Executive functioning in cognitively normal middle-aged offspring of late-onset Alzheimer's disease patients

Episodic memory deficits are traditionally seen as the hallmark cognitive impairment during the prodromal continuum of late-onset Alzheimer's disease (LOAD). Previous studies identified early brain alterations in regions subserving executive functions in asymptomatic, middle-aged offspring of patients with LOAD (O-LOAD), suggesting that premature episodic memory deficits could be associated to executive dysfunction in this model. We hypothesized that O-LOAD would exhibit reduced executive performance evidenced by increased errors and decreased strategy use on an episodic memory task. We assessed 32 asymptomatic middle-aged O-LOAD and 28 age-equivalent control subjects (CS) with several tests that measure executive functions and the Rey Auditory Verbal Learning Test (RAVLT) to measure memory performance. All tests were scored using both traditional and process scores (quantification of errors and strategies underlying overall performance). T-tests were used to compare performance between both groups and Spearman correlations were implemented to measure associations between variables. O-LOAD participants exhibited decreased executive performance compared to CS as it relates to initiation time (Tower of London), mental switching (Trail Making Test B), and interference effects (Stroop Word-Color condition). Traditional RAVLT measures showed a poorer performance by O-LOAD and RAVLT process scores revealed increased interference effects on this group. Positive correlations (r s ) were found between the executive measures and several RAVLT measures for O-LOAD but not for CS. In conclusion, O-LOAD participants exhibited early subtle cognitive changes in executive processing. Observed memory difficulties may be associated in part to executive deficits suggesting an interplay between memory and executive functions. Process score impairments were observed earlier than clinical decline on neuropsychological scores in this at-risk cohort and might be useful cognitive markers of preclinical LOAD.Fil: Abulafia, Carolina Andrea. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Fundación para la Lucha contra las Enfermedades Neurológicas de la Infancia; ArgentinaFil: Fiorentini, Leticia. Fundación para la Lucha contra las Enfermedades Neurológicas de la Infancia; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Loewenstein, David A.. University of Miami; Estados UnidosFil: Curiel Cid, Rosie. University of Miami; Estados UnidosFil: Sevlever, Gustavo. Fundación para la Lucha contra las Enfermedades Neurológicas de la Infancia; ArgentinaFil: Nemeroff, Charles B.. University of Texas at Austin; Estados UnidosFil: Villarreal, Mirta Fabiana. Fundación para la Lucha contra las Enfermedades Neurológicas de la Infancia; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad de Buenos Aires; ArgentinaFil: Vigo, Daniel Eduardo. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Investigaciones Biomédicas. Universidad de Buenos Aires. Facultad de Medicina. Instituto de Investigaciones Biomédicas; ArgentinaFil: Guinjoan, Salvador Martín. Fundación para la Lucha contra las Enfermedades Neurológicas de la Infancia; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad de Buenos Aires; Argentin

Salient Cognitive Paradigms to Assess Preclinical Alzheimer's Disease

Despite the growing emphasis to identify early biological markers that can detect the progressive accumulation of brain pathology in the complex pathophysiologic cascade that occurs in Alzheimer's disease (AD), we continue to employ the same neuropsychological paradigms that were developed to detect dementia or frank cognitive impairment. It has become increasingly clear that we cannot expect to measure clinically meaningful change in relationship to these emerging preclinical biomarkers using these traditional cognitive assessment paradigms, nor will we advance the efforts to identify the earliest cognitive changes that emerge in AD. Over the last decade, a few novel promising cognitive assessment paradigms have emerged that have shown promise in identifying subtle cognitive deficits in AD which aids in early detection and monitoring of meaningful cognitive change over time. Some of these cognitive assessment paradigms are reviewed here, including semantic interference, semantic intrusion errors, memory binding, and binding of face and name associations. These paradigms may be useful for AD clinical trials focused on secondary prevention if there is sufficient rigor to suggest that they correlate with AD biomarkers, having robust sensitivity, specificity, and predictive utility among culturally and linguistically diverse populations at-risk for AD

A-144 A Cross-Validation Study of Memory and Non-Memory Neuropsychology Measures with Spanish-Speaking Older Adults

Abstract Objective: To evaluate the clinical utility of the Spanish versions of memory vs. non-memory instruments in a Spanish-speaking sample; specifically, the comparative performance for the English versions in amnestic MCI (aMCI) and cognitively unimpaired (CU) elders. Method: 255 Non-Hispanic English speakers (NH-ES; 157 CU; 98 aMCI) and 201 Hispanic Spanish speakers (H-SS; 103 CU; 98 aMCI) were classified using the Clinical Dementia Rating Scale and a validated culturally fair test. ANCOVA procedures were used to test for differences between four groups across languages adjusting for age, sex, and education for memory (e.g., Hopkins Verbal Learning Test-HVLT-R; NACC Logical Memory) and non-memory measures (e.g., Trail-Making Test A-B, Category and Phonemic Fluency). Results: For memory measures, CU older adults were statistically differentiated from aMCI counterparts regardless of language. No significant differences between H-SS aMCI and NH-ES aMCI groups’ on HVLT-R and NACC story passages immediate/delayed conditions. No significant differences found between H-SS CU and NH-ES CU on memory indices. Conversely, Bonferroni corrected means (p<.05) revealed that even after adjustment for demographic covariates, ES CU outperformed H-SS CU counterparts on Trails A-B, and Category/Phonemic Fluencies. NH-ES aMCI groups scored better than H-SS aMCI on Trails B. Conclusions: Results indicate that memory measures experience less bias when employed among different linguistic/cultural groups regardless of cognitive status. In contrast, CU H-SS groups scored lower on all non-memory measures. Factors that lead to potential bias, particularly among CU are discussed. Trails-B evidenced bias for both Hispanic CU and MCI, making this a measure that requires the judicious use of appropriate norms

Patient values in healthcare decision making among diverse older adults

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. 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). Investigators used a qualitative descriptive approach to analyze transcripts and identify themes. Forty-nine individuals (49% with cognitive impairment; 51% Hispanic) participated. Participants expressed a wide range of values relating to individual factors, familial/cultural beliefs and expectations, balancing risks and benefits, receiving decisional support, and considering values other than their own. Participants emphasized that values are individual-specific, influenced by aging, and change throughout life course. Participants described barriers and facilitators that interfere with or promote value solicitation and incorporation during medical encounters. Study findings highlight that in older adults with various health experiences, cognitive and physical health status, and sociocultural backgrounds, medical decisions are influenced by a variety of values. Clinicians should take time to elicit, understand, and reassess the different types of values of older adults. •Older adults incorporate unique and multifaceted values in health decisions.•Values that influence medical decisions change with aging.•Values include consideration of familial roles and decisional support.•Older adults value quality of life and balance risks versus benefits

Value Assessment in Healthcare Decision-Making of Ethnically and Cognitively Diverse Older Adults

Abstract Objective Little is known regarding the values that patients with mild cognitive impairment (MCI) incorporate into healthcare decision-making or how culture may affect such values. Even if values overlap across cultures, cultural groups may emphasize the importance of specific values differently since values emanate, at least in part, from cultural and life-long learning. The aim of this study was to explore and compare values that older adults of different ethnicities and cognitive statuses incorporate in their medical decisions. Participants and Method Four focus groups were established by identifying older adults as, a) Hispanic or non-Hispanic, and with b) normal cognition or MCI. Participants were recruited from the 1Florida Alzheimer’s Disease Research Center. Focus groups were audio-recorded and transcribed using a professional transcription service. Results There were a total of 23 participants (Age: M = 70.9, SD = 6.4). MCI groups had briefer discussions (Time M = 44 minutes) than the normal cognition groups (Time M = 62 minutes). Qualitative analysis of discussions was used to explore the values identified across the focus groups. The MCI groups valued spirituality, doctor recommendations, and family involvement when facing medical decisions. Normal cognition groups valued the necessity of proactive involvement as healthcare consumers and the relationship between the quality of patient-clinician interaction and their health care related decisions. Cultural themes involving perceptions of gender and generational differences emerged from the Hispanic normal cognition group. Conclusions This study identified many determinants influencing the medical decision-making process of diverse older adults: including past experiences, family involvement, healthcare barriers, and cultural background. These results have the potential to impact patient-clinician discussions, decisions made by surrogates, and the development of decision aids with a broader range of relevant patient values

A Review of Novel Cognitive Challenge Tests for the Assessment of Preclinical Alzheimer's Disease

Objectives: There is currently a lack of consensus among neuropsychologists about which cognitive assessment paradigms hold the most promise in identifying subtle cognitive deficits in preclinical Alzheimer's Disease (AD) and which are most useful for monitoring risk of cognitive deterioration. Many widely used instruments are older versions of tests originally developed for the assessment of dementia or traumatic brain injury. Current efforts to digitize these measures provides more uniform and remote assessment, which is an advancement, but does not reflect significant changes in paradigmatic underpinnings or recent advances in cognitive neuroscience. Method: This work provides an overview of novel Cognitive Challenge Tests (CCTs) that employ semantic interference paradigms that uniquely measure the failure to recover from proactive semantic interference (frPSI). Other salient methods to measure meaningful cognitive change in early stage AD are also presented, as well as how they compare with traditional neuropsychological assessments. Finally, future directions for the development of more effective assessment paradigms are discussed. Results: frPSI is a cognitive marker which measures the persistent inability to learn new semantically competing stimuli despite multiple opportunities to do so. frPSI and deficits in semantic inhibitory control have repeatedly shown utility for the early detection of AD during its preclinical stages. These novel cognitive markers have been related to various biomarkers of AD and neurodegeneration among culturally diverse older adults. Conclusions: To meet the critical needs of a rapidly evolving field, cognitive assessment instruments must show sufficient scientific rigor including robust sensitivity, specificity, and predictive utility among culturally and linguistically diverse populations and importantly, be correlated to AD biomarkers

A Teleneuropsychology Protocol for the Cognitive Assessment of Older Adults During COVID-19

The Coronavirus Disease 2019 (COVID-19) pandemic prompted the need for a teleneuropsychology protocol for the cognitive assessment of older adults, who are at increased risk for both COVID-19 and dementia. Prior recommendations for teleneuropsychological assessment did not consider many of the unique challenges posed by COVID-19. The field is still in need of clear guidelines and standards of care for the assessment of older adults under the current circumstances. Advantages of teleneuropsychological assessment during the COVID-19 pandemic include reduced risk of contracting the virus, eliminating travel time and reducing cost, and more rapid access to needed services. Challenges include disparities in technology access among patients, reduced control over the testing environment, impeded ability to make behavioral observations, and limited research on valid and reliable cognitive assessment measures. The aim of this perspective review is to propose a teleneuropsychological protocol to facilitate neuropsychological assessment utilizing a virtual platform. The proposed protocol has been successful with our clinical and research populations and may help neuropsychologists implement teleneuropsychology services without compromising validity or reliability. However, there is increasing need for research on teleneuropsychological assessment options for both clinical and research purposes

A Deep-Learning Approach for the Prediction of Mini-Mental State Examination Scores in a Multimodal Longitudinal Study

This study introduces a new multimodal deep regression method to predict cognitive test score in a 5-year longitudinal study on Alzheimer's disease (AD). The proposed model takes advantage of multimodal data that includes cerebrospinal fluid (CSF) levels of tau and beta-amyloid, structural measures from magnetic resonance imaging (MRI), functional and metabolic measures from positron emission tomography (PET), and cognitive scores from neuropsychological tests (Cog), all with the aim of achieving highly accurate predictions of future Mini-Mental State Examination (MMSE) test scores up to five years after baseline biomarker collection. A novel data augmentation technique is leveraged to increase the numbers of training samples without relying on synthetic data. With the proposed method, the best and most encompassing regressor is shown to achieve better than state-of-the-art correlations of 85.07%(SD=1.59) for 6 months in the future, 87.39% (SD =1.48) for 12 months, 84.78% (SD=2.66) for 18 months, 85.13% (SD=2.19) for 24 months, 81.15% (SD=5.48) for 30 months, 81.17% (SD=4.44) for 36 months, 79.25% (SD=5.85) for 42 months, 78.98% (SD=5.79) for 48 months, 78.93%(SD=5.76) for 54 months, and 74.96% (SD=7.54) for 60 months

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. Different multimodality scenarios are investigated, and complementary aspects of the multimodal features are exploited to simultaneously delineate the subject’s label and predict related cognitive scores at future timepoints using baseline data. The main intent in this multitask framework is to consolidate the highest accuracy possible in terms of precision, sensitivity, F1 score, and area under the curve (AUC) in the multiclass classification task while maintaining the highest similarity in the MMSE score as measured through the correlation coefficient and the RMSE for all time points under the prediction task, with both tasks, run simultaneously under the same set of hyperparameters. The overall accuracy for multiclass classification of the proposed KTMnet method is 66.85 ± 3.77. The prediction results show an average RMSE of 2.32 ± 0.52 and a correlation of 0.71 ± 5.98 for predicting MMSE throughout the time points. These results are compared to state-of-the-art techniques reported in the literature. A discovery from the multitasking of this consolidated machine learning framework is that a set of hyperparameters that optimize the prediction results may not necessarily be the same as those that would optimize the multiclass classification. In other words, there is a breakpoint beyond which enhancing further the results of one process could lead to the downgrading in accuracy for the other

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

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