Consequence Of Cognitive Decline Research Articles

Living Beyond 80: A Longitudinal Study of Cognitive and IADL Disablement Among the Oldest Mexican Americans

Mexican Americans live longer on average than other ethnic groups, but often with protracted cognitive and physical disability. Little is known, however, about the role of cognitive decline for transitions in IADL disability and tertiary outcomes of the IADL disablement for the oldest old. We employ the Hispanic Established Populations for the Epidemiologic Study of the Elderly (2010-2011, 2012-2013, 2016, N=1,078) to investigate the longitudinal patterns of IADL decline using Latent Transition Analysis. Three IADL groups were identified: independent (developing mobility limitations), emerging dependence (limited mobility and community activities), and dependent (limited mobility and household and community activities). Declines in cognitive function were a consistent predictor of greater IADL disablement, and loneliness was a particularly salient distal outcome for emerging dependence. These results highlight the social consequences of cognitive decline and dependency as well as underscore important areas of intervention at each stage of the disablement process.

Assessing the cognitive status of Drosophila by the value-based feeding decision

Decision-making is considered an important aspect of cognitive function. Impaired decision-making is a consequence of cognitive decline caused by various physiological conditions, such as aging and neurodegenerative diseases. Here we exploited the value-based feeding decision (VBFD) assay, which is a simple sensory–motor task, to determine the cognitive status of Drosophila. Our results indicated the deterioration of VBFD is notably correlated with aging and neurodegenerative disorders. Restriction of the mushroom body (MB) neuronal activity partly blunted the proper VBFD. Furthermore, using the Drosophila polyQ disease model, we demonstrated the impaired VBFD is ameliorated by the dinitrosyl iron complex (DNIC-1), a novel and steady nitric oxide (NO)-releasing compound. Therefore we propose that the VBFD assay provides a robust assessment of Drosophila cognition and can be used to characterize additional neuroprotective interventions.

Differential effects of aging and cognitive decline on visual exploration behavior in the elderly

Visual exploration disturbance has been examined in the elderly, mainly from the perspective of associations with cognitive function. However, it remains unknown whether this is a consequence of cognitive decline, age-related changes independent of cognitive decline, or both. In this study, 15 healthy elderly individuals were evaluated using two figure-matching tasks representing visual information processing (clock-matching and inverted clock-matching tasks). Cognitive functions were evaluated for each subject using the Mini-Mental State Examination (MMSE). Infrared eye-movement assessments were used to analyze eye movements during task performance. Behavioral analyses showed that age was associated with longer reaction time, while MMSE score was associated with higher accuracy on the inverted clock-matching task. Analyses of eye-movement parameters showed that MMSE score was negatively associated with a parameter indicating difficulty in the efficiency of visual exploration planning, while age was tended to be positively associated with the sum of saccade times in each trial, both predominantly on the inverted clock-matching task. Our approaches highlighted that age and cognitive decline are separately associated with eye-movement characteristics: cognitive decline is associated with difficulty in visual exploration planning, particularly in situations that require substantial visual working memory resources, whereas aging may be associated with oculomotor dysfunction.

Understanding Transitions in IADL and Their Consequences for Cognitive Impairment Among Older Mexican Americans

Mexican Americans tend to live longer lives than other ethnic groups, but it remains unclear how this trend influences the trajectory of disability and its consequences for cognitive frailty. Building on previous research, we assess transitions in IADL among the oldest old. We use data from three waves of the Hispanic Established Population of the Epidemiologic Study of the Elderly (H-EPESE) to investigate trajectories of IADL disability as individuals’ age into their 80s and 90s, a period of the life course with much higher rates of morbidity and decreasing socioeconomic resources. The H-EPESE is a benchmark longitudinal cohort study based on an original sample of 3,050 Mexican-Americans aged 65 and older in the Southwestern United States. Our modeling approach estimates transitions in patterns of IADL employing the Latent Transition Analysis (LTA). Results revealed three heterogeneous latent classes: high IADLs, difficulty in transportation and mobility, and low IADLs. Those with high IADLs tended to remain in the same class over time. Individuals having difficulty in transportation and mobility tended to stay in the same class or transfer to high IADLs, whereas those with overall low IADLs transferred to either the same class or to difficulty in transportation and mobility. Additional analysis revealed that cognitive impairment was a significant predictor of instrumental disability over time. Furthermore, females were more likely than males to belong to difficulty in transportation or mobility class than to the low IADL class. Our results highlight the long term consequences of cognitive decline on IADL limitations.

Detection of abnormal behaviour for dementia sufferers using Convolutional Neural Networks.

In recent years, there is a rapid increase in the population of elderly people. However, elderly people may suffer from the consequences of cognitive decline, which is a mental health disorder that primarily affects cognitive abilities such as learning, memory, etc. As a result, the elderly people may get dependent on caregivers to complete daily life tasks. Detecting the early indicators of dementia before it gets worsen and warning the caregivers and medical doctors would be helpful for further diagnosis. In this paper, the problem of activity recognition and abnormal behaviour detection is investigated for elderly people with dementia. First of all, the paper presents a methodology for generating synthetic data reflecting on some behavioural difficulties of people with dementia given the difficulty of obtaining real-world data. Secondly, the paper explores Convolutional Neural Networks (CNNs) to model patterns in activity sequences and detect abnormal behaviour related to dementia. Activity recognition is considered as a sequence labelling problem, while abnormal behaviour is flagged based on the deviation from normal patterns. Moreover, the performance of CNNs is compared against the state-of-art methods such as Naïve Bayes (NB), Hidden Markov Models (HMMs), Hidden Semi-Markov Models (HSMM), Conditional Random Fields (CRFs). The results obtained indicate that CNNs are competitive with those state-of-art methods.

Poor decision making is a consequence of cognitive decline among older persons without Alzheimer's disease or mild cognitive impairment.

ObjectiveDecision making is an important determinant of health and well-being across the lifespan but is critical in aging, when many influential decisions are made just as cognitive function declines. Increasing evidence suggests that older adults, even those without dementia, often make poor decisions and are selectively vulnerable to scams. To date, however, the factors associated with poor decision making in old age are unknown. The objective of this study was to test the hypothesis that poor decision making is a consequence of cognitive decline among older persons without Alzheimer’s disease or mild cognitive impairment.MethodsParticipants were 420 non-demented persons from the Memory and Aging Project, a longitudinal, clinical-pathologic cohort study of aging in the Chicago metropolitan area. All underwent repeated cognitive evaluations and subsequently completed assessments of decision making and susceptibility to scams. Decision making was measured using 12 items from a previously established performance-based measure and a self-report measure of susceptibility to scams.ResultsCognitive function data were collected over an average of 5.5 years prior to the decision making assessment. Regression analyses were used to examine whether the prior rate of cognitive decline predicted the level of decision making and susceptibility to scams; analyses controlled for age, sex, education, and starting level of cognition. Among 420 persons without dementia, more rapid cognitive decline predicted poorer decision making and increased susceptibility to scams (p’s<0.001). Further, the relations between cognitive decline, decision making and scams persisted in analyses restricted to persons without any cognitive impairment (i.e., no dementia or even mild cognitive impairment).ConclusionsPoor decision making is a consequence of cognitive decline among older persons without Alzheimer’s disease or mild cognitive impairment, those widely considered “cognitively healthy.” These findings suggest that even very subtle age-related changes in cognition have detrimental effects on judgment.