Changes in visual memory in mild cognitive impairment: a longitudinal study with CANTAB.

BACKGROUND: 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. METHODS: 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. RESULTS: 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. CONCLUSIONS: 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.

Cognitive reserve and working memory in cognitive performance of adults with subjective cognitive complaints: longitudinal structural equation modeling.

OBJECTIVE: To study the influence of cognitive reserve (CR) on cognitive performance of individuals with subjective cognitive complaints (SCCs) within a period of 36 months. DESIGN: We used a general linear model repeated measures procedure to analyze the differences in performance between three assessments. We used a longitudinal structural equation modeling to analyze the relationship between CR and cognitive performance at baseline and at two follow-up assessments. SETTING: Participants with SCCs were recruited and assessed in primary care health centers. PARTICIPANTS: A total of 212 participants older than 50 years with SCCs. MEASUREMENTS: Cognitive reserve data were collected with an ad hoc questionnaire administered to the subjects in an interview. General cognitive performance (GCP), episodic memory (EM), and working memory (WM) have been evaluated. The Mini-Mental State Examination and the total score of Spanish version of the Cambridge Cognitive Examination evaluated the GCP. Episodic memory was assessed with the Spanish version of the California Verbal Learning. Working memory was evaluated by the counting span task and the listening span task. RESULTS: The satisfactory fit of the proposed model confirmed the direct effects of CR on WM and GCP at baseline, as well as indirect effects on EM and WM at first and second follow-up. Indirect effects of CR on other cognitive constructs via WM were observed over time. CONCLUSION: The proposed model is useful for measuring the influence of CR on cognitive performance over time. Cognitive response acquired throughout life may influence cognitive performance in old age and prevent cognitive deterioration, thus increasing processing resources via WM.

Neuropsychiatric symptoms as predictors of conversion from MCI to dementia: a machine learning approach.

OBJECTIVES: To use a Machine Learning (ML) approach to compare Neuropsychiatric Symptoms (NPS) in participants of a longitudinal study who developed dementia and those who did not. DESIGN: Mann-Whitney U and ML analysis. Nine ML algorithms were evaluated using a 10-fold stratified validation procedure. Performance metrics (accuracy, recall, F-1 score, and Cohen's kappa) were computed for each algorithm, and graphic metrics (ROC and precision-recall curves) and features analysis were computed for the best-performing algorithm. SETTING: Primary care health centers. PARTICIPANTS: 128 participants: 78 cognitively unimpaired and 50 with MCI. MEASUREMENTS: Diagnosis at baseline, months from the baseline assessment until the 3rd follow-up or development of dementia, gender, age, Charlson Comorbidity Index, Neuropsychiatric Inventory-Questionnaire (NPI-Q) individual items, NPI-Q total severity, and total stress score and Geriatric Depression Scale-15 items (GDS-15) total score. RESULTS: 30 participants developed dementia, while 98 did not. Most of the participants who developed dementia were diagnosed at baseline with amnestic multidomain MCI. The Random Forest Plot model provided the metrics that best predicted conversion to dementia (e.g. accuracy=.88, F1=.67, and Cohen's kappa=.63). The algorithm indicated the importance of the metrics, in the following (decreasing) order: months from first assessment, age, the diagnostic group at baseline, total NPI-Q severity score, total NPI-Q stress score, and GDS-15 total score. CONCLUSIONS: ML is a valuable technique for detecting the risk of conversion to dementia in MCI patients. Some NPS proxies, including NPI-Q total severity score, NPI-Q total stress score, and GDS-15 total score, were deemed as the most important variables for predicting conversion, adding further support to the hypothesis that some NPS are associated with a higher risk of dementia in MCI.

Design of optimal nonlinear network controllers for Alzheimer's disease.

Brain stimulation can modulate the activity of neural circuits impaired by Alzheimer's disease (AD), having promising clinical benefit. However, all individuals with the same condition currently receive identical brain stimulation, with limited theoretical basis for this generic approach. In this study, we introduce a control theory framework for obtaining exogenous signals that revert pathological electroencephalographic activity in AD at a minimal energetic cost, while reflecting patients' biological variability. We used anatomical networks obtained from diffusion magnetic resonance images acquired by the Alzheimer's Disease Neuroimaging Initiative (ADNI) as mediators for the interaction between Duffing oscillators. The nonlinear nature of the brain dynamics is preserved, given that we extend the so-called state-dependent Riccati equation control to reflect the stimulation objective in the high-dimensional neural system. By considering nonlinearities in our model, we identified regions for which control inputs fail to correct abnormal activity. There are changes to the way stimulated regions are ranked in terms of the energetic cost of controlling the entire network, from a linear to a nonlinear approach. We also found that limbic system and basal ganglia structures constitute the top target locations for stimulation in AD. Patients with highly integrated anatomical networks-namely, networks having low average shortest path length, high global efficiency-are the most suitable candidates for the propagation of stimuli and consequent success on the control task. Other diseases associated with alterations in brain dynamics and the self-control mechanisms of the brain can be addressed through our framework.

Assessing mild behavioral impairment with the mild behavioral impairment checklist in people with subjective cognitive decline.

ABSTRACTObjectives:To estimate the prevalence of Mild Behavioral Impairment (MBI) in people with Subjective Cognitive Decline (SCD), and validate the Mild Behavioral Impairment Checklist (MBI-C) with respect to score distribution, sensitivity, specificity, and utility for MBI diagnosis, as well as correlation with other neuropsychological tests. DESIGN: Correlational study with a convenience sampling. Descriptive, logistic regression, ROC curve, and bivariate correlations analyses were performed. SETTING: Primary care health centers. PARTICIPANTS: 127 patients with SCD. MEASUREMENTS: An extensive evaluation, including Questionnaire for Subjective Memory Complaints, Mini-Mental State Examination, Cambridge Cognitive Assessment-Revised, Neuropsychiatric Inventory-Questionnaire (NPI-Q), the Geriatric Depression Scale-15 items (GDS-15), the Lawton and Brody Index and the MBI-C, which was administered by phone to participants' informants. RESULTS: MBI prevalence was 5.8% in those with SCD. The total MBI-C scoring was low and differentiated people with MBI at a cut-off point of 8.5 (optimizing sensitivity and specificity). MBI-C total scoring correlated positively with NPI-Q, Questionnaire for Subjective Cognitive Complaints (QSCC) from the informant and GDS-15. CONCLUSIONS: The phone administration of the MBI-C is useful for detecting MBI in people with SCD. The prevalence of MBI in SCD was low. The MBI-C detected subtle Neuropsychiatric symptoms (NPS) that were correlated with scores on the NPI-Q, depressive symptomatology (GDS-15), and memory performance perceived by their relatives (QSCC). Next steps are to determine the predictive utility of MBI in SCD, and its relation to incident cognitive decline over time.

Do informant-reported subjective cognitive complaints predict progression to mild cognitive impairment and dementia better than self-reported complaints in old adults? A meta-analytical study.

BACKGROUND: Subjective cognitive complaints (SCCs) are considered a risk factor for objective cognitive decline and conversion to dementia. The aim of this study was to determine whether self-reported or informant-reported SCCs best predict progression to mild cognitive impairment (MCI) and/or dementia. METHODS: We reviewed prospective longitudinal studies of Cognitively Unimpaired (CU) older adults with self-reported and informant-reported SCCs at baseline, assessed by questions or questionnaires that considered the transition to MCI and/or dementia. A random-effects meta-analysis was performed to obtain pooled estimates and 95% CIs. RESULTS: Both self-reported and informant-reported SCCs are associated with an elevated risk of transition from CU to MCI and/or dementia. The association appears stronger and more robust for informant-reported data [1.38, with a 95% CI of 1.16 -1.64, p < 0.001] than for self-reported data [1.27 (95% CI 1.06 - 1.534, p = 0.011]. CONCLUSIONS: Our results suggest that corroborated information from one informant could provide important details for distinguishing between normal aging and clinical states.

Spanish Consortium for Ageing Normative Data (SCAND): Semantic Verbal Fluency Tests.

OBJECTIVE: Semantic verbal fluency constitutes a good candidate for identifying cognitive impairment. This paper offers normative data of different semantic verbal fluency tests for middle-aged and older adults natives from Spain considering sociodemographic factors, and different measures for each specific category (number of words produced, errors, and words evoked every 15 s). METHOD: Two thousand and eighty-eight cognitively unimpaired subjects aged between 50 and 89 years old, community dwelling, participated in the study. The statistical procedure includes the conversion of percentile ranges into scalar scores. Secondly, the effects of age, education and gender were verified. Linear regressions are used to calculate the scalar adjusted scores. RESULTS: Scalar scores and percentiles corresponding to all semantic verbal fluency tests across different measures are shown. Additional tables, which show the points that must be added or subtracted from direct scores, are provided for Education regarding the total number of "animals" and "clothes" evoked by participants, as well as for Age and Education in case of the total number of "clothes". Gender affects the number of "clothes" produced by participants in the first two 15-second segments. CONCLUSIONS: The current norms should provide clinically useful data for evaluating Spanish-speaking natives from Spain aged from 50 to 89 years.

Does the neuropsychiatric inventory predict progression from mild cognitive impairment to dementia? A systematic review and meta-analysis.

BACKGROUND: Neuropsychiatric Symptoms (NPS) are common in Mild Cognitive Impairment (MCI). The Neuropsychiatric Inventory (NPI) and its shorter version, the Neuropsychiatric Inventory Questionnaire (NPI-Q), are the most common measures to assess NPS. Our objective was to determine if NPI/NPI-Q ratings predict conversion from MCI to dementia. METHODS: Empirical longitudinal studies published in English or Spanish, concerned with the role of NPS as a risk factor for conversion from MCI to dementia, with a diagnosis of MCI following clinical criteria, that reported NPI/NPI-Q total score in converters versus non-converters, were included. Random effects models were used, and heterogeneity was explored with stratification and a random-effects meta-regression. The overall conversion rate and the standardized mean difference (SMD) for evolution, as a function of NPI/NPI-Q scores, were calculated. RESULTS: The overall conversion rate was 35 %. Mean NPI/NPI-Q ratings were higher in converters versus in non-converters, with the overall SMD approaching significance. Heterogeneity was observed in studies of more than two years of follow-up and in a study with a mean age of more than 80 years. This heterogeneity concerned the size, not the direction of the difference. CONCLUSIONS: Our results suggest that NPI/NPI-Q ratings are associated with conversion from MCI to dementia.

Longitudinal Patterns of the Tip-of-the-Tongue Phenomenon in People With Subjective Cognitive Complaints and Mild Cognitive Impairment.

BACKGROUND: The Tip-of-the-Tongue (ToTs) state is considered a universal phenomenon and is a frequent cognitive complaint in old age. Previous cross-sectional studies have found that ToT measures successfully discriminate between cognitively unimpaired adults and adults with Mild Cognitive Impairment (MCI). The aim of this study was to identify longitudinal patterns of ToTs in individuals with subjective complaints and with MCI regarding progress of their cognitive status. METHOD: The study included 193 participants with subjective cognitive complaints (SCC) and 56 participants with MCI who completed a baseline and two follow-up assessments, with an interval of about 18 months between each assessment. Participants were classified into three groups by considering cognitive stability or deterioration from the baseline diagnosis: SCC-stable, MCI-stable and MCI-worsened. Participants performed a ToT task involving recognition and naming of famous people depicted in 50 photographs. Generalized Linear Mixed Models (GLMM) were used to model longitudinal changes in familiarity, feeling of knowing, semantic access, phonological access and verbal fluency. RESULTS: Phonological access differentiated MCI patients, stable and worsened, from adults with SCCs at all evaluation times. Phonological access declined over time in the three groups, without significant interactions between groups and time. DISCUSSION: This study provides the first longitudinal evidence of differences in ToT measures for adults with MCI. The findings indicate that phonological access measures successfully differentiated between the diagnostic groups. However, slopes remain irrespective of the diagnostic group and progression toward more advance stages of cognitive impairment.

Does Empirically Derived Classification of Individuals with Subjective Cognitive Complaints Predict Dementia?

(1) Background: Early identification of mild cognitive impairment (MCI) in people reporting subjective cognitive complaints (SCC) and the study of progression of cognitive decline are important issues in dementia research. This paper examines whether empirically derived procedures predict progression from MCI to dementia. (2) Methods: At baseline, 192 participants with SCC were diagnosed according to clinical criteria as cognitively unimpaired (70), single-domain amnestic MCI (65), multiple-domain amnestic MCI (33) and multiple-domain non-amnestic MCI (24). A two-stage hierarchical cluster analysis was performed for empirical classification. Categorical regression analysis was then used to assess the predictive value of the clusters obtained. Participants were re-assessed after 36 months. (3) Results: Participants were grouped into four empirically derived clusters: Cluster 1, similar to multiple-domain amnestic MCI; Cluster 2, characterized by subjective cognitive decline (SCD) but with low scores in language and working memory; Cluster 3, with specific deterioration in episodic memory, similar to single-domain amnestic MCI; and Cluster 4, with SCD but with scores above the mean in all domains. The majority of participants who progressed to dementia were included in Cluster 1. (4) Conclusions: Cluster analysis differentiated between MCI and SCD in a sample of people with SCC and empirical criteria were more closely associated with progression to dementia than standard criteria.

Assessing Mild Behavioral Impairment with the Mild Behavioral Impairment-Checklist in People with Mild Cognitive Impairment.

BACKGROUND: Neuropsychiatric symptoms (NPS) are non-cognitive, behavioral, or psychiatric symptoms, common in mild cognitive impairment (MCI) and associated with a higher risk of dementia. Mild behavioral impairment (MBI) is a validated diagnostic entity, that describes the emergence of later life NPS in pre-dementia states. The Mild Behavioral Impairment Checklist (MBI-C) is the first measure developed to assess MBI. OBJECTIVE: To estimate the prevalence of MBI in people with MCI and to study the score distribution, sensitivity, specificity, diagnostic utility of the MBI-C, and its correlations with neuropsychological tests. METHODS: One hundred eleven MCI participants were evaluated with the Questionnaire for Subjective Memory Complaints (QSMC), Mini-Mental State Examination, Cambridge Cognitive Assessment-Revised, Neuropsychiatric Inventory-Questionnaire (NPI-Q), Geriatric Depression Scale-15 items (GDS-15), Lawton and Brody Index, and the MBI-C, which was administered by phone to participants' informants. Descriptive, logistic regression, ROC curve, and bivariate correlations analyses were performed. RESULTS: MBI diagnosis prevalence was 14.2%. The total MBI-C score differentiated people with MBI at a cutoff-point of 6.5, optimizing sensitivity and specificity. MBI-C total score correlated positively with NPI-Q, QSMC, GDS-15, and Lawton and Brody Index. CONCLUSION: The total MBI-C score, obtained by phone administration, is sensitive for detecting MBI in people with MCI. The MBI-C scores indicated that MCI participants had subtle NPS that were correlated to their subjective memory complaints reported by informants, depressive symptoms, and negatively with Instrumental Activities of Daily Living. Further research should be done to clarify the predictive role of NPS in MCI for incident dementia.