Exploring bi-directional temporal associations between timed-up-and-go and cognitive domains in the Irish longitudinal study on ageing (TILDA)

The temporal precision of audiovisual integration is associated with longitudinal fall incidents but not sensorimotor fall risk in older adults

Sustained multisensory integration over long inter-stimulus time delays is typically found in older adults, particularly those with a history of falls. However, the extent to which the temporal precision of audio-visual integration is associated with longitudinal fall or fall risk trajectories is unknown. A large sample of older adults (N = 2319) were grouped into longitudinal trajectories of self-reported fall incidents (i.e., decrease, stable, or increase in number) and, separately, their performance on a standard, objective measure of fall risk, Timed Up and Go (TUG; stable, moderate decline, severe decline). Multisensory integration was measured once as susceptibility to the Sound-Induced Flash Illusion (SIFI) across three stimulus onset asynchronies (SOAs): 70 ms, 150 ms and 230 ms. Older adults with an increasing fall number showed a significantly different pattern of performance on the SIFI than non-fallers, depending on age: For adults with increasing incidents of falls, those aged 53-59 years showed a much smaller difference in illusion susceptibility at 70 ms versus 150 ms than those aged 70 + years. In contrast, non-fallers showed a more comparable difference between these SOA conditions across age groups. There was no association between TUG performance trajectories and SIFI susceptibility. These findings suggests that a fall event is associated with distinct temporal patterns of multisensory integration in ageing and have implications for our understanding of the mechanisms underpinning brain health in older age.

Brain connectivity in frailty: Insights from The Irish Longitudinal Study on Ageing (TILDA)

Frailty in older adults is associated with greater risk of cognitive decline. Brain connectivity insights could help understand the association, but studies are lacking. We applied connectome-based predictive modeling to a 32-item self-reported Frailty Index (FI) using resting state functional MRI data from The Irish Longitudinal Study on Ageing. A total of 347 participants were included (48.9% male, mean age 68.2 years). From connectome-based predictive modeling, we obtained 204 edges that positively correlated with the FI and composed the "frailty network" characterised by connectivity of the visual network (right); and 188 edges that negatively correlated with the FI and formed the "robustness network" characterized by connectivity in the basal ganglia. Both networks' highest degree node was the caudate but with different patterns: from caudate to visual network in the frailty network; and to default mode network in the robustness network. The FI was correlated with walking speed but not with metrics of global cognition, reinforcing the matching between the FI and the brain connectivity pattern found (main predicted connectivity in basal ganglia).

Mediating effect of lower extremity muscle strength on the relationship between mobility and cognitive function in Chinese older adults: A cross-sectional study

Aging is a multifactorial process associated with irreversible decline in mobility and cognitive function. However, the mechanisms underlying the relationship between mobility and cognitive function remain elusive. In specific, the mediating effect of muscle strength, which is essential to maintain mobility, on this relationship has yet to be clarified. Accordingly, we performed a cross-sectional study involving Chinese older adults to understand the role of muscle strength in the relationship between mobility and cognitive function. The cognitive function and physical performance of 657 community-dwelling participants aged over 65 years old were observed. Cognitive function was assessed using the Mini-Mental State Examination, whereas physical performance, including mobility and muscle strength, was measured via Timed Up-and-Go Test and knee extension strength measurement. Data were statistically analyzed using PROCESS Model 4 developed by Hayes, and 595 complete data were finally included. Physical performance (mobility and muscle strength) was significantly correlated with cognitive function (p < 0.01). Muscle strength was negatively correlated with mobility (r = −0.273, p < 0.001) and positively correlated with cognitive function (r = 0.145, p < 0.001). Muscle strength accounted for 20.1% of the total mediating effects on the relationship between mobility and cognitive function, which revealed the partial mediating role of lower extremity muscle strength in this relationship.

Longitudinal Study on Sustained Attention to Response Task (SART): Clustering Approach for Mobility and Cognitive Decline

The Sustained Attention to Response Task (SART) is a computer-based go/no-go task to measure neurocognitive function in older adults. However, simplified average features of this complex dataset lead to loss of primary information and fail to express associations between test performance and clinically meaningful outcomes. Here, we combine a novel method to visualise individual trial (raw) information obtained from the SART test in a large population-based study of ageing in Ireland and an automatic clustering technique. We employed a thresholding method, based on the individual trial number of mistakes, to identify poorer SART performances and a fuzzy clusters algorithm to partition the dataset into 3 subgroups, based on the evolution of SART performance after 4 years. Raw SART data were available for 3468 participants aged 50 years and over at baseline. The previously reported SART visualisation-derived feature ‘bad performance’, indicating the number of SART trials with at least 4 mistakes, and its evolution over time, combined with the fuzzy c-mean (FCM) algorithm, individuated 3 clusters corresponding to 3 degrees of physiological dysregulation. The biggest cluster (94% of the cohort) was constituted by healthy participants, a smaller cluster (5% of the cohort) by participants who showed improvement in cognitive and psychological status, and the smallest cluster (1% of the cohort) by participants whose mobility and cognitive functions dramatically declined after 4 years. We were able to identify in a cohort of relatively high-functioning community-dwelling adults a very small group of participants who showed clinically significant decline. The selected smallest subset manifested not only mobility deterioration, but also cognitive decline, the latter being usually hard to detect in population-based studies. The employed techniques could identify at-risk participants with more specificity than current methods, and help clinicians better identify and manage the small proportion of community-dwelling older adults who are at significant risk of functional decline and loss of independence.