Cross-cultural Diagnostic Validity of the Multilingual Naming Test (MINT) in a Sample of Older Adults.

Objective: We aimed to evaluate the psychometric properties and diagnostic accuracy of the 32-item version of the Multilingual Naming Test (MINT) in participants from 2 ethnic groups (European Americans [EA; n = 106] and Hispanic Americans [HA; n = 175]) with 3 diagnostic groups (cognitively normal [CN], n = 94, mild cognitive impairment [MCI], n = 148, and dementia, n = 39).

Method: An Item Response Theory model was used to evaluate items across ethnicity and language groups (Spanish and English), resulting in a 24-item version. We analyzed the MINT discriminant and predictive validity across diagnostic groups.

Stability in cognitive classification as a function of severity of impairment and ethnicity: A longitudinal analysis.

Objective: The interaction of ethnicity, progression of cognitive impairment, and neuroimaging biomarkers of Alzheimer's Disease remains unclear. We investigated the stability in cognitive status classification (cognitively normal [CN] and mild cognitive impairment [MCI]) of 209 participants (124 Hispanics/Latinos and 85 European Americans).

Methods: Biomarkers (structural MRI and amyloid PET scans) were compared between Hispanic/Latino and European American individuals who presented a change in cognitive diagnosis during the second or third follow-up and those who remained stable over time.

The association of depression and apathy with Alzheimer's disease biomarkers in a cross-cultural sample.

Cross-cultural differences in the association between neuropsychiatric symptoms and Alzheimer's disease (AD) biomarkers are not well understood. This study aimed to (1) compare depressive symptoms and frequency of reported apathy across diagnostic groups of participants with normal cognition (CN), mild cognitive impairment (MCI), and dementia, as well as ethnic groups of Hispanic Americans (HA) and European Americans (EA); (2) evaluate the relationship between depression and apathy with Aβ deposition and brain atrophy. Statistical analyses included ANCOVAs, chi-squared, nonparametric tests, correlations, and logistic regressions.

A Tensorized Multitask Deep Learning Network for Progression Prediction of Alzheimer's Disease.

With the advances in machine learning for the diagnosis of Alzheimer's disease (AD), most studies have focused on either identifying the subject's status through classification algorithms or on predicting their cognitive scores through regression methods, neglecting the potential association between these two tasks. Motivated by the need to enhance the prospects for early diagnosis along with the ability to predict future disease states, this study proposes a deep neural network based on modality fusion, kernelization, and tensorization that perform multiclass classification and longitudinal regression simultaneously within a unified multitask framework. This relationship between multiclass classification and longitudinal regression is found to boost the efficacy of the final model in dealing with both tasks.

The Contribution of Bilingualism to Cognitive Functioning and Regional Brain Volume in Normal and Abnormal Aging.

We examined the association between bilingualism, executive function (EF), and brain volume in older monolinguals and bilinguals who spoke English, Spanish, or both, and were cognitively normal (CN) or diagnosed with Mild Cognitive Impairment (MCI) or dementia. Gray matter volume (GMV) was higher in language and EF brain regions among bilinguals, but no differences were found in memory regions. Neuropsychological performance did not vary across language groups over time; however, bilinguals exhibited reduced Stroop interference and lower scores on Digit Span Backwards and category fluency.

Patient values in healthcare decision making among diverse older adults.

Objective: To provide high-quality healthcare, it is essential to understand values that guide the healthcare decisions of older adults. We investigated the types of values that culturally diverse older adults incorporate in medical decision making.

Methods: Focus groups were held with older adults who varied in cognitive status (mildly impaired versus those with normal cognition) and ethnicity (Hispanic and non-Hispanic).

The Association Between Functional Assessment and Structural Brain Biomarkers in an Ethnically Diverse Sample With Normal Cognition, Mild Cognitive Impairment, or Dementia.

Objective: To investigate the association between the functional activities questionnaire (FAQ) and brain biomarkers (bilateral hippocampal volume [HV], bilateral entorhinal volume [ERV], and entorhinal cortical thickness [ERT]) in cognitively normal (CN) individuals, mild cognitive impairment (MCI), or dementia.

Method: In total, 226 participants (137 females; mean age = 71.76, SD = 7.

Gaussian discriminative component analysis for early detection of Alzheimer's disease: A supervised dimensionality reduction algorithm.

Background: Using multiple modalities of biomarkers, several machine leaning-based approaches have been proposed to characterize patterns of structural, functional and metabolic differences discernible from multimodal neuroimaging data for Alzheimer's disease (AD). Current investigations report several studies using binary classification often augmented with local feature selection methods, while fewer other studies address the challenging problem of multiclass classification.

New Method: To assess the merits of each of these research directions, this study introduces a supervised Gaussian discriminative component analysis (GDCA) algorithm, which can effectively delineate subtle changes of early mild cognitive impairment (EMCI) group in relation to the cognitively normal control (CN) group.

Memory Impairment in Relapsing-Remitting Multiple Sclerosis Using a Challenging Semantic Interference Task.

Episodic memory is frequently impaired in Multiple Sclerosis (MS), but the cognitive characteristics and neuropsychological processes involved remain controversial. Our aim was to study episodic memory dysfunction in MS, using the LASSI-L, a novel memory-based cognitive stress test that uses a new paradigm that capitalizes on semantic interference. Cross-sectional study in which 93 patients with MS (relapsing-remitting) and 124 healthy controls were included.

A Gaussian-based model for early detection of mild cognitive impairment using multimodal neuroimaging.

Background: Diagnosis of early mild cognitive impairment (EMCI) as a prodromal stage of Alzheimer's disease (AD) with its delineation from the cognitively normal (CN) group remains a challenging but essential step for the planning of early treatment. Although several studies have focused on the MCI diagnosis, this study introduces the early stage of MCI to assess more thoroughly the earliest signs of disease manifestation and progression.

New Method: We used random forest feature selection model with a Gaussian-based algorithm to perform method evaluation.

Depression and the Diagnosis of MCI in a Culturally Diverse Sample in the United States.

Objective: To analyze (1) whether there are ethnic differences in the severity of depressive symptoms between groups of elders classified as cognitively normal (CN) or amnestic mild cognitive impairment (aMCI) and (2) the influence of depressive symptoms on specific cognitive performance by ethnicity across diagnoses, controlling for covariates.

Methods: 164 Hispanics residing in the United States (HAs) and European Americans (EAs) (100 women; Mage = 72.1, SD = 8.

A distributed multitask multimodal approach for the prediction of Alzheimer's disease in a longitudinal study.

Predicting the progression of Alzheimer's Disease (AD) has been held back for decades due to the lack of sufficient longitudinal data required for the development of novel machine learning algorithms. This study proposes a novel machine learning algorithm for predicting the progression of Alzheimer's disease using a distributed multimodal, multitask learning method. More specifically, each individual task is defined as a regression model, which predicts cognitive scores at a single time point.

Types of errors on a semantic interference task in mild cognitive impairment and dementia.

Objective: This research aimed to determine whether qualitative analysis of different types of intrusion errors on a verbal cognitive task was useful in detecting subtle cognitive impairment in preclinical stages prior to the progression to dementia.

Method: Different types of semantic intrusions on the Loewenstein-Acevedo Scales of Semantic Interference and Learning (LASSI-L) were compared across 160 individuals diagnosed as cognitively normal (CN), amnestic Mild Cognitive Impairment (aMCI), and dementia. The sample included Hispanics and non-Hispanic European Americans.

Effects of Bilingualism on Verbal and Nonverbal Memory Measures in Mild Cognitive Impairment.

Objectives: Maintaining two active languages may increase cognitive and brain reserve among bilingual individuals. We explored whether such a neuroprotective effect was manifested in the performance of memory tests for participants with amnestic mild cognitive impairment (aMCI).

Methods: We compared 42 bilinguals to 25 monolinguals on verbal and nonverbal memory tests.

Utilizing semantic intrusions to identify amyloid positivity in mild cognitive impairment.

Objective: Semantic intrusion (SI) errors may highlight specific breakdowns in memory associated with preclinical Alzheimer disease (AD); however, there have been no investigations to determine whether SI errors occur with greater frequency in persons with amnestic mild cognitive impairment (aMCI) confirmed as amyloid positive (Amy+) vs those who have clinical symptoms of aMCI-AD with negative amyloid scans (suspected non-AD pathology [SNAP]) or persons who are diagnosed with other brain disorders affecting cognition.

Methods: Eighty-eight participants with aMCI underwent brain amyloid PET and MRI scans and were classified as early AD (Amy+), SNAP (Amy-), or other neurological/psychiatric diagnosis (Amy-). We focused on SI on the Loewenstein-Acevedo Scales for Semantic Interference and Learning (LASSI-L) targeting proactive semantic interference (PSI; old semantic learning interferes with new semantic learning), failure to recover from PSI after an additional learning trial (frPSI), and retroactive semantic interference (new semantic learning interferes with memory for old semantic learning).

Semantic Intrusions and Failure to Recover From Semantic Interference in Mild Cognitive Impairment: Relationship to Amyloid and Cortical Thickness.

Background: Accumulating evidence indicates that the failure to recover from the effects of proactive semantic interference [frPSI] represents an early cognitive manifestation of preclinical Alzheimer's disease. A limitation of this novel paradigm has been a singular focus on the number of targets correctly recalled, without examining co-occurring semantic intrusions [SI] that may highlight specific breakdowns in memory.

Objectives: We focused on SI and their relationship to amyloid load and regional cortical thickness among persons with amnestic mild cognitive impairment (aMCI).

Novel Cognitive Paradigms for the Detection of Memory Impairment in Preclinical Alzheimer's Disease.

In spite of advances in neuroimaging and other brain biomarkers to assess preclinical Alzheimer's disease (AD), cognitive assessment has relied on traditional memory paradigms developed well over six decades ago. This has led to a growing concern about their effectiveness in the early diagnosis of AD which is essential to develop preventive and early targeted interventions before the occurrence of multisystem brain degeneration. We describe the development of novel tests that are more cognitively challenging, minimize variability in learning strategies, enhance initial acquisition and retrieval using cues, and exploit vulnerabilities in persons with incipient AD such as the susceptibility to proactive semantic interference, and failure to recover from proactive semantic interference.

Comparison between FCSRT and LASSI-L to Detect Early Stage Alzheimer's Disease.

Background: The Free and Cued Selective Reminding Test (FCSRT) is the most accurate test for the diagnosis of prodromal Alzheimer's disease (AD). Recently, a novel cognitive test, the Loewenstein-Acevedo Scale for Semantic Interference and Learning (LASSI-L), has been developed in order to provide an early diagnosis.

Objective: To compare the diagnostic accuracy of the FCSRT and the LASSI-L for the diagnosis of AD in its preclinical and prodromal stages using 18F-fluorodeoxyglucose positron emission tomography (FDG-PET) as a reference.

A novel cognitive assessment paradigm to detect Pre-mild cognitive impairment (PreMCI) and the relationship to biological markers of Alzheimer's disease.

Objective: A number of older adults obtain normal scores on formal cognitive tests, but present clinical concerns that raise suspicion of cognitive decline. Despite not meeting full criteria for Mild Cognitive Impairment (MCI), these PreMCI states confer risk for progression to Alzheimer's disease (AD). This investigation addressed a pressing need to identify cognitive measures that are sensitive to PreMCI and are associated with brain biomarkers of neurodegeneration.

Recovery from Proactive Semantic Interference and MRI Volume: A Replication and Extension Study.

Background: The rise in incidence of Alzheimer's disease (AD) has led to efforts to advance early detection of the disease during its preclinical stages. To achieve this, the field needs to develop more sensitive cognitive tests that relate to biological markers of disease pathology. Failure to recover from proactive interference (frPSI) is one such cognitive marker that is associated with volumetric reductions in the hippocampus, precuneus, and other AD-prone regions, and to amyloid load in the brain.

A Novel Method for Direct Assessment of Everyday Competence Among Older Adults.

Background: Recent findings indicate that impairments in functional performance do occur among individuals diagnosed with mild cognitive impairment (MCI). Most assessment strategies for everyday competence are associated with challenges with reliability, are typically in paper and pencil format, or require in-person administration by a trained professional.

Objective: This paper reports on a novel technology-based assessment battery of everyday competence that includes ecologically valid simulations of daily activities important to independence.

Recovery from Proactive Semantic Interference in Mild Cognitive Impairment and Normal Aging: Relationship to Atrophy in Brain Regions Vulnerable to Alzheimer's Disease.

Background: There is growing evidence that proactive semantic interference (PSI) and failure to recover from PSI may represent early features of Alzheimer's disease (AD).

Objective: This study investigated the association between PSI, recovery from PSI, and reduced MRI volumes in AD signature regions among cognitively impaired and unimpaired older adults.

Methods: Performance on the LASSI-L (a novel test of PSI and recovery from PSI) and regional brain volumetric measures were compared between 38 cognitively normal (CN) elders and 29 older participants with amnestic mild cognitive impairment (MCI).

Validation of the Spanish Version of the LASSI-L for Diagnosing Mild Cognitive Impairment and Alzheimer's Disease.

Background: The Loewenstein-Acevedo Scale for Semantic Interference and Learning (LASSI-L) is a novel cognitive test that measures recovery from proactive semantic interference, which may be an early cognitive marker of Alzheimer's disease (AD).

Objective: To generate normative data for a Spaniard population and to validate the LASSI-L for the diagnosis of amnestic mild cognitive impairment (aMCI) and mild AD.

Methods: We performed a cross-sectional study in which 97 healthy participants, 34 with aMCI, and 33 with mild AD were studied with LASSI-L and a comprehensive neuropsychological protocol.

A Brief Computerized Paired Associate Test for the Detection of Mild Cognitive Impairment in Community-Dwelling Older Adults.

Background: Semantic memory interference has been found to be a predictive cognitive marker of incipient AD. This is relevant given that developing assessment paradigms to identify subtle cognitive and functional deficits is a priority in preclinical Alzheimer's disease research.

Objective: To examine the utility of a novel computerized paired associate test in distinguishing between mild cognitive impairment (MCI) and cognitively normal (CN) groups of older adults residing in the community.

A Novel Cognitive Stress Test for the Detection of Preclinical Alzheimer Disease: Discriminative Properties and Relation to Amyloid Load.

Objective: To examine the utility of a novel "cognitive stress test" to detect subtle cognitive impairments and amyloid load within the brains of neuropsychologically normal community-dwelling elders.

Methods: Participants diagnosed as cognitively normal (CN), subjective memory impairment (SMI), mild cognitive impairment (MCI), and preclinical mild cognitive impairment (PreMCI) were administered the Loewenstein-Acevedo Scale for Semantic Interference and Learning (LASSI-L), a sensitive test of proactive semantic interference (PSI), retroactive semantic interference, and, uniquely, the ability to recover from the effects of PSI. Ninety-three subjects (31 men and 62 women) were recruited from three academic institutions in a research consortium.