Biology subjects

langley, j.

Publications and source records attributed to langley, j..

2 recordsLinked to original sources

bioRxiv2025

Connectome-based predictive modelling predicts frailty levels in older adults

Frailty is characterized by a persistent and progressive decline in physiological reserves, leading to increased vulnerability to stressors and a heightened risk of adverse health outcomes, both physically and mentally. Despite frailtys prevalence in older adults, there is limited research on its neural substrates, especially using task-based brain functional connectivity. In this study, we used connectome-based predictive modelling (CPM) to find a linear relationship between task-based connectomes -- taken from tasks that involved similar handgrip manipulations -- and a separate measure of frailty: the maximum grip strength in older adults. We observed that the task-based connectomes were able to explain individual differences in grip strength, with the Subcortical and Cerebellum network, particularly the caudate nucleus, functional connectivity being the strongest predictor. These findings demonstrate that task-based functional connectomes can serve as personalized markers that can predict individual behavioral measures, including handgrip strength, and point to involvement of the caudate nucleus in frailty. Key pointsO_LIWe used connectome-based predictive modeling on task-based fMRI to predict grip strength in older adults, a key marker of physical frailty. C_LIO_LIThe model significantly explained inter-individual differences in contraction strength using functional connectivity patterns. C_LIO_LISubcortical regions, especially the caudate nucleus, played a major role in prediction, highlighting their relevance in frailty assessment and potential interventions. C_LI

neuroscience↗

bioRxiv2022

Locus coeruleus neuromelanin predicts ease of attaining and maintaining neural states of arousal

The locus coeruleus (LC), a small subcortical structure in the brainstem, is the brains principal source of norepinephrine. It plays a primary role in regulating stress, the sleep-wake cycle, and attention, and its degradation is associated with aging and neurodegenerative diseases associated with cognitive deficits (e.g., Parkinsons, Alzheimers). Yet precisely how norepinephrine drives brain networks to support healthy cognitive function remains poorly understood - partly because LCs small size makes it difficult to study noninvasively in humans. Here, we characterized LCs influence on brain dynamics using a hidden Markov model fitted to functional neuroimaging data from healthy young adults across four attention-related brain networks and LC. We modulated LC activity using a behavioral paradigm and measured individual differences in LC magnetization transfer contrast. The model revealed five hidden states, including a stable state dominated by salience-network activity that occurred when subjects actively engaged with the task. LC magnetization transfer contrast correlated with this states stability across experimental manipulations and with subjects propensity to enter into and remain in this state. These results provide new insight into LCs role in driving spatiotemporal neural patterns associated with attention, and demonstrate that variation in LC integrity can explain individual differences in these patterns even in healthy young adults.

neuroscience↗