first step toward elucidating the relationship between cognitive impairment and PC needs in a diverse community sample of older adults. More research is needed to better understand the unique PC needs of older adults with cognitive impairment living in the community.

To assess the influence of mild behavioral impairment (MBI) on the cognitive performance of older adults who are cognitively healthy or have mild cognitive impairment (MCI).

Secondary data analysis of a sample (n = 497) of older adults from the Florida Alzheimer’s Disease Research Center who were either cognitively healthy (n = 285) or diagnosed with MCI (n = 212). Over half of the sample (n = 255) met the operationalized diagnostic criteria for MBI. Cognitive domains of executive function, attention, short-term memory, and episodic memory were assessed using a battery of neuropsychological tests.

Older adults with MBI performed worse on tasks of executive function, attention, and episodic memory compared to those without MBI. A significant interaction revealed that persons with MBI and MCI performed worse on tasks of episodic memory compared to individuals with only MCI, but no significant differences were found in performance in cognitively healthy older adults with or without MBI on this cognitive domain. As expected, cognitively healthy older adults performed better than individuals with MCI on every domain of cognition.

The present study found evidence that independent of cognitive status, individuals with MBI performed worse on tests of executive function, attention, and episodic memory than individuals without MBI. Additionally, those with MCI and MBI perform significantly worse on episodic memory tasks than individuals with only MCI. These results provide support for a unique cognitive phenotype associated with MBI and highlight the necessity for assessing both cognitive and behavioral symptoms.

Mild cognitive impairment (MCI), as a stage in the cognitive continuum between normal ageing and dementia, is mainly characterized by memory impairment. The aims of this study were to examine CANTAB measures of temporal changes of visual memory in MCI and to evaluate the usefulness of the baseline scores for predicting changes in cognitive status.

The study included 201 participants aged over 50 years with subjective cognitive complaints. Visual memory was assessed with four CANTAB tests [paired associates learning (PAL), delayed matching to sample (DMS), pattern recognition memory (PRM) and spatial span (SSP)] administered at baseline and on two further occasions, with a follow-up interval of 18–24 months. Participants were divided into three groups according to the change in their cognitive status: participants with subjective cognitive complaints who remained stable, MCI participants who remained stable (MCI-Stable) and MCI participants whose cognitive deterioration continued (MCI-Worsened). Linear mixed models were used to model longitudinal changes, with evaluation time as a fixed variable, and multinomial regression models were used to predict changes in cognitive status.

Isolated significant effects were obtained for age and group with all CANTAB tests used. Interactions between evaluation time and group were identified in the PAL and DMS tests, indicating different temporal patterns depending on the changes in cognitive status. Regression models also indicated that CANTAB scores were good predictors of changes in cognitive status.

Decline in visual memory measured by PAL and DMS tests can successfully distinguish different types of MCI, and considered together PAL, DMS, PRM and SSP can predict changes in cognitive status.

Mild cognitive impairment (MCI) may gradually worsen to dementia, but often remains stable for extended periods of time. Little is known about the predictors of decline to help explain this variation. We aimed to explore whether this heterogeneous course of MCI may be predicted by the presence of Lewy body (LB) symptoms in a prospectively-recruited longitudinal cohort of MCI with Lewy bodies (MCI-LB) and Alzheimer's disease (MCI-AD).

A prospective cohort (n = 76) aged ⩾60 years underwent detailed assessment after recent MCI diagnosis, and were followed up annually with repeated neuropsychological testing and clinical review of cognitive status and LB symptoms. Latent class mixture modelling identified data-driven sub-groups with distinct trajectories of global cognitive function.

Three distinct trajectories were identified in the full cohort: slow/stable progression (46%), intermediate progressive decline (41%) and a small group with a much faster decline (13%). The presence of LB symptomology, and visual hallucinations in particular, predicted decline v. a stable cognitive trajectory. With time zeroed on study end (death, dementia or withdrawal) where available (n = 39), the same subgroups were identified. Adjustment for baseline functioning obscured the presence of any latent classes, suggesting that baseline function is an important parameter in prospective decline.

These results highlight some potential signals for impending decline in MCI; poorer baseline function and the presence of probable LB symptoms – particularly visual hallucinations. Identifying people with a rapid decline is important but our findings are preliminary given the modest cohort size.

Individuals with subjective cognitive impairment (SCI) have persistent memory complaints but normal neurocognitive performance. For some, this may represent a pre-mild cognitive impairment (MCI) stage of Alzheimer's disease (AD). Given that attentional deficits and associated brain activation changes are present early in the course of AD, we aimed to determine whether SCI is associated with brain activation changes during attentional processing.

Eleven SCI subjects and 10 controls completed a divided attention task during functional magnetic resonance imaging.

SCI and control groups did not differ in sociodemographic, neurocognitive or behavioural measures. When group activation during the divided attention task was compared, the SCI group demonstrated increased activation in left medial temporal lobe, bilateral thalamus, posterior cingulate and caudate.

This pattern of increased activation is similar to the pattern of decreased activation reported during divided attention in AD and may indicate compensatory changes. These findings suggest the presence of early functional changes in SCI; longitudinal studies will help to further elucidate the relationship between SCI and AD.

To determine how well machine learning algorithms can classify mild cognitive impairment (MCI) subtypes and Alzheimer’s disease (AD) using features obtained from the digital Clock Drawing Test (dCDT).

dCDT protocols were administered to 163 patients diagnosed with AD(n = 59), amnestic MCI (aMCI; n = 26), combined mixed/dysexecutive MCI (mixed/dys MCI; n = 43), and patients without MCI (non-MCI; n = 35) using standard clock drawing command and copy procedures, that is, draw the face of the clock, put in all of the numbers, and set the hands for “10 after 11.” A digital pen and custom software recorded patient’s drawings. Three hundred and fifty features were evaluated for maximum information/minimum redundancy. The best subset of features was used to train classification models to determine diagnostic accuracy.

Neural network employing information theoretic feature selection approaches achieved the best 2-group classification results with 10-fold cross validation accuracies at or above 83%, that is, AD versus non-MCI = 91.42%; AD versus aMCI = 91.49%; AD versus mixed/dys MCI = 84.05%; aMCI versus mixed/dys MCI = 84.11%; aMCI versus non-MCI = 83.44%; and mixed/dys MCI versus non-MCI = 85.42%. A follow-up two-group non-MCI versus all MCI patients analysis yielded comparable results (83.69%). Two-group classification analyses were achieved with 25–125 dCDT features depending on group classification. Three- and four-group analyses yielded lower but still promising levels of classification accuracy.

Early identification of emergent neurodegenerative illness is criterial for better disease management. Applying machine learning to standard neuropsychological tests promises to be an effective first line screening method for classification of non-MCI and MCI subtypes.

The Apolipoprotein (APOE) ε4 allele increases the risk for mild cognitive impairment (MCI) and dementia, but not all carriers develop MCI/dementia. The purpose of this exploratory study was to determine if early and subtle preclinical signs of cognitive dysfunction and medial temporal lobe atrophy are observed in cognitively intact ε4 carriers who subsequently develop MCI.

Twenty-nine healthy, cognitively intact ε4 carriers (ε3/ε4 heterozygotes; ages 65–85) underwent neuropsychological testing and MRI-based measurements of medial temporal volumes over a 5-year follow-up interval; data were converted to z-scores based on a non-carrier group consisting of 17 ε3/ε3 homozygotes.

At follow-up, 11 ε4 carriers (38%) converted to a diagnosis of MCI. At study entry, the MCI converters had significantly lower scores on the Mini-Mental State Examination, Rey Auditory Verbal Learning Test (RAVLT) Trials 1–5, and RAVLT Immediate Recall compared to non-converters. MCI converters also had smaller MRI volumes in the left subiculum than non-converters. Follow-up logistic regressions revealed that left subiculum volumes and RAVLT Trials 1–5 scores were significant predictors of MCI conversion.

Results from this exploratory study suggest that ε4 carriers who convert to MCI exhibit subtle cognitive and volumetric differences years prior to diagnosis.