Evidence of regional associations between age-related inter-individual differences in resting-state functional connectivity and cortical thinning revealed through a multi-level analysis

Resting-State Changes in Aging and Parkinson's Disease Are Shaped by Underlying Neurotransmission: A Normative Modeling Study

BACKGROUND

Human healthy and pathological aging is linked to a steady decline in brain resting-state activity and connectivity measures. The neurophysiological mechanisms that underlie these changes remain poorly understood.

METHODS

Making use of recent developments in normative modeling and availability of in vivo maps for various neurochemical systems, we tested in the UK Biobank cohort (n = 25,917) whether and how age- and Parkinson's disease-related resting-state changes in commonly applied local and global activity and connectivity measures colocalize with underlying neurotransmitter systems.

RESULTS

We found that the distributions of several major neurotransmitter systems including serotonergic, dopaminergic, noradrenergic, and glutamatergic neurotransmission correlated with age-related changes across functional activity and connectivity measures. Colocalization patterns in Parkinson's disease deviated from normative aging trajectories for these, as well as for cholinergic and GABAergic (gamma-aminobutyric acidergic) neurotransmission. The deviation from normal colocalization of brain function and GABAA correlated with disease duration.

CONCLUSIONS

These findings provide new insights into molecular mechanisms underlying age- and Parkinson's-related brain functional changes by extending the existing evidence elucidating the vulnerability of specific neurochemical attributes to normal aging and Parkinson's disease. The results particularly indicate that alongside dopamine and serotonin, increased vulnerability of glutamatergic, cholinergic, and GABAergic systems may also contribute to Parkinson's disease-related functional alterations. Combining normative modeling and neurotransmitter mapping may aid future research and drug development through deeper understanding of neurophysiological mechanisms that underlie specific clinical conditions.

Caudate functional networks influence brain structural changes with aging

Neurogenesis decline with aging may be associated with brain atrophy. Subventricular zone neuron precursor cells possibly modulate striatal neuronal activity via the release of soluble molecules. Neurogenesis decay in the subventricular zone may result in structural alterations of brain regions connected to the caudate, particularly to its medial component. The aim of this study was to investigate how the functional organization of caudate networks relates to structural brain changes with aging. One hundred and fifty-two normal subjects were recruited: 52 young healthy adults (≤35 years old), 42 middle-aged (36 ≤ 60 years old) and 58 elderly subjects (≥60 years old). In young adults, stepwise functional connectivity was used to characterize regions that connect to the medial and lateral caudate at different levels of link-step distances. A statistical comparison between the connectivity of medial and lateral caudate in young subjects was useful to define medial and lateral caudate connected regions. Atrophy of medial and lateral caudate connected regions was estimated in young, middle-aged and elderly subjects using T1-weighted images. Results showed that middle-aged and elderly adults exhibited decreased stepwise functional connectivity at one-link step from the caudate, particularly in the frontal, parietal, temporal and occipital brain regions, compared to young subjects. Elderly individuals showed increased stepwise functional connectivity in frontal, parietal, temporal and occipital lobes compared to both young and middle-aged adults. Additionally, elderly adults displayed decreased stepwise functional connectivity compared to middle-aged subjects in specific parietal and subcortical areas. Moreover, in young adults, the medial caudate showed higher direct connectivity to the basal ganglia (left thalamus), superior, middle and inferior frontal and inferior parietal gyri (medial caudate connected region) relative to the lateral caudate. Considering the opposite contrast, lateral caudate showed stronger connectivity to the basal ganglia (right pallidum), orbitofrontal, rostral anterior cingulate and insula cortices (lateral caudate connected region) compared to medial caudate. In elderly subjects, the medial caudate connected region showed greater atrophy relative to the lateral caudate connected region. Brain regions linked to the medial caudate appear to be more vulnerable to aging than lateral caudate connected areas. The adjacency to the subventricular zone may, at least partially, explain these findings. Stepwise functional connectivity analysis can be useful to evaluate the role of the subventricular zone in network disruptions in age-related neurodegenerative disorders.

Age-related vulnerability of the human brain connectome

Multifactorial models integrating brain variables at multiple scales are warranted to investigate aging and its relationship with neurodegeneration. Our aim was to evaluate how aging affects functional connectivity of pivotal regions of the human brain connectome (i.e., hubs), which represent potential vulnerability 'stations' to aging, and whether such effects influence the functional and structural changes of the whole brain. We combined the information of the functional connectome vulnerability, studied through an innovative graph-analysis approach (stepwise functional connectivity), with brain cortical thinning in aging. Using data from 128 cognitively normal participants (aged 20-85 years), we firstly investigated the topological functional network organization in the optimal healthy condition (i.e., young adults) and observed that fronto-temporo-parietal hubs showed a highly direct functional connectivity with themselves and among each other, while occipital hubs showed a direct functional connectivity within occipital regions and sensorimotor areas. Subsequently, we modeled cortical thickness changes over lifespan, revealing that fronto-temporo-parietal hubs were among the brain regions that changed the most, whereas occipital hubs showed a quite spared cortical thickness across ages. Finally, we found that cortical regions highly functionally linked to the fronto-temporo-parietal hubs in healthy adults were characterized by the greatest cortical thinning along the lifespan, demonstrating that the topology and geometry of hub functional connectome govern the region-specific structural alterations of the brain regions.

Increased functional connectivity in the right dorsal auditory stream after a full year of piano training in healthy older adults

Learning to play an instrument at an advanced age may help to counteract or slow down age-related cognitive decline. However, studies investigating the neural underpinnings of these effects are still scarce. One way to investigate the effects of brain plasticity is using resting-state functional connectivity (FC). The current study compared the effects of learning to play the piano (PP) against participating in music listening/musical culture (MC) lessons on FC in 109 healthy older adults. Participants underwent resting-state functional magnetic resonance imaging at three time points: at baseline, and after 6 and 12 months of interventions. Analyses revealed piano training-specific FC changes after 12 months of training. These include FC increase between right Heschl's gyrus (HG), and other right dorsal auditory stream regions. In addition, PP showed an increased anticorrelation between right HG and dorsal posterior cingulate cortex and FC increase between the right motor hand area and a bilateral network of predominantly motor-related brain regions, which positively correlated with fine motor dexterity improvements. We suggest to interpret those results as increased network efficiency for auditory-motor integration. The fact that functional neuroplasticity can be induced by piano training in healthy older adults opens new pathways to countervail age related decline.

Predicting executive functioning from brain networks: modality specificity and age effects

Healthy aging is associated with structural and functional network changes in the brain, which have been linked to deterioration in executive functioning (EF), while their neural implementation at the individual level remains unclear. As the biomarker potential of individual resting-state functional connectivity (RSFC) patterns has been questioned, we investigated to what degree individual EF abilities can be predicted from the gray-matter volume (GMV), regional homogeneity, fractional amplitude of low-frequency fluctuations (fALFF), and RSFC within EF-related, perceptuo-motor, and whole-brain networks in young and old adults. We examined whether the differences in out-of-sample prediction accuracy were modality-specific and depended on age or task-demand levels. Both uni- and multivariate analysis frameworks revealed overall low prediction accuracies and moderate-to-weak brain-behavior associations (R2 < 0.07, r < 0.28), further challenging the idea of finding meaningful markers for individual EF performance with the metrics used. Regional GMV, well linked to overall atrophy, carried the strongest information about individual EF differences in older adults, whereas fALFF, measuring functional variability, did so for younger adults. Our study calls for future research analyzing more global properties of the brain, different task-states and applying adaptive behavioral testing to result in sensitive predictors for young and older adults, respectively.

Predicting Executive Functioning from Brain Networks: Modality Specificity and Age Effects

Healthy aging is associated with structural and functional network changes in the brain, which have been linked to deterioration in executive functioning (EF), while their neural implementation at the individual level remains unclear. As the biomarker potential of individual resting-state functional connectivity (RSFC) patterns has been questioned, we investigated to what degree individual EF abilities can be predicted from gray-matter volume (GMV), regional homogeneity, fractional amplitude of low-frequency fluctuations (fALFF), and RSFC within EF-related, perceptuo-motor, and whole-brain networks in young and old adults. We examined whether differences in out-of-sample prediction accuracy were modality-specific and depended on age or task-demand levels. Both uni- and multivariate analysis frameworks revealed overall low prediction accuracies and moderate to weak brain-behavior associations (R2 < .07, r < .28), further challenging the idea of finding meaningful markers for individual EF performance with the metrics used. Regional GMV, well linked to overall atrophy, carried the strongest information about individual EF differences in older adults, whereas fALFF, measuring functional variability, did so for younger adults. Our study calls for future research analyzing more global properties of the brain, different task-states and applying adaptive behavioral testing to result in sensitive predictors for young and older adults, respectively.

Linking resting-state network fluctuations with systems of coherent synaptic density: A multimodal fMRI and 11C-UCB-J PET study

Introduction: Resting-state network (RSN) connectivity is a widely used measure of the brain's functional organization in health and disease; however, little is known regarding the underlying neurophysiology of RSNs. The aim of the current study was to investigate associations between RSN connectivity and synaptic density assessed using the synaptic vesicle glycoprotein 2A radioligand 11C-UCB-J PET. Methods: Independent component analyses (ICA) were performed on resting-state fMRI and PET data from 34 healthy adult participants (16F, mean age: 46 ± 15 years) to identify a priori RSNs of interest (default-mode, right frontoparietal executive-control, salience, and sensorimotor networks) and select sources of 11C-UCB-J variability (medial prefrontal, striatal, and medial parietal). Pairwise correlations were performed to examine potential intermodal associations between the fractional amplitude of low-frequency fluctuations (fALFF) of RSNs and subject loadings of 11C-UCB-J source networks both locally and along known anatomical and functional pathways. Results: Greater medial prefrontal synaptic density was associated with greater fALFF of the anterior default-mode, posterior default-mode, and executive-control networks. Greater striatal synaptic density was associated with greater fALFF of the anterior default-mode and salience networks. Post-hoc mediation analyses exploring relationships between aging, synaptic density, and RSN activity revealed a significant indirect effect of greater age on fALFF of the anterior default-mode network mediated by the medial prefrontal 11C-UCB-J source. Discussion: RSN functional connectivity may be linked to synaptic architecture through multiple local and circuit-based associations. Findings regarding healthy aging, lower prefrontal synaptic density, and lower default-mode activity provide initial evidence of a neurophysiological link between RSN activity and local synaptic density, which may have relevance in neurodegenerative and psychiatric disorders.

Brain network architecture constrains age-related cortical thinning

Age-related cortical atrophy, approximated by cortical thickness measurements from magnetic resonance imaging, follows a characteristic pattern over the lifespan. Although its determinants remain unknown, mounting evidence demonstrates correspondence between the connectivity profiles of structural and functional brain networks and cortical atrophy in health and neurological disease. Here, we performed a cross-sectional multimodal neuroimaging analysis of 2633 individuals from a large population-based cohort to characterize the association between age-related differences in cortical thickness and functional as well as structural brain network topology. We identified a widespread pattern of age-related cortical thickness differences including "hotspots" of pronounced age effects in sensorimotor areas. Regional age-related differences were strongly correlated within the structurally defined node neighborhood. The overall pattern of thickness differences was found to be anchored in the functional network hierarchy as encoded by macroscale functional connectivity gradients. Lastly, the identified difference pattern covaried significantly with cognitive and motor performance. Our findings indicate that connectivity profiles of functional and structural brain networks act as organizing principles behind age-related cortical thinning as an imaging surrogate of cortical atrophy.

Covariance-based vs. correlation-based functional connectivity dissociates healthy aging from Alzheimer disease

Prior studies of aging and Alzheimer disease have evaluated resting state functional connectivity (FC) using either seed-based correlation (SBC) or independent component analysis (ICA), with a focus on particular functional systems. SBC and ICA both are insensitive to differences in signal amplitude. At the same time, accumulating evidence indicates that the amplitude of spontaneous BOLD signal fluctuations is physiologically meaningful. We systematically compared covariance-based FC, which is sensitive to amplitude, vs. correlation-based FC, which is not, in affected individuals and controls drawn from two cohorts of participants including autosomal dominant Alzheimer disease (ADAD), late onset Alzheimer disease (LOAD), and age-matched controls. Functional connectivity was computed over 222 regions of interest and group differences were evaluated in terms of components projected onto a space of lower dimension. Our principal observations are: (1) Aging is associated with global loss of resting state fMRI signal amplitude that is approximately uniform across resting state networks. (2) Thus, covariance FC measures decrease with age whereas correlation FC is relatively preserved in healthy aging. (3) In contrast, symptomatic ADAD and LOAD both lead to loss of spontaneous activity amplitude as well as severely degraded correlation structure. These results demonstrate a double dissociation between age vs. Alzheimer disease and the amplitude vs. correlation structure of resting state BOLD signals. Modeling results suggest that the AD-associated loss of correlation structure is attributable to a relative increase in the fraction of locally restricted as opposed to widely shared variance.

Brain Structure and Function Predict Adherence to an Exercise Intervention in Older Adults

INTRODUCTION

Individual differences in brain structure and function in older adults are potential proxies of brain reserve or maintenance and may provide mechanistic predictions of adherence to exercise. We hypothesized that multimodal neuroimaging features would predict adherence to a 6-month randomized controlled trial of exercise in 131 older adults (age, 65.79 ± 4.65 yr, 63% female), alone and in combination with psychosocial, cognitive, and health measures.

METHODS

Regularized elastic net regression within a nested cross-validation framework was applied to predict adherence to the intervention in three separate models (brain structure and function only; psychosocial, health, and demographic data only; and a multimodal model).

RESULTS

Higher cortical thickness in somatosensory and inferior frontal regions and less surface area in primary visual and inferior frontal regions predicted adherence. Higher nodal functional connectivity (degree count) in default, frontoparietal, and attentional networks and less nodal strength in primary visual and temporoparietal networks predicted exercise adherence ( r = 0.24, P = 0.004). Survey and clinical measures of gait and walking self-efficacy, biological sex, and perceived stress also predicted adherence ( r = 0.17, P = 0.056); however, this prediction was not significant when tested against a null test statistic. A combined multimodal model achieved the highest predictive strength ( r = 0.28, P = 0.001).

CONCLUSIONS

Our results suggest that there is a substantial utility of using brain-based measures in future research into precision and individualized exercise interventions older adults.

Longitudinal functional connectivity patterns of the default mode network in healthy older adults

Cross-sectional studies have consistently identified age-associated alterations in default mode network (DMN) functional connectivity (FC). Yet, research on longitudinal trajectories of FC changes of the DMN in healthy aging is less conclusive. For the present study, we used a resting state functional MRI dataset drawn from the Longitudinal Healthy Aging Brain Database Project (LHAB) collected in 5 occasions over a course of 7 years (baseline N = 232, age range: 64-87 y, mean age = 70.85 y). FC strength changes within the DMN and its regions were investigated using a network-based statistical method suitable for the analysis of longitudinal data. The average DMN FC strength remained stable, however, various DMN components showed differential age- and time-related effects. Our results revealed a complex pattern of longitudinal change seen as decreases and increases of FC strength encompassing the majority of DMN regions, while age-related effects were negative and present in select brain areas. These findings testify to the growing importance of longitudinal studies using more sophisticated fine-grained tools needed to highlight the complexity of the functional reorganization of DMN with healthy aging.

Covariance and Correlation Analysis of Resting State Functional Magnetic Resonance Imaging Data Acquired in a Clinical Trial of Mindfulness-Based Stress Reduction and Exercise in Older Individuals

We describe and apply novel methodology for whole-brain analysis of resting state fMRI functional connectivity data, combining conventional multi-channel Pearson correlation with covariance analysis. Unlike correlation, covariance analysis preserves signal amplitude information, which feature of fMRI time series may carry physiological significance. Additionally, we demonstrate that dimensionality reduction of the fMRI data offers several computational advantages including projection onto a space of manageable dimension, enabling linear operations on functional connectivity measures and exclusion of variance unrelated to resting state network structure. We show that group-averaged, dimensionality reduced, covariance and correlation matrices are related, to reasonable approximation, by a single scalar factor. We apply this methodology to the analysis of a large, resting state fMRI data set acquired in a prospective, controlled study of mindfulness training and exercise in older, sedentary participants at risk for developing cognitive decline. Results show marginally significant effects of both mindfulness training and exercise in both covariance and correlation measures of functional connectivity.

Association of Age and Structural Brain Changes With Functional Connectivity and Executive Function in a Middle-Aged to Older Population-Based Cohort

Aging is accompanied by structural brain changes that are thought to underlie cognitive decline and dementia. Yet little is known regarding the association between increasing age, structural brain damage, and alterations of functional brain connectivity. The aim of this study was to evaluate whether cortical thickness and white matter damage as markers of age-related structural brain changes are associated with alterations in functional connectivity in non-demented healthy middle-aged to older adults. Therefore, we reconstructed functional connectomes from resting-state functional magnetic resonance imaging (MRI) (rsfMRI) data of 976 subjects from the Hamburg City Health Study, a prospective population-based study including participants aged 45-74 years from the metropolitan region Hamburg, Germany. We performed multiple linear regressions to examine the association of age, cortical thickness, and white matter damage quantified by the peak width of skeletonized mean diffusivity (PSMD) from diffusion tensor imaging on whole-brain network connectivity and four predefined resting state networks (default mode, dorsal, salience, and control network). In a second step, we extracted subnetworks with age-related decreased functional connectivity from these networks and conducted a mediation analysis to test whether the effect of age on these networks is mediated by decreased cortical thickness or PSMD. We observed an independent association of higher age with decreased functional connectivity, while there was no significant association of functional connectivity with cortical thickness or PSMD. Mediation analysis identified cortical thickness as a partial mediator between age and default subnetwork connectivity and functional connectivity within the default subnetwork as a partial mediator between age and executive cognitive function. These results indicate that, on a global scale, functional connectivity is not determined by structural damage in healthy middle-aged to older adults. There is a weak association of higher age with decreased functional connectivity which, for specific subnetworks, appears to be mediated by cortical thickness.

Higher-order resting state network association with the useful field of view task in older adults

Speed-of-processing abilities decline with age yet are important in performing instrumental activities of daily living. The useful field of view, or Double Decision task, assesses speed-of-processing and divided attention. Performance on this task is related to attention, executive functioning, and visual processing abilities in older adults, and poorer performance predicts more motor vehicle accidents in the elderly. Cognitive training in this task reduces risk of dementia. Structural and functional neural correlates of this task suggest that higher-order resting state networks may be associated with performance on the Double Decision task, although this has never been explored. This study aimed to assess the association of within-network connectivity of the default mode network, dorsal attention network, frontoparietal control network, and cingulo-opercular network with Double Decision task performance, and subcomponents of this task in a sample of 267 healthy older adults. Multiple linear regressions showed that connectivity of the cingulo-opercular network is associated with visual speed-of-processing and divided attention subcomponents of the Double Decision task. Cingulo-opercular network and frontoparietal control network connectivity is associated with Double Decision task performance. Stronger connectivity is related to better performance in all cases. These findings confirm the unique role of the cingulo-opercular network in visual attention and sustained divided attention. Frontoparietal control network connectivity, in addition to cingulo-opercular network connectivity, is related to Double Decision task performance, a task implicated in reduced dementia risk. Future research should explore the role these higher-order networks play in reduced dementia risk after cognitive intervention using the Double Decision task.

Individual prediction of hemispheric similarity of functional connectivity during normal aging

In the aging process of normal people, the functional activity pattern of brain is in constant change, and the change of brain runs through the whole life cycle, which plays a crucial role in the track of individual development. In recent years, some studies had been carried out on the brain functional activity pattern during individual aging process from different perspectives, which provided an opportunity for the problem we want to study. In this study, we used the resting-state functional magnetic resonance imaging (rs-fMRI) data from Cambridge Center for Aging and Neuroscience (Cam-CAN) database with large sample and long lifespan, and computed the functional connectivity (FC) values for each individual. Based on these values, the hemispheric similarity of functional connectivity (HSFC) obtained by Pearson correlation was used as the starting point of this study. We evaluated the ability of individual recognition of HSFC in the process of aging, as well as the variation trend with aging process. The results showed that HSFC could be used to identify individuals effectively, and it could reflect the change rule in the process of aging. In addition, we observed a series of results at the sub-module level and find that the recognition rate in the sub-module was different from each other, as well as the trend with age. Finally, as a validation, we repeated the main results by human brainnetome atlas (BNA) template and without global signal regression, found that had a good robustness. This also provides a new clue to hemispherical change patterns during normal aging.

Dynamic functional connectivity profile of the salience network across the life span

The insular cortex and anterior cingulate cortex together comprise the salience or midcingulo-insular network, involved in detecting salient events and initiating control signals to mediate brain network dynamics. The extent to which functional coupling between the salience network and the rest of the brain undergoes changes due to development and aging is at present largely unexplored. Here, we examine dynamic functional connectivity (dFC) of the salience network in a large life span sample (n = 601; 6-85 years old). A sliding-window analysis and k-means clustering revealed five states of dFC formed with the salience network, characterized by either widespread asynchrony or different patterns of synchrony between the salience network and other brain regions. We determined the frequency, dwell time, total transitions, and specific state-to-state transitions for each state and subject, regressing the metrics with subjects' age to identify life span trends. A dynamic state characterized by low connectivity between the salience network and the rest of the brain had a strong positive quadratic relationship between age and both frequency and dwell time. Additional frequency, dwell time, total transitions, and state-to-state transition trends were observed with other salience network states. Our results highlight the metastable dynamics of the salience network and its role in the maturation of brain regions critical for cognition.

The Influence of Discrete Negative and Positive Stimuli on Recognition Memory of Younger vs. Older Adults

Background: The effects of emotional stimuli on memory in older adults are often addressed in terms of socio-emotional selectivity theory and the valence dimension. Older adults usually remember positive stimuli better than negative stimuli. However, studies examining the effects of discrete emotions on the elderly are still limited. The present study examined the effects of negative and positive discrete emotions (fear, disgust, and happiness) on recognition memory of older and younger adults. Method: In the encoding phase, participants studied happiness-, disgust-, fear-, and neutral- related photos while doing a line discrimination task that assessed their attention. After 45 minutes, they completed an old/new recognition memory test on a confidence rating scale and also rated self-relevance of photos. Results: Younger participants showed a more liberal response bias for disgust- and fear-related stimuli, and were also more accurate in recognizing disgust-related photos compared to others. Older adults showed a more liberal bias only for disgust-related stimuli, however, their recognition accuracy did not differ across emotion categories. Conclusion: These results suggested that the effect of disgust-related stimuli on recognition memory may decrease with age and emotion effects cannot solely be accounted for by the valence/arousal dimensions.

Age-related assessment of diffusion parameters in specific brain tracts correlated with cortical thinning

The aging process is associated with many brain structural alterations. These changes are not associated with neuronal loss but can be due to cortical structural changes that may be related to white matter (WM) structural alterations. In this study, we evaluated age-related changes in WM and gray matter (GM) parameters and how they correlate for specific brain tracts in a cohort of 158 healthy individuals, aged between 18 and 83 years old. In the tract-cortical analysis, cortical regions connected by tracts demonstrated similar thinning patterns for the majority of tracts. Additionally, a significant relationship was found between mean cortical thinning rate with fractional anisotropy (FA) and mean diffusivity (MD) alteration rates. For all tracts, age was the main effect controlling diffusion parameter alterations. We found no direct correlations between cortical thickness and FA or MD, except for in the fornix, for which the subcallosal gyrus thickness was significantly correlated to FA and MD (p < 0.05 FDR corrected). Our findings lead to the conclusion that alterations in the WM diffusion parameters are explained by the aging process, also associated with cortical thickness changes. Also, the alteration rates of the structural parameters are correlated to the different brain tracts in the aging process.