Age-related changes of deep-brain neurophysiological activity.

Cognitive decline with age is associated with brain atrophy and reduced brain activations, but the underlying neurophysiological mechanisms are unclear, especially in deeper brain structures primarily affected by healthy aging or neurodegenerative processes. Here, we characterize time-resolved, resting-state magnetoencephalography activity of the hippocampus and subcortical brain regions in a large cohort of healthy young (20-30 years) and older (70-80 years) volunteers from the Cam-CAN (Cambridge Centre for Ageing and Neuroscience) open repository. The data show age-related changes in both rhythmic and arrhythmic signal strength in multiple deeper brain regions, including the hippocampus, striatum, and thalamus. We observe a slowing of neural activity across deeper brain regions, with increased delta and reduced gamma activity, which echoes previous reports of cortical slowing. We also report reduced occipito-parietal alpha peak associated with increased theta-band activity in the hippocampus, an effect that may reflect compensatory processes as theta activity, and slope of arrhythmic activity were more strongly expressed when short-term memory performances were preserved. Overall, this study advances the understanding of the biological nature of inter-individual variability in aging. The data provide new insight into how hippocampus and subcortical neurophysiological activity evolve with biological age, and highlight frequency-specific effects associated with cognitive decline versus cognitive maintenance.

Connectivity dynamics and cognitive variability during aging.

Aging is associated with cognitive changes, with strong variations across individuals. One way to characterize this individual variability is to use techniques such as magnetoencephalography (MEG) to measure the dynamics of neural synchronization between brain regions, and the variability of this connectivity over time. Indeed, few studies have focused on fluctuations in the dynamics of brain networks over time and their evolution with age. We therefore characterize aging effects on MEG phase synchrony in healthy young and older adults from the Cam-CAN database. Age-related changes were observed, with an increase in the variability of brain synchronization, as well as a reversal of the direction of information transfer in the default mode network (DMN), in the delta frequency band. These changes in functional connectivity were associated with cognitive decline. Results suggest that advancing age is accompanied by a functional disorganization of dynamic networks, with a loss of communication stability and a decrease in the information transmitted.

When the time is right: Temporal dynamics of brain activity in healthy aging and dementia.

Brain activity and communications are complex phenomena that dynamically unfold over time. However, in contrast with the large number of studies reporting neuroanatomical differences in activation relative to young adults, changes of temporal dynamics of neural activity during normal and pathological aging have been grossly understudied and are still poorly known. Here, we synthesize the current state of knowledge from MEG and EEG studies that aimed at specifying the effects of healthy and pathological aging on local and network dynamics, and discuss the clinical and theoretical implications of these findings. We argue that considering the temporal dynamics of brain activations and networks could provide a better understanding of changes associated with healthy aging, and the progression of neurodegenerative disease. Recent research has also begun to shed light on the association of these dynamics with other imaging modalities and with individual differences in cognitive performance. These insights hold great potential for driving new theoretical frameworks and development of biomarkers to aid in identifying and treating age-related cognitive changes.

Age-related differences in network structure and dynamic synchrony of cognitive control.

Cognitive trajectories vary greatly across older individuals, and the neural mechanisms underlying these differences remain poorly understood. Here, we investigate the cognitive variability in older adults by linking the influence of white matter microstructure on the task-related organization of fast and effective communications between brain regions. Using diffusion tensor imaging and electroencephalography, we show that individual differences in white matter network organization are associated with network clustering and efficiency in the alpha and high-gamma bands, and that functional network dynamics partly explain individual differences in cognitive control performance in older adults. We show that older individuals with high versus low structural network clustering differ in task-related network dynamics and cognitive performance. These findings were corroborated by investigating magnetoencephalography networks in an independent dataset. This multimodal (fMRI and biological markers) brain connectivity framework of individual differences provides a holistic account of how differences in white matter microstructure underlie age-related variability in dynamic network organization and cognitive performance.

Disrupted Neural Synchrony Mediates the Relationship between White Matter Integrity and Cognitive Performance in Older Adults.

Our main goal was to determine the influence of white matter integrity on the dynamic coupling between brain regions and the individual variability of cognitive performance in older adults. Electroencephalography was recorded while participants performed a task specifically designed to engage working memory and inhibitory processes, and the associations among functional activity, structural integrity, and cognitive performance were assessed. We found that the association between white matter microstructural integrity and cognitive functioning with aging is mediated by time-varying alpha and gamma phase-locking value. Specifically, better preservation of the inferior fronto-occipital fasciculus in older individuals drives faster task-related modulations of alpha and gamma long-range phase-locking value between the inferior frontal gyrus and occipital lobe and lower local phase-amplitude coupling in occipital lobes, which in turn drives better cognitive control performance. Our results help delineate the role of individual variability of white matter microstructure in dynamic synchrony and cognitive performance during normal aging.

Value-driven attentional capture is modulated by the contents of working memory: An EEG study.

Attention and working memory (WM) have previously been shown to interact closely when sensory information is being maintained. However, when non-sensory information is maintained in WM, the relationship between WM and sensory attention may be less strong. In the current study, we used electroencephalography to evaluate whether value-driven attentional capture (i.e., allocation of attention to a task-irrelevant feature previously associated with a reward) and its effects on either sensory or non-sensory WM performance might be greater than the effects of salient, non-reward-associated stimuli. In a training phase, 19 participants learned to associate a color with reward. Then, participants were presented with squares and encoded their locations into WM. Participants were instructed to convert the spatial locations either to another type of sensory representation or to an abstract, relational type of representation. During the WM delay period, task-irrelevant distractors, either previously-rewarded or non-rewarded, were presented, with a novel color distractor in the other hemifield. The results revealed lower alpha power and larger N2pc amplitude over posterior electrode sides contralateral to the previously rewarded color, compared to ipsilateral. These effects were mainly found during relational WM, compared to sensory WM, and only for the previously rewarded distractor color, compared to a previous non-rewarded target color or novel color. These effects were associated with modulations of WM performance. These results appear to reflect less capture of attention during maintenance of specific location information, and suggest that value-driven attentional capture can be mitigated as a function of the type of information maintained in WM.

Age-related changes in strategic variations during arithmetic problem solving: The role of executive control.

In this review, we provide an overview of how age-related changes in executive control influence aging effects in arithmetic processing. More specifically, we consider the role of executive control in strategic variations with age during arithmetic problem solving. Previous studies found that age-related differences in arithmetic performance are associated with strategic variations. That is, when they accomplish arithmetic problem-solving tasks, older adults use fewer strategies than young adults, use strategies in different proportions, and select and execute strategies less efficiently. Here, we review recent evidence, suggesting that age-related changes in inhibition, cognitive flexibility, and working memory processes underlie age-related changes in strategic variations during arithmetic problem solving. We discuss both behavioral and neural mechanisms underlying age-related changes in these executive control processes.