Memory and Executive Functioning Predict Shopping Ability in Alzheimer's Disease

2011 ◽  
Author(s):  
Beyon H. Miloyan ◽  
Justina Avila ◽  
Inna Ghajoyan ◽  
Jill Razani
2021 ◽  
Vol 36 (6) ◽  
pp. 1060-1060
Author(s):  
Zachary Peart ◽  
Samantha Spagna ◽  
Bailey McDonald ◽  
Brittny Arias ◽  
D'anna Sydow ◽  
...  

Abstract Objective To investigate the effects of Type 2 Diabetes (T2D) on performance on attention and executive function measures in a sample of MCI patients. Method Individuals with a clinician diagnosis of MCI with T2D and [n = 719,Mage = 75.24,50.3% female] and MCI persons without T2D [n = 719,Mage = 75.21,47.1% female] were selected from the Alzheimer’s Disease Research Centers database by the National Institute on Aging. Those with motor disturbances were excluded from the analysis. Significant differences (p < 0.001) were found for race and education between groups. Results Multiple ANCOVAs controlled for gender, education, age, and race on performance. Significant differences (p < 0.001) were found in performance on the Trail Making Test [A, B], Digit Span forward [longest recall, correct trials], Digit Span backward [longest recall, correct trials], and Verbal Fluency tasks [F word, L words]. No significant differences were found in the animal and vegetable naming fluency tasks. The T2D group showed poorer mean scores on every test analyzed. Conclusion Results indicated modestly lower performance on measures of attention and executive functioning in MCI patients with comorbid T2D. Previous research supports these conclusions, as T2D has been associated with increased risk for dementia, accelerated decline from MCI to dementia, and modestly lower scores on cognitive tests via effects of microvascular function and altered glucose metabolism. Future studies should aim to identify protective factors in T2D cognitive decrements while controlling for exercise, diet, SES, and underlying medical comorbidities. The NACC database is funded by NIA/NIH Grant U01 AG016976. NACC data are contributed by the NIA-funded Alzheimer’s Disease Research Centers.


2019 ◽  
Vol 112 ◽  
pp. 23-29 ◽  
Author(s):  
Carolina Abulafia ◽  
Leticia Fiorentini ◽  
David A. Loewenstein ◽  
Rosie Curiel-Cid ◽  
Gustavo Sevlever ◽  
...  

2020 ◽  
Vol 16 (S9) ◽  
Author(s):  
Lovingly Park ◽  
Lev Gertsik ◽  
Zyanya Mendoza ◽  
Lydia Morris ◽  
Claudia Aguilar ◽  
...  

Author(s):  
J.S. Shaw ◽  
S.M.H. Hosseini

Findings that the brain is capable of plasticity up until old age have led to interest in the use of cognitive training as a potential intervention to delay the onset of dementia. However, individuals participating in training regimens differ greatly with respect to their outcomes, demonstrating the importance of considering individual differences, in particular age and baseline performance in a cognitive domain, when evaluating the effectiveness of cognitive training. In this review, we summarize existing literature on cognitive training in adults across the domains of episodic memory, working memory and the task-switching component of executive functioning to clarify the picture on the impact of age and baseline performance on cognitive training-related improvements. Studies targeting episodic memory induced greater improvements in younger adults with more intact cognitive abilities, explained in part by factors specific to episodic memory training. By contrast, older, lower baseline performance adults improved most in several studies targeting working memory in older individuals as well as in the majority of studies targeting executive functioning, suggesting the preservation of neural plasticity in these domains until very old age. Our findings can have important implications for informing the design of future interventions for enhancing cognitive functions in individuals at the prodromal stage of Alzheimer’s Disease and potentially delaying the clinical onset of Alzheimer’s Disease. Future research should more clearly stratify individuals according to their baseline cognitive abilities and assign specialized, skill-specific cognitive training regimens in order to directly answer the question of how individual differences impact training effectiveness.


Author(s):  
B. McGuinness ◽  
S. L. Barrett ◽  
D. Craig ◽  
J. Lawson ◽  
A. P. Passmore

2020 ◽  
Vol 2 (2) ◽  
Author(s):  
Ellen Dicks ◽  
Lisa Vermunt ◽  
Wiesje M van der Flier ◽  
Frederik Barkhof ◽  
Philip Scheltens ◽  
...  

Abstract Biomarkers are needed to monitor disease progression in Alzheimer’s disease. Grey matter network measures have such potential, as they are related to amyloid aggregation in cognitively unimpaired individuals and to future cognitive decline in predementia Alzheimer’s disease. Here, we investigated how grey matter network measures evolve over time within individuals across the entire Alzheimer’s disease cognitive continuum and whether such changes relate to concurrent decline in cognition. We included 190 cognitively unimpaired, amyloid normal (controls) and 523 individuals with abnormal amyloid across the cognitive continuum (preclinical, prodromal, Alzheimer’s disease dementia) from the Alzheimer’s Disease Neuroimaging Initiative and calculated single-subject grey matter network measures (median of five networks per individual over 2 years). We fitted linear mixed models to investigate how network measures changed over time and whether such changes were associated with concurrent changes in memory, language, attention/executive functioning and on the Mini-Mental State Examination. We further assessed whether associations were modified by baseline disease stage. We found that both cognitive functioning and network measures declined over time, with steeper rates of decline in more advanced disease stages. In all cognitive stages, decline in network measures was associated with concurrent decline on the Mini-Mental State Examination, with stronger effects for individuals closer to Alzheimer’s disease dementia. Decline in network measures was associated with concurrent cognitive decline in different cognitive domains depending on disease stage: In controls, decline in networks was associated with decline in memory and language functioning; preclinical Alzheimer’s disease showed associations of decline in networks with memory and attention/executive functioning; prodromal Alzheimer’s disease showed associations of decline in networks with cognitive decline in all domains; Alzheimer’s disease dementia showed associations of decline in networks with attention/executive functioning. Decline in grey matter network measures over time accelerated for more advanced disease stages and was related to concurrent cognitive decline across the entire Alzheimer’s disease cognitive continuum. These associations were disease stage dependent for the different cognitive domains, which reflected the respective cognitive stage. Our findings therefore suggest that grey matter measures are helpful to track disease progression in Alzheimer’s disease.


2020 ◽  
Vol 17 (7) ◽  
pp. 667-679
Author(s):  
Matteo De Marco ◽  
Riccardo Manca ◽  
Janine Kirby ◽  
Guillaume M. Hautbergue ◽  
Daniel J. Blackburn ◽  
...  

Background: Research indicates that polygenic indices of risk of Alzheimer’s disease are linked to clinical profiles. Objective: Given the “genetic centrality” of the APOE gene, we tested whether this held true for both APOE-ε4 carriers and non-carriers. Methods: A polygenic hazard score (PHS) was extracted from 784 non-demented participants recruited in the Alzheimer’s Disease Neuroimaging Initiative and stratified by APOE ε4 status. Datasets were split into sub-cohorts defined by clinical (unimpaired/MCI) and amyloid status (Aβ+/Aβ-). Linear models were devised in each sub-cohort and for each APOE-ε4 status to test the association between PHS and memory, executive functioning and grey-matter volumetric maps. Results: PHS predicted memory and executive functioning in ε4ε3 MCI patients, memory in ε3ε3 MCI patients, and memory in ε4ε3 Aβ+ participants. PHS also predicted volume in sensorimotor regions in ε3ε3 Aβ+ participants. Conclusion: The link between polygenic hazard and neurocognitive variables varies depending on APOE-ε4 allele status. This suggests that clinical phenotypes might be influenced by complex genetic interactions.


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