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Following traumatic brain injury (TBI), cognitive impairments manifest through interactions between microscopic and macroscopic changes. On the microscale, a neurometabolic cascade alters neurotransmission, while on the macroscale diffuse axonal injury impacts the integrity of long-range connections. Large-scale brain network modeling allows us to make predictions across these spatial scales by integrating neuroimaging data with biophysically based models to investigate how microscale changes invisible to conventional neuroimaging influence large-scale brain dynamics. To this end, we analyzed structural and functional neuroimaging data from a well characterized sample of 44 adult TBI patients recruited from a regional trauma center, scanned at 1-2 weeks postinjury, and with follow-up behavioral outcome assessed 6 months later. Thirty-six age-matched healthy adults served as comparison participants. Using The Virtual Brain, we fit simulations of whole-brain resting-state functional MRI to the empirical static and dynamic functional connectivity of each participant. Multivariate partial least squares (PLS) analysis showed that patients with acute traumatic intracranial lesions had lower cortical regional inhibitory connection strengths than comparison participants, while patients without acute lesions did not differ from the comparison group. Further multivariate PLS analyses found correlations between lower semiacute regional inhibitory connection strengths and more symptoms and lower cognitive performance at a 6 month follow-up. Critically, patients without acute lesions drove this relationship, suggesting clinical relevance of regional inhibitory connection strengths even when traumatic intracranial lesions were not present. Our results suggest that large-scale connectome-based models may be sensitive to pathophysiological changes in semi-acute phase TBI patients and predictive of their chronic outcomes.

Mild cognitive impairment (MCI) is a prevalent and complex condition among older adults that often progresses into Alzheimer's disease (AD). Although MCI affects individuals differently, there are specific indicators of risk commonly associated with the development of MCI. The present study explored the prevalence of seven established MCI risk categories within a large sample of older adults with and without MCI. We explored trends across the different diagnostic groups and extracted the most salient risk factors related to MCI using partial least squares. Neuropsychological risk categories showed the largest differences across groups, with the cognitively unimpaired groups outperforming the MCI groups on all measures. Apolipoprotein E4 (ApoE4) carriers were significantly more common among the more severe MCI group, whereas ApoE4 non‐carriers were more common in the healthy controls. Participants with subjective and objective cognitive impairment were trending towards AD‐like cerebral spinal fluid (CSF) biomarker levels. Increased age, being male and having fewer years of education were identified as important risk factors of MCI. Higher CSF tau levels were correlated with ApoE4 carrier status, age and a decrease in the ability to carry out daily activities across all diagnostic groups. Amyloid beta1–42 CSF concentration was positively correlated with cognitive and memory performance and non‐ApoE4 carrier status regardless of diagnostic status. Unlike previous research, poor cardiovascular health or being female had no relation to MCI. Altogether, the results highlighted risk factors that were specific to persons with MCI, findings that will inform future research in healthy aging, MCI and AD. [ABSTRACT FROM AUTHOR]

The use of multi-modal approaches, particularly in conjunction with multivariate analytic techniques, can enrich models of cognition, brain function, and how they change with age. Recently, multivariate approaches have been applied to the study of eye movements in a manner akin to that of neural activity (i.e., pattern similarity). Here, we review the literature regarding multi-modal and/or multivariate approaches, with specific reference to the use of eyetracking to characterize age-related changes in memory. By applying multi-modal and multivariate approaches to the study of aging, research has shown that aging is characterized by moment-to-moment alterations in the amount and pattern of visual exploration, and by extension, alterations in the activity and function of the hippocampus and broader medial temporal lobe (MTL). These methodological advances suggest that age-related declines in the integrity of the memory system has consequences for oculomotor behavior in the moment, in a reciprocal fashion. Age-related changes in hippocampal and MTL structure and function may lead to an increase in, and change in the patterns of, visual exploration in an effort to upregulate the encoding of information. However, such visual exploration patterns may be non-optimal and actually reduce the amount and/or type of incoming information that is bound into a lasting memory representation. This research indicates that age-related cognitive impairments are considerably broader in scope than previously realized. [ABSTRACT FROM AUTHOR]

The global population is aging rapidly, and a research question of critical importance is why some older adults suffer tremendous cognitive decline while others are mostly spared. Past aging research has shown that older adults with spared cognitive ability have better local short-range information processing while global long-range processing is less efficient. We took this research a step further to investigate whether the underlying structural connections, measured in vivo using diffusion magnetic resonance imaging (dMRI), show a similar shift to support cognitive ability. We analyzed the structural connectivity streamline probability (representing the probability of connection between regions) and nodal efficiency and local efficiency regional graph theory metrics to determine whether age and cognitive ability are related to structural network differences. We found that the relationship between structural connectivity and cognitive ability with age was nuanced, with some differences with age that were associated with poorer cognitive outcomes, but other reorganizations that were associated with spared cognitive ability. These positive changes included strengthened local intrahemispheric connectivity and increased nodal efficiency of the ventral occipital-temporal stream, nucleus accumbens, and hippocampus for older adults, and widespread local efficiency primarily for middle-aged individuals., Competing Interests: Competing Interests: The authors have declared that no competing interests exist., (© 2024 Massachusetts Institute of Technology.)

The use of multi-modal approaches, particularly in conjunction with multivariate analytic techniques, can enrich models of cognition, brain function, and how they change with age. Recently, multivariate approaches have been applied to the study of eye movements in a manner akin to that of neural activity (i.e., pattern similarity ). Here, we review the literature regarding multi-modal and/or multivariate approaches, with specific reference to the use of eyetracking to characterize age-related changes in memory. By applying multi-modal and multivariate approaches to the study of aging, research has shown that aging is characterized by moment-to-moment alterations in the amount and pattern of visual exploration, and by extension, alterations in the activity and function of the hippocampus and broader medial temporal lobe (MTL). These methodological advances suggest that age-related declines in the integrity of the memory system has consequences for oculomotor behavior in the moment, in a reciprocal fashion. Age-related changes in hippocampal and MTL structure and function may lead to an increase in, and change in the patterns of, visual exploration in an effort to upregulate the encoding of information. However, such visual exploration patterns may be non-optimal and actually reduce the amount and/or type of incoming information that is bound into a lasting memory representation. This research indicates that age-related cognitive impairments are considerably broader in scope than previously realized.