The Effect of Aging on Resting State Connectivity of Predefined Networks in the Brain

Aging of Amateur Singers and Non-singers: From Behavior to Resting-state Connectivity

Healthy aging is associated with extensive changes in brain structure and physiology, with impacts on cognition and communication. The "mental exercise hypothesis" proposes that certain lifestyle factors such as singing-perhaps the most universal and accessible music-making activity-can affect cognitive functioning and reduce cognitive decline in aging, but the neuroplastic mechanisms involved remain unclear. To address this question, we examined the association between age and resting-state functional connectivity (RSFC) in 84 healthy singers and nonsingers in five networks (auditory, speech, language, default mode, and dorsal attention) and its relationship to auditory cognitive aging. Participants underwent cognitive testing and fMRI. Our results show that RSFC is not systematically lower with aging and that connectivity patterns vary between singers and nonsingers. Furthermore, our results show that RSFC of the precuneus in the default mode network was associated with auditory cognition. In these regions, lower RSFC was associated with better auditory cognitive performance for both singers and nonsingers. Our results show, for the first time, that basic brain physiology differs in singers and nonsingers and that some of these differences are associated with cognitive performance.

Functional gradients reveal altered functional segregation in patients with amnestic mild cognitive impairment and Alzheimer's disease

Alzheimer's disease and amnestic mild cognitive impairment are associated with disrupted functional organization in brain networks, involved with alteration of functional segregation. Connectome gradients are a new tool representing brain functional topological organization to smoothly capture the human macroscale hierarchy. Here, we examined altered topological organization in amnestic mild cognitive impairment and Alzheimer's disease by connectome gradient mapping. We further quantified functional segregation by gradient dispersion. Then, we systematically compared the alterations observed in amnestic mild cognitive impairment and Alzheimer's disease patients with those in normal controls in a two-dimensional functional gradient space from both the whole-brain level and module level. Compared with normal controls, the first gradient, which described the neocortical hierarchy from unimodal to transmodal regions, showed a more distributed and significant suppression in Alzheimer's disease than amnestic mild cognitive impairment patients. Furthermore, gradient dispersion showed significant decreases in Alzheimer's disease at both the global level and module level, whereas this alteration was limited only to limbic areas in amnestic mild cognitive impairment. Notably, we demonstrated that suppressed gradient dispersion in amnestic mild cognitive impairment and Alzheimer's disease was associated with cognitive scores. These findings provide new evidence for altered brain hierarchy in amnestic mild cognitive impairment and Alzheimer's disease, which strengthens our understanding of the progressive mechanism of cognitive decline.

Directed functional connectivity of the sensorimotor system in young and older individuals

Introduction

Studies in the sensorimotor system of older versus young individuals have shown alterations in functional connectivity and organization. Our objective was to explore the implications of these differences in terms of local organizations, and to identify processes that correlate with neuropsychological parameters.

Methods

Using a novel multivariate analysis method on resting-state functional MRI data obtained from 50 young and 31 older healthy individuals, we identified directed 4-node functional pathways within the sensorimotor system and examined their correlations with neuropsychological assessments.

Results

In young individuals, the functional pathways were unidirectional, flowing from the primary motor and sensory cortices to higher motor and visual regions. In older individuals, the functional pathways were more complex. They originated either from the calcarine sulcus or the insula and passed through mutually coupled high-order motor areas before reaching the primary sensory and motor cortices. Additionally, the pathways in older individuals that resembled those found in young individuals exhibited a positive correlation with years of education.

Discussion

The flow pattern of young individuals suggests efficient and fast information transfer. In contrast, the mutual coupling of high-order motor regions in older individuals suggests an inefficient and slow transfer, a less segregated and a more integrated organization. The differences in the number of sensorimotor pathways and of their directionality suggests reduced efferent degenerated pathways and increased afferent compensated pathways. Furthermore, the positive effect of years of education may be associated with the Cognitive Reserve Hypothesis, implying that cognitive reserve could be maintained through specific information transfer pathways.

Atypical Hierarchical Connectivity Revealed by Stepwise Functional Connectivity in Aging

Hierarchical functional structure plays a crucial role in brain function. We aimed to investigate how aging affects hierarchical functional structure and to evaluate the relationship between such effects and molecular, microvascular, and cognitive features. We used resting-state functional magnetic resonance imaging (fMRI) data from 95 older adults (66.94 ± 7.23 years) and 44 younger adults (21.8 ± 2.53 years) and employed an innovative graph-theory-based analysis (stepwise functional connectivity (SFC)) to reveal the effects of aging on hierarchical functional structure in the brain. In the older group, an SFC pattern converged on the primary sensory-motor network (PSN) rather than the default mode network (DMN). Moreover, SFC decreased in the DMN and increased in the PSN at longer link-steps in aging, indicating a reconfiguration of brain hub systems during aging. Subsequent correlation analyses were performed between SFC values and molecular, microvascular features, and behavioral performance. Altered SFC patterns were associated with dopamine and serotonin, suggesting that altered hierarchical functional structure in aging is linked to the molecular fundament with dopamine and serotonin. Furthermore, increased SFC in the PSN, decreased SFC in the DMN, and accelerated convergence rate were all linked to poorer microvascular features and lower executive function. Finally, a mediation analysis among SFC features, microvascular features, and behavioral performance indicated that the microvascular state may influence executive function through SFC features, highlighting the interactive effects of SFC features and microvascular state on cognition.

Comment on Muth et al. Assessing Critical Flicker Fusion Frequency: Which Confounders? A Narrative Review. Medicina 2023, 59, 800

We first want to thank the authors of the excellent review for their contributions to summarizing the confounders associated with critical flicker fusion frequency (CFFF) [...].

Functional alterations in bipartite network of white and grey matters during aging

The effects of normal aging on functional connectivity (FC) within various brain networks of gray matter (GM) have been well-documented. However, the age effects on the networks of FC between white matter (WM) and GM, namely WM-GM FC, remains unclear. Evaluating crucial properties, such as global efficiency (GE), for a WM-GM FC network poses a challenge due to the absence of closed triangle paths which are essential for assessing network properties in traditional graph models. In this study, we propose a bipartite graph model to characterize the WM-GM FC network and quantify these challenging network properties. Leveraging this model, we assessed the WM-GM FC network properties at multiple scales across 1,462 cognitively normal subjects aged 22-96 years from three repositories (ADNI, BLSA and OASIS-3) and investigated the age effects on these properties throughout adulthood and during late adulthood (age ≥70 years). Our findings reveal that (1) heterogeneous alterations occurred in region-specific WM-GM FC over the adulthood and decline predominated during late adulthood; (2) the FC density of WM bundles engaged in memory, executive function and processing speed declined with age over adulthood, particularly in later years; and (3) the GE of attention, default, somatomotor, frontoparietal and limbic networks reduced with age over adulthood, and GE of visual network declined during late adulthood. These findings provide unpresented insights into multi-scale alterations in networks of WM-GM functional synchronizations during normal aging. Furthermore, our bipartite graph model offers an extendable framework for quantifying WM-engaged networks, which may contribute to a wide range of neuroscience research.

Functional network structure supports resilience to memory deficits in cognitively normal older adults with amyloid-β pathology

Older adults may harbor large amounts of amyloid-β (Aβ) pathology, yet still perform at age-normal levels on memory assessments. We tested whether functional brain networks confer resilience or compensatory mechanisms to support memory in the face of Aβ pathology. Sixty-five cognitively normal older adults received high-resolution resting state fMRI to assess functional networks, 18F-florbetapir-PET to measure Aβ, and a memory assessment. We characterized functional networks with graph metrics of local efficiency (information transfer), modularity (specialization of functional modules), and small worldness (balance of integration and segregation). There was no difference in functional network measures between older adults with high Aβ (Aβ+) compared to those with no/low Aβ (Aβ-). However, in Aβ+ older adults, increased local efficiency, modularity, and small worldness were associated with better memory performance, while this relationship did not occur Aβ- older adults. Further, the association between increased local efficiency and better memory performance in Aβ+ older adults was localized to local efficiency of the default mode network and hippocampus, regions vulnerable to Aβ and involved in memory processing. Our results suggest functional networks with modular and efficient structures are associated with resilience to Aβ pathology, providing a functional target for intervention.

Simple topological task-based functional connectivity features predict longitudinal behavioral change of fluid reasoning in the RANN cohort

Recent attention has been given to topological data analysis (TDA), and more specifically persistent homology (PH), to identify the underlying shape of brain network connectivity beyond simple edge pairings by computing connective components across different connectivity thresholds (see Sizemore et al., 2019). In the present study, we applied PH to task-based functional connectivity, computing 0-dimension Betti (B0) curves and calculating the area under these curves (AUC); AUC indicates how quickly a single connected component is formed across correlation filtration thresholds, with lower values interpreted as potentially analogous to lower whole-brain system segregation (e.g., Gracia-Tabuenca et al., 2020). One hundred sixty-three participants from the Reference Ability Neural Network (RANN) longitudinal lifespan cohort (age 20-80 years) were tested in-scanner at baseline and five-year follow-up on a battery of tests comprising four domains of cognition (i.e., Stern et al., 2014). We tested for 1.) age-related change in the AUC of the B0 curve over time, 2.) the predictive utility of AUC in accounting for longitudinal change in behavioral performance and 3.) compared system segregation to the PH approach. Results demonstrated longitudinal age-related decreases in AUC for Fluid Reasoning, with these decreases predicting longitudinal declines in cognition, even after controlling for demographic and brain integrity factors; moreover, change in AUC partially mediated the effect of age on change in cognitive performance. System segregation also significantly decreased with age in three of the four cognitive domains but did not predict change in cognition. These results argue for greater application of TDA to the study of aging.

How Does Aging Affect Whole-brain Functional Network Connectivity? Evidence from An ICA Method

Many studies have shown that changes in the functional connectivity are diverse along with aging. However, few studies have addressed how aging affects connectivity among large-scale brain networks, and it is challenging to examine gradual aging trajectories from middle adulthood to old age. In this work, based on large-sample fMRI data from 6300 subjects aged between 49 to 73 years, we apply an independent component analysis-based method called NeuroMark to extract brain functional networks and their connectivity (i.e., functional network connectivity (FNC)), and then propose a two-level statistical analysis method to explore robust aging-related changes in functional network connectivity. We found that the enhanced FNCs mainly occur between different functional domains, involving the default mode and cognitive control networks, while the reduced FNCs come from not only between different domains but also within the same domain, primarily relating to the visual network, cognitive control network and cerebellum. Our results emphasize the diversity of brain aging and provide new evidence for non-pathological aging of the whole brain.Clinical Relevance-This provides new evidence for non-pathological aging of functional network connectivity in the whole brain.

Changes in white matter functional networks across late adulthood

Introduction

The aging brain is characterized by decreases in not only neuronal density but also reductions in myelinated white matter (WM) fibers that provide the essential foundation for communication between cortical regions. Age-related degeneration of WM has been previously characterized by histopathology as well as T2 FLAIR and diffusion MRI. Recent studies have consistently shown that BOLD (blood oxygenation level dependent) effects in WM are robustly detectable, are modulated by neural activities, and thus represent a complementary window into the functional organization of the brain. However, there have been no previous systematic studies of whether or how WM BOLD signals vary with normal aging. We therefore performed a comprehensive quantification of WM BOLD signals across scales to evaluate their potential as indicators of functional changes that arise with aging.

Methods

By using spatial independent component analysis (ICA) of BOLD signals acquired in a resting state, WM voxels were grouped into spatially distinct functional units. The functional connectivities (FCs) within and among those units were measured and their relationships with aging were assessed. On a larger spatial scale, a graph was reconstructed based on the pair-wise connectivities among units, modeling the WM as a complex network and producing a set of graph-theoretical metrics.

Results

The spectral powers that reflect the intensities of BOLD signals were found to be significantly affected by aging across more than half of the WM units. The functional connectivities (FCs) within and among those units were found to decrease significantly with aging. We observed a widespread reduction of graph-theoretical metrics, suggesting a decrease in the ability to exchange information between remote WM regions with aging.

Discussion

Our findings converge to support the notion that WM BOLD signals in specific regions, and their interactions with other regions, have the potential to serve as imaging markers of aging.

Functional topography of the neocortex predicts covariation in complex cognitive and basic motor abilities

Although higher-order cognitive and lower-order sensorimotor abilities are generally regarded as distinct and studied separately, there is evidence that they not only covary but also that this covariation increases across the lifespan. This pattern has been leveraged in clinical settings where a simple assessment of sensory or motor ability (e.g. hearing, gait speed) can forecast age-related cognitive decline and risk for dementia. However, the brain mechanisms underlying cognitive, sensory, and motor covariation are largely unknown. Here, we examined whether such covariation in midlife reflects variability in common versus distinct neocortical networks using individualized maps of functional topography derived from BOLD fMRI data collected in 769 45-year-old members of a population-representative cohort. Analyses revealed that variability in basic motor but not hearing ability reflected individual differences in the functional topography of neocortical networks typically supporting cognitive ability. These patterns suggest that covariation in motor and cognitive abilities in midlife reflects convergence of function in higher-order neocortical networks and that gait speed may not be simply a measure of physical function but rather an integrative index of nervous system health.

Persistent homology-based functional connectivity and its association with cognitive ability: Life-span study

Brain-segregation attributes in resting-state functional networks have been widely investigated to understand cognition and cognitive aging using various approaches [e.g., average connectivity within/between networks and brain system segregation (BSS)]. While these approaches have assumed that resting-state functional networks operate in a modular structure, a complementary perspective assumes that a core-periphery or rich club structure accounts for brain functions where the hubs are tightly interconnected to each other to allow for integrated processing. In this article, we apply a novel method, persistent homology (PH), to develop an alternative to standard functional connectivity by quantifying the pattern of information during the integrated processing. We also investigate whether PH-based functional connectivity explains cognitive performance and compare the amount of variability in explaining cognitive performance for three sets of independent variables: (1) PH-based functional connectivity, (2) graph theory-based measures, and (3) BSS. Resting-state functional connectivity data were extracted from 279 healthy participants, and cognitive ability scores were generated in four domains (fluid reasoning, episodic memory, vocabulary, and processing speed). The results first highlight the pattern of brain-information flow over whole brain regions (i.e., integrated processing) accounts for more variance of cognitive abilities than other methods. The results also show that fluid reasoning and vocabulary performance significantly decrease as the strength of the additional information flow on functional connectivity with the shortest path increases. While PH has been applied to functional connectivity analysis in recent studies, our results demonstrate potential utility of PH-based functional connectivity in understanding cognitive function.

Resting State Network Segregation Modulates Age-Related Differences in Language Production

Older adults typically exhibit decline in language production. However, how the brain supports or fails to support these processes is unclear. Moreover, there are competing hypotheses about the nature of age-related neural changes and whether age-related increases in neural activity reflect compensation or a decline in neural efficiency. In the current study, we investigated the neural bases of language production focusing on resting state functional connectivity. We hypothesized that language production performance, functional connectivity, and their relationship would differ as a function of age. Consistent with prior work, older age was associated with worse language production performance. Functional connectivity analyses showed that network segregation within the left hemisphere language network was maintained across adulthood. However, increased age was associated with lower whole brain network segregation. Moreover, network segregation was related to language production ability. In both network analyses, there were significant interactions with age-higher network segregation was associated with better language production abilities for younger and middle-aged adults, but not for older adults. Interestingly, there was a stronger relationship between language production and the whole brain network segregation than between production and the language network. These results highlight the utility of network segregation measures as an index of brain function, with higher network segregation associated with better language production ability. Moreover, these results are consistent with stability in the left hemisphere language network across adulthood and suggest that dedifferentiation among brain networks, outside of the language network, is a hallmark of aging and may contribute to age-related language production difficulties.

Changes of creative ability and underlying brain network connectivity throughout the lifespan

Creativity, or divergent thinking, is essential to and supported by cognitive functions necessary for everyday tasks. The current study investigates divergent thinking and its neural mechanisms from adolescence to late adulthood. To do this, 180 healthy participants completed a creativity task called the egg task including 86 adolescents (mean age (SD) = 13.62 (1.98)), 52 young adults (24.92 (3.60), and 42 older adults (62.84 (7.02)). Additionally, a subsample of 111 participants completed a resting-state fMRI scan. After investigating the impact of age on different divergent thinking metrics, we investigated the impact of age on the association between divergent thinking and resting-state functional connectivity within and between major resting-state brain networks associated with creative thinking: the DMN, ECN, and SN. Adolescents tended to be less creative than both young and older adults in divergent thinking scores related to expansion creativity, and not in persistent creativity, while young and older adults performed relatively similar. We found that adolescents' functional integrity of the executive control network (ECN) was positively associated with expansion creativity, which was significantly different from the negative association in both the young and older adults. These results suggest that creative performance and supporting brain networks change throughout the lifespan.

Predicting executive functioning from functional brain connectivity: network specificity and age effects

Healthy aging is associated with altered executive functioning (EF). Earlier studies found age-related differences in EF performance to be partially accounted for by changes in resting-state functional connectivity (RSFC) within brain networks associated with EF. However, it remains unclear which role RSFC in EF-associated networks plays as a marker for individual differences in EF performance. Here, we investigated to what degree individual abilities across 3 different EF tasks can be predicted from RSFC within EF-related, perceptuo-motor, whole-brain, and random networks separately in young and old adults. Specifically, we were interested if (i) young and old adults differ in predictability depending on network or EF demand level (high vs. low), (ii) an EF-related network outperforms EF-unspecific networks when predicting EF abilities, and (iii) this pattern changes with demand level. Both our uni- and multivariate analysis frameworks analyzing interactions between age × demand level × networks revealed overall low prediction accuracies and a general lack of specificity regarding neurobiological networks for predicting EF abilities. This questions the idea of finding markers for individual EF performance in RSFC patterns and calls for future research replicating the current approach in different task states, brain modalities, different, larger samples, and with more comprehensive behavioral measures.

Education differentiates cognitive performance and resting state fMRI connectivity in healthy aging

Objectives

In healthy aging, the way people cope differently with cognitive and neural decline is influenced by exposure to cognitively enriching life-experiences. Education is one of them, so that in general, the higher the education, the better the expected cognitive performance in aging. At the neural level, it is not clear yet how education can differentiate resting state functional connectivity profiles and their cognitive underpinnings. Thus, with this study, we aimed to investigate whether the variable education allowed for a finer description of age-related differences in cognition and resting state FC.

Methods

We analyzed in 197 healthy individuals (137 young adults aged 20-35 and 60 older adults aged 55-80 from the publicly available LEMON database), a pool of cognitive and neural variables, derived from magnetic resonance imaging, in relation to education. Firstly, we assessed age-related differences, by comparing young and older adults. Then, we investigated the possible role of education in outlining such differences, by splitting the group of older adults based on their education.

Results

In terms of cognitive performance, older adults with higher education and young adults were comparable in language and executive functions. Interestingly, they had a wider vocabulary compared to young adults and older adults with lower education. Concerning functional connectivity, the results showed significant age- and education-related differences within three networks: the Visual-Medial, the Dorsal Attentional, and the Default Mode network (DMN). For the DMN, we also found a relationship with memory performance, which strengthen the evidence that this network has a specific role in linking cognitive maintenance and FC at rest in healthy aging.

Discussion

Our study revealed that education contributes to differentiating cognitive and neural profiles in healthy older adults. Also, the DMN could be a key network in this context, as it may reflect some compensatory mechanisms relative to memory capacities in older adults with higher education.

Aging brain shows joint declines in brain within-network connectivity and between-network connectivity: a large-sample study (N > 6,000)

Introduction

Numerous studies have shown that aging has important effects on specific functional networks of the brain and leads to brain functional connectivity decline. However, no studies have addressed the effect of aging at the whole-brain level by studying both brain functional networks (i.e., within-network connectivity) and their interaction (i.e., between-network connectivity) as well as their joint changes.

Methods

In this work, based on a large sample size of neuroimaging data including 6300 healthy adults aged between 49 and 73 years from the UK Biobank project, we first use our previously proposed priori-driven independent component analysis (ICA) method, called NeuroMark, to extract the whole-brain functional networks (FNs) and the functional network connectivity (FNC) matrix. Next, we perform a two-level statistical analysis method to identify robust aging-related changes in FNs and FNCs, respectively. Finally, we propose a combined approach to explore the synergistic and paradoxical changes between FNs and FNCs.

Results

Results showed that the enhanced FNCs mainly occur between different functional domains, involving the default mode and cognitive control networks, while the reduced FNCs come from not only between different domains but also within the same domain, primarily relating to the visual network, cognitive control network, and cerebellum. Aging also greatly affects the connectivity within FNs, and the increased within-network connectivity along with aging are mainly within the sensorimotor network, while the decreased within-network connectivity significantly involves the default mode network. More importantly, many significant joint changes between FNs and FNCs involve default mode and sub-cortical networks. Furthermore, most synergistic changes are present between the FNCs with reduced amplitude and their linked FNs, and most paradoxical changes are present in the FNCs with enhanced amplitude and their linked FNs.

Discussion

In summary, our study emphasizes the diversity of brain aging and provides new evidence via novel exploratory perspectives for non-pathological aging of the whole brain.

Large-Scale Network Connectivity and Cognitive Function Changes After Exercise Training in Older Adults with Intact Cognition and Mild Cognitive Impairment

Background

Despite growing evidence regarding the association between exercise training (ET) and functional brain network connectivity, little is known about the effects of ET on large-scale within- and between-network functional connectivity (FC) of core brain networks.

Objective

We investigated the effects of ET on within- and between-network functional connectivity of the default mode network (DMN), frontoparietal network (FPN), and salience network (SAL) in older adults with intact cognition (CN) and older adults diagnosed with mild cognitive impairment (MCI). The association between ET-induced changes in FC and cognitive performance was examined.

Methods

33 older adults (78.0±7.0 years; 16 MCI and 17 CN) participated in this study. Before and after a 12-week walking ET intervention, participants underwent a graded exercise test, Controlled Oral Word Association Test (COWAT), Rey Auditory Verbal Learning Test (RAVLT), a narrative memory test (logical memory; LM), and a resting-state fMRI scan. We examined the within (_W) and between (_B) network connectivity of the DMN, FPN, and SAL. We used linear regression to examine associations between ET-related changes in network connectivity and cognitive function.

Results

There were significant improvements in cardiorespiratory fitness, COWAT, RAVLT, and LM after ET across participants. Significant increases in DMN_W and SAL_W, and DMN-FPN_B, DMN-SAL_B, and FPN-SAL_B were observed after ET. Greater SAL_W and FPN-SAL_B were associated with enhanced LM immediate recall performance after ET in both groups.

Conclusion

Increased within- and between-network connectivity following ET may subserve improvements in memory performance in older individuals with intact cognition and with MCI due to Alzheimer's disease.

Task difficulty modulates age-related differences in functional connectivity during word production

Older adults typically report increased difficulty with language production, while its neural bases are less clear. The current study investigated the neural bases of age-related differences in language production at the word level and the modulating effect of task difficulty, focusing on task-based functional connectivity. Using an English phonological Go/No-Go picture naming task, task difficulty was manipulated by varying the proportion of naming trials (Go trials) and inhibition trials (No-Go trials) across runs. Behaviorally, compared to younger adults, older adults performed worse, and showed larger effects of task difficulty. Neurally, older adults had lower within language network connectivity compared to younger adults. Moreover, older adults' language network became less segregated as task difficulty increased. These results are consistent with the Compensation-Related Utilization of Neural Circuits Hypothesis, suggesting that the brain becomes less specified and efficient with increased task difficulty, and that these effects are stronger among older adults (i.e., more dedifferentiated).

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.

Graph-theoretical insights into the effects of aging on the speech production network

Speech production relies on the interplay of different brain regions. Healthy aging leads to complex changes in speech processing and production. Here, we investigated how the whole-brain functional connectivity of healthy elderly individuals differs from that of young individuals. In total, 23 young (aged 24.6 ± 2.2 years) and 23 elderly (aged 64.1 ± 6.5 years) individuals performed a picture naming task during functional magnetic resonance imaging. We determined whole-brain functional connectivity matrices and used them to compute group averaged speech production networks. By including an emotionally neutral and an emotionally charged condition in the task, we characterized the speech production network during normal and emotionally challenged processing. Our data suggest that the speech production network of elderly healthy individuals is as efficient as that of young participants, but that it is more functionally segregated and more modularized. By determining key network regions, we showed that although complex network changes take place during healthy aging, the most important network regions remain stable. Furthermore, emotional distraction had a larger influence on the young group's network than on the elderly's. We demonstrated that, from the neural network perspective, elderly individuals have a higher capacity for emotion regulation based on their age-related network re-organization.

Cognitive and neuroimaging outcomes in individuals with benign and low-grade brain tumours receiving radiotherapy: a protocol for a prospective cohort study

INTRODUCTION

Radiation-induced cognitive decline (RICD) occurs in 50%-90% of adult patients 6 months post-treatment. In patients with low-grade and benign tumours with long expected survival, this is of paramount importance. Despite advances in radiation therapy (RT) treatment delivery, better understanding of structures important for RICD is necessary to improve cognitive outcomes. We hypothesise that RT may affect network topology and microstructural integrity on MRI prior to any gross anatomical or apparent cognitive changes. In this longitudinal cohort study, we aim to determine the effects of RT on brain structural and functional integrity and cognition.

METHODS AND ANALYSIS

This study will enroll patients with benign and low-grade brain tumours receiving partial brain radiotherapy. Patients will receive either hypofractionated (>2 Gy/fraction) or conventionally fractionated (1.8-2 Gy/fraction) RT. All participants will be followed for 12 months, with MRIs conducted pre-RT and 6-month and 12 month post-RT, along with a battery of neurocognitive tests and questionnaires. The study was initiated in late 2018 and will continue enrolling through 2024 with final follow-ups completing in 2025. The neurocognitive battery assesses visual and verbal memory, attention, executive function, processing speed and emotional cognition. MRI protocols incorporate diffusion tensor imaging and resting state fMRI to assess structural connectivity and functional connectivity, respectively. We will estimate the association between radiation dose, imaging metrics and cognitive outcomes.

ETHICS AND DISSEMINATION

This study has been approved by the Research Subjects Review Board at the University of Rochester (STUDY00001512: Cognitive changes in patients receiving partial brain radiation). All results will be published in peer-reviewed journals and at scientific conferences.

TRIAL REGISTRATION NUMBER

ClinicalTrials.gov NCT04390906.

Age Related Functional Connectivity Signature Extraction Using Energy-Based Machine Learning Techniques

The study of brain connectivity plays an important role in understanding the functional organizations of the brain. It also helps to identify connectivity signatures that can be used for evaluating neural disorders and monitoring treatment efficacy. In this work, age-related changes in brain connectivity are studied to obtain aging signatures based on various modeling techniques. These include an energy-based machine learning technique to identify brain network interaction differences between two age groups with a large (30 years) age gap between them. Disconnectivity graphs and activation maps of the seven prominent resting-state networks (RSN) were obtained from functional MRI data of old and young adult subjects. Two-sample t-tests were performed on the local minimums with Bonferroni correction to control the family-wise error rate. These local minimums are connectivity states showing not only which brain regions but also how strong they are working together. They work as aging signatures that can be used to differentiate young and old groups. We found that the attention network's connectivity signature is a state with all the regions working together and young subjects have a stronger average connectivity among these regions. We have also found a common pattern between young and old subjects where the left and right brain regions of the frontal network are sometimes working separately instead of together. In summary, in this work, we combined machine learning and statistical approaches to extract connectivity signatures, which can be utilized to distinguish aging brains and monitor possible treatment efficacy.

Longitudinal association between changes in resting-state network connectivity and cognition trajectories: The moderation role of a healthy diet

Introduction

Healthy diet has been shown to alter brain structure and function and improve cognitive performance, and prior work from our group showed that Mediterranean diet (MeDi) moderates the effect of between-network resting-state functional connectivity (rsFC) on cognitive function in a cross-sectional sample of healthy adults. The current study aimed to expand on this previous work by testing whether MeDi moderates the effects of changes in between- and within-network rsFC on changes in cognitive performance over an average of 5 years.

Methods

At baseline and 5-year follow up, 124 adults aged 20-80 years underwent resting state fMRI to measure connectivity within and between 10 pre-defined networks, and completed six cognitive tasks to measure each of four cognitive reference abilities (RAs): fluid reasoning (FLUID), episodic memory, processing speed and attention, and vocabulary. Participants were categorized into low, moderate, and high MeDi groups based on food frequency questionnaires (FFQs). Multivariable linear regressions were used to test relationships between MeDi, change in within- and between-network rsFC, and change in cognitive function.

Results

Results showed that MeDi group significantly moderated the effects of change in overall between-network and within-network rsFC on change in memory performance. Exploratory analyses on individual networks revealed that interactions between MeDi and between-network rsFC were significant for nearly all individual networks, whereas the moderating effect of MeDi on the relationship between within-network rsFC change and memory change was limited to a subset of specific functional networks.

Discussion

These findings suggest healthy diet may protect cognitive function by attenuating the negative effects of changes in connectivity over time. Further research is warranted to understand the mechanisms by which MeDi exerts its neuroprotective effects over the lifespan.

Age-dependent changes in the dynamic functional organization of the brain at rest: a cross-cultural replication approach

Age-associated changes in brain function play an important role in the development of neurodegenerative diseases. Although previous work has examined age-related changes in static functional connectivity, accumulating evidence suggests that advancing age is especially associated with alterations in the dynamic interactions and transitions between different brain states, which hitherto have received less attention. Conclusions of previous studies in this domain are moreover limited by suboptimal replicability of resting-state functional magnetic resonance imaging (fMRI) and culturally homogenous cohorts. Here, we investigate the robustness of age-associated changes in dynamic functional connectivity (dFC) by capitalizing on the availability of fMRI cohorts from two cultures (Western European and Chinese). In both the LEMON (Western European) and SALD (Chinese) cohorts, we consistently identify two distinct states: a more frequent segregated within-network connectivity state (state I) and a less frequent integrated between-network connectivity state (state II). Moreover, in both these cohorts, older (55-80 years) compared to younger participants (20-35 years) exhibited lower occurrence of and spent less time in state I. Older participants also tended to exhibit more transitions between networks and greater variance in global efficiency. Overall, our cross-cultural replication of age-associated changes in dFC metrics implies that advancing age is robustly associated with a reorganization of dynamic brain activation that favors the use of less functionally specific networks.

The older adult brain is less modular, more integrated, and less efficient at rest: A systematic review of large-scale resting-state functional brain networks in aging

The literature on large-scale resting-state functional brain networks across the adult lifespan was systematically reviewed. Studies published between 1986 and July 2021 were retrieved from PubMed. After reviewing 2938 records, 144 studies were included. Results on 11 network measures were summarized and assessed for certainty of the evidence using a modified GRADE method. The evidence provides high certainty that older adults display reduced within-network and increased between-network functional connectivity. Older adults also show lower segregation, modularity, efficiency and hub function, and decreased lateralization and a posterior to anterior shift at rest. Higher-order functional networks reliably showed age differences, whereas primary sensory and motor networks showed more variable results. The inflection point for network changes is often the third or fourth decade of life. Age effects were found with moderate certainty for within- and between-network altered patterns and speed of dynamic connectivity. Research on within-subject bold variability and connectivity using glucose uptake provides low certainty of age differences but warrants further study. Taken together, these age-related changes may contribute to the cognitive decline often seen in older adults.

Functional connectivity in older adults-the effect of cerebral small vessel disease

Ageing is associated with functional reorganization that is mainly characterized by declining functional connectivity due to general neurodegeneration and increasing incidence of disease. Functional connectivity has been studied across the lifespan; however, there is a paucity of research within the older groups (≥75 years) where neurodegeneration and disease prevalence are at its highest. In this cross-sectional study, we investigated associations between age and functional connectivity and the influence of cerebral small vessel disease (CSVD)-a common age-related morbidity-in 167 community-dwelling older adults aged 75-91 years (mean = 80.3 ± 3.8). Resting-state functional MRI was used to determine functional connectivity within ten standard networks and calculate the whole-brain graph theoretical measures global efficiency and clustering coefficient. CSVD features included white matter hyperintensities, lacunar infarcts, cerebral microbleeds, and atrophy that were assessed in each individual and a composite score was calculated. Both main and interaction effects (age*CSVD features) on functional connectivity were studied. We found stable levels of functional connectivity across the age range. CSVD was not associated with functional connectivity measures. To conclude, our data show that the functional architecture of the brain is relatively unchanged after 75 years of age and not differentially affected by individual levels of vascular pathology.

Associations Between Insulin-Like Growth Factor-1 and Resting-State Functional Connectivity in Cognitively Unimpaired Midlife Adults

BACKGROUND

Insulin-like growth factor (IGF)-1 plays an important role in Alzheimer's disease (AD) pathogenesis and increases disease risk. However, prior research examining IGF-1 levels and brain neural network activity is mixed.

OBJECTIVE

The present study investigated the relationship between IGF-1 levels and 21 neural networks, as measured by functional magnetic resonance imaging (fMRI) in 13,235 UK Biobank participants.

METHODS

Linear mixed models were used to regress IGF-1 against the intrinsic functional connectivity (i.e., degree of network activity) for each neural network. Interactions between IGF-1 and AD risk factors such as Apolipoprotein E4 (APOE4) genotype, sex, AD family history, and age were also tested.

RESULTS

Higher IGF-1 was associated with more network activity in the right Executive Function neural network. IGF-1 interactions with APOE4 or sex implicated motor, primary/extrastriate visual, and executive function related neural networks. Neural network activity trends with increasing IGF-1 were different in different age groups. Higher IGF-1 levels relate to much more network activity in the Sensorimotor Network and Cerebellum Network in early-life participants (40-52 years old), compared with mid-life (52-59 years old) and late-life (59-70 years old) participants.

CONCLUSION

These findings suggest that sex and APOE4 genotype may modify the relationship between IGF-1 and brain network activities related to visual, motor, and cognitive processing. Additionally, IGF-1 may have an age-dependent effect on neural network connectivity.

Interrelating differences in structural and functional connectivity in the older adult's brain

In the normal aging process, the functional connectome restructures and shows a shift from more segregated to more integrated brain networks, which manifests itself in highly different cognitive performances in older adults. Underpinnings of this reorganization are not fully understood, but may be related to age-related differences in structural connectivity, the underlying scaffold for information exchange between regions. The structure-function relationship might be a promising factor to understand the neurobiological sources of interindividual cognitive variability, but remain unclear in older adults. Here, we used diffusion weighted and resting-state functional magnetic resonance imaging as well as cognitive performance data of 573 older subjects from the 1000BRAINS cohort (55-85 years, 287 males) and performed a partial least square regression on 400 regional functional and structural connectivity (FC and SC, respectively) estimates comprising seven resting-state networks. Our aim was to identify FC and SC patterns that are, together with cognitive performance, characteristic of the older adults aging process. Results revealed three different aging profiles prevalent in older adults. FC was found to behave differently depending on the severity of age-related SC deteriorations. A functionally highly interconnected system is associated with a structural connectome that shows only minor age-related decreases. Because this connectivity profile was associated with the most severe age-related cognitive decline, a more interconnected FC system in older adults points to a process of dedifferentiation. Thus, functional network integration appears to increase primarily when SC begins to decline, but this does not appear to mitigate the decline in cognitive performance.

Effects of aging on cognitive and brain inter-network integration patterns underlying usual and dual-task gait performance

Introduction

Aging affects the interplay between cognition and gait performance. Neuroimaging studies reported associations between gait performance and structural measures; however, functional connectivity (FC) analysis of imaging data can help to identify dynamic neural mechanisms underlying optimal performance. Here, we investigated the effects on divergent cognitive and inter-network FC patterns underlying gait performance during usual (UW) and dual-task (DT) walking.

Methods

A total of 115 community-dwelling, healthy participants between 20 and 80 years were enrolled. All participants underwent comprehensive cognitive and gait assessments in two conditions and resting state functional MRI (fMRI) scans. Inter-network FC from motor-related to 6 primary cognitive networks were estimated. Step-wise regression models tested the relationships between gait parameters, inter-network FC, neuropsychological scores, and demographic variables. A threshold of p < 0.05 was adopted for all statistical analyses.

Results

UW was largely associated with FC levels between motor and sustained attention networks. DT performance was associated with inter-network FC between motor and divided attention, and processing speed in the overall group. In young adults, UW was associated with inter-network FC between motor and sustained attention networks. On the other hand, DT performance was associated with cognitive performance, as well as inter-network connectivity between motor and divided attention networks (VAN and SAL). In contrast, the older age group (> 65 years) showed increased integration between motor, dorsal, and ventral attention, as well as default-mode networks, which was negatively associated with UW gait performance. Inverse associations between motor and sustained attention inter-network connectivity and DT performance were observed.

Conclusion

While UW relies on inter-network FC between motor and sustained attention networks, DT performance relies on additional cognitive capacities, increased motor, and executive control network integration. FC analyses demonstrate that the decline in cognitive performance with aging leads to the reliance on additional neural resources to maintain routine walking tasks.

Diet moderates the effect of resting state functional connectivity on cognitive function

Past research suggests modifiable lifestyle factors impact structural and functional measures of brain health, as well as cognitive performance, but no study to date has tested the effect of diet on resting state functional connectivity (rsFC), and its relationship with cognition. The current study tested whether Mediterranean diet (MeDi) moderates the associations between internetwork rsFC and cognitive function. 201 cognitively intact adults 20-80 years old underwent resting state fMRI to measure rsFC among 10 networks, and completed 12 cognitive tasks assessing perceptual speed, fluid reasoning, episodic memory, and vocabulary. Food frequency questionnaires were used to categorize participants into low, moderate, and high MeDi adherence groups. Multivariable linear regressions were used to test associations between MeDi group, task performance, and internetwork rsFC. MeDi group moderated the relationship between rsFC and fluid reasoning for nine of the 10 functional networks' connectivity to all others: higher internetwork rsFC predicted lower fluid reasoning performance in the low MeDi adherence group, but not in moderate and high MeDi groups. Results suggest healthy diet may support cognitive ability despite differences in large-scale network connectivity at rest. Further research is warranted to understand how diet impacts neural processes underlying cognitive function over time.

Alterations in resting-state functional connectivity associated to the age-related decline in time-based prospective memory

Time-based prospective memory (TBPM) is defined as the ability to remember to perform intended actions at a specific time in the future. TBPM is impaired in aging, and this decline has been associated with white-matter alterations within the superior fronto-occipital fasciculus. In the present study, we used resting-state functional magnetic resonance imaging from 22 healthy young (26 ± 5.2 years) and 23 older (63 ± 6.1 years) participants to investigate how age-related alterations in resting-state functional connectivity are related to TBPM performance, and whether these alterations are associated with the white-matter disruptions we have previously observed with diffusion tensor imaging. Whole-brain analyses revealed lower resting-state functional connectivity in older participants compared with younger ones, which in turn correlated with TBPM performance. These correlations were mainly located in the salience network and the parietal part of the frontoparietal network. Our findings suggest that resting-state functional connectivity alterations contribute to the age-related decline in TBPM.

Associations of lifetime concussion history and repetitive head impact exposure with resting-state functional connectivity in former collegiate American football players: An NCAA 15-year follow-up study

The objective of this study was to examine associations of lifetime concussion history (CHx) and an advanced metric of lifetime repetitive head impact exposure with resting-state functional connectivity (rsFC) across the whole-brain and among large-scale functional networks (Default Mode; Dorsal Attention; and Frontoparietal Control) in former collegiate football players. Individuals who completed at least one year of varsity collegiate football were eligible to participate in this observational cohort study (n = 48; aged 36–41 years; 79.2% white/Caucasian; 12.5±4.4 years of football played; all men). Individuals were excluded if they reported history/suspicion of psychotic disorder with active symptoms, contraindications to participation in study procedures (e.g., MRI safety concern), or inability to travel. Each participant provided concussion and football playing histories. Self-reported concussion history was analyzed in two different ways based on prior research: dichotomous “High” (≥3 concussions; n = 28) versus “Low” (<3 concussions; n = 20); and four ordinal categories (0–1 concussion [n = 19]; 2–4 concussions [n = 8]; 5–7 concussions [n = 9]; and ≥8 concussions [n = 12]). The Head Impact Exposure Estimate (HIEE) was calculated from football playing history captured via structured interview. Resting-state fMRI and T1-weighted MRI were acquired and preprocessed using established pipelines. Next, rsFC was calculated using the Seitzman et al., (2020) 300-ROI functional atlas. Whole-brain, within-network, and between-network rsFC were calculated using all ROIs and network-specific ROIs, respectively. Effects of CHx and HIEE on rsFC values were examined using separate multivariable linear regression models, with a-priori α set to 0.05. We observed no statistically significant associations between rsFC outcomes and either CHx or HIEE (ps ≥ .12). Neither CHx nor HIEE were associated with neural signatures that have been observed in studies of typical and pathological aging. While CHx and repetitive head impacts have been associated with changes in brain health in older former athletes, our preliminary results suggest that associations with rsFC may not be present in early midlife former football players.

Normal aging in mice is associated with a global reduction in cortical spectral power and network-specific declines in functional connectivity

Normal aging is associated with a variety of neurologic changes including declines in cognition, memory, and motor activity. These declines correlate with neuronal changes in synaptic structure and function. Degradation of brain network activity and connectivity represents a likely mediator of age-related functional deterioration resulting from these neuronal changes. Human studies have demonstrated both general decreases in spontaneous cortical activity and disruption of cortical networks with aging. Current techniques used to study cerebral network activity are hampered either by limited spatial resolution (e.g. electroencephalography, EEG) or limited temporal resolution (e.g., functional magnetic resonance imaging, fMRI). Here we utilize mesoscale imaging of neuronal activity in Thy1-GCaMP6f mice to characterize neuronal network changes in aging with high spatial resolution across a wide frequency range. We show that while evoked activity is unchanged with aging, spontaneous neuronal activity decreases across a wide frequency range (0.01-4 Hz) involving all regions of the cortex. In contrast to this global reduction in cortical power, we found that aging is associated with functional connectivity (FC) deterioration of select networks including somatomotor, cingulate, and retrosplenial nodes. These changes are corroborated by reductions in homotopic FC and node degree within somatomotor and visual cortices. Finally, we found that whole-cortex delta power and delta band node degree correlate with exploratory activity in young but not aged animals. Together these data suggest that aging is associated with global declines in spontaneous cortical activity and focal deterioration of network connectivity, and that these reductions may be associated with age-related behavioral declines.

Connectome-based predictive models using resting-state fMRI for studying brain aging

Changes in the brain with age can provide useful information regarding an individual's chronological age. studies have suggested that functional connectomes identified via resting-state functional magnetic resonance imaging (fMRI) could be a powerful feature for predicting an individual's age. We applied connectome-based predictive modeling (CPM) to investigate individual chronological age predictions via resting-state fMRI using open-source datasets. The significant feature for age prediction was confirmed in 168 subjects from the Southwest University Adult Lifespan Dataset. The higher contributing nodes for age production included a positive connection from the left inferior parietal sulcus and a negative connection from the right middle temporal sulcus. On the network scale, the subcortical-cerebellum network was the dominant network for age prediction. The generalizability of CPM, which was constructed using the identified features, was verified by applying this model to independent datasets that were randomly selected from the Autism Brain Imaging Data Exchange I and the Open Access Series of Imaging Studies 3. CPM via resting-state fMRI is a potential robust predictor for determining an individual's chronological age from changes in the brain.

Harmonizing functional connectivity reduces scanner effects in community detection

Community detection on graphs constructed from functional magnetic resonance imaging (fMRI) data has led to important insights into brain functional organization. Large studies of brain community structure often include images acquired on multiple scanners across different studies. Differences in scanner can introduce variability into the downstream results, and these differences are often referred to as scanner effects. Such effects have been previously shown to significantly impact common network metrics. In this study, we identify scanner effects in data-driven community detection results and related network metrics. We assess a commonly employed harmonization method and propose new methodology for harmonizing functional connectivity that leverage existing knowledge about network structure as well as patterns of covariance in the data. Finally, we demonstrate that our new methods reduce scanner effects in community structure and network metrics. Our results highlight scanner effects in studies of brain functional organization and provide additional tools to address these unwanted effects. These findings and methods can be incorporated into future functional connectivity studies, potentially preventing spurious findings and improving reliability of results.

Age-related changes of whole-brain dynamics in spontaneous neuronal coactivations

Human brains experience whole-brain anatomic and functional changes throughout the lifespan. Age-related whole-brain network changes have been studied with functional magnetic resonance imaging (fMRI) to determine their low-frequency spatial and temporal characteristics. However, little is known about age-related changes in whole-brain fast dynamics at the scale of neuronal events. The present study investigated age-related whole-brain dynamics in resting-state electroencephalography (EEG) signals from 73 healthy participants from 6 to 65 years old via characterizing transient neuronal coactivations at a resolution of tens of milliseconds. These uncovered transient patterns suggest fluctuating brain states at different energy levels of global activations. Our results indicate that with increasing age, shorter lifetimes and more occurrences were observed in the brain states that show the global high activations and more consecutive visits to the global highest-activation brain state. There were also reduced transitional steps during consecutive visits to the global lowest-activation brain state. These age-related effects suggest reduced stability and increased fluctuations when visiting high-energy brain states and with a bias toward staying low-energy brain states. These age-related whole-brain dynamics changes are further supported by changes observed in classic alpha and beta power, suggesting its promising applications in examining the effect of normal healthy brain aging, brain development, and brain disease.

Age-associated changes to neuronal dynamics involve a disruption of excitatory/inhibitory balance in C. elegans

In the aging brain, many of the alterations underlying cognitive and behavioral decline remain opaque. C. elegans offers a powerful model for aging research, with a simple, well-studied nervous system to further our understanding of the cellular modifications and functional alterations accompanying senescence. We perform multi-neuronal functional imaging across the aged C. elegans nervous system, measuring an age-associated breakdown in system-wide functional organization. At single-cell resolution, we detect shifts in activity dynamics toward higher frequencies. In addition, we measure a specific loss of inhibitory signaling that occurs early in the aging process and alters the systems critical excitatory/inhibitory balance. These effects are recapitulated with mutation of the calcium channel subunit UNC-2/CaV2a. We find that manipulation of inhibitory GABA signaling can partially ameliorate or accelerate the effects of aging. The effects of aging are also partially mitigated by disruption of the insulin signaling pathway, known to increase longevity, or by a reduction of caspase activation. Data from mammals are consistent with our findings, suggesting a conserved shift in the balance of excitatory/inhibitory signaling with age that leads to breakdown in global neuronal dynamics and functional decline.

Functional Connectivity and Complexity in the Phenomenological Model of Mild Cognitive-Impaired Alzheimer's Disease

Background

Functional connectivity and complexity analysis has been discretely studied to understand intricate brain dynamics. The current study investigates the interplay between functional connectivity and complexity using the Kuramoto mean-field model.

Method

Functional connectivity matrices are estimated using the weighted phase lag index and complexity measures through popularly used complexity estimators such as Lempel-Ziv complexity (LZC), Higuchi's fractal dimension (HFD), and fluctuation-based dispersion entropy (FDispEn). Complexity measures are estimated on real and simulated electroencephalogram (EEG) signals of patients with mild cognitive-impaired Alzheimer's disease (MCI-AD) and controls. Complexity measures are further applied to simulated signals generated from lesion-induced connectivity matrix and studied its impact. It is a novel attempt to study the relation between functional connectivity and complexity using a neurocomputational model.

Results

Real EEG signals from patients with MCI-AD exhibited reduced functional connectivity and complexity in anterior and central regions. A simulation study has also displayed significantly reduced regional complexity in the patient group with respect to control. A similar reduction in complexity was further evident in simulation studies with lesion-induced control groups compared with non-lesion-induced control groups.

Conclusion

Taken together, simulation studies demonstrate a positive influence of reduced connectivity in the model imparting a reduced complexity in the EEG signal. The study revealed the presence of a direct relation between functional connectivity and complexity with reduced connectivity, yielding a decreased EEG complexity.

AGING-ASSOCIATED COGNITIVE DECLINE IS REVERSED BY D-SERINE SUPPLEMENTATION

Brain aging is a natural process that involves structural and functional changes that lead to cognitive decline, even in healthy subjects. This detriment has been associated with N-methyl-D-aspartate receptor (NMDAR) hypofunction due to a reduction in the brain levels of D-serine, the endogenous NMDAR co-agonist. However, it is not clear if D-serine supplementation could be used as an intervention to reduce or reverse age-related brain alterations. In the present work, we aimed to analyze the D-serine effect on aging-associated alterations in cellular and large-scale brain systems that could support cognitive flexibility in rats. We found that D-serine supplementation reverts the age-related decline in cognitive flexibility, frontal dendritic spine density, and partially restored large-scale functional connectivity without inducing nephrotoxicity; instead, D-serine restored the thickness of the renal epithelial cells that were affected by age. Our results suggest that D-serine could be used as a therapeutic target to reverse age-related brain alterations.SIGNIFICANT STATEMENTAge-related behavioral changes in cognitive performance occur as a physiological process of aging. Then, it is important to explore possible therapeutics to decrease, retard or reverse aging effects on the brain. NMDA receptor hypofunction contributes to the aging-associated cognitive decline. In the aged brain, there is a reduction in the brain levels of the NMDAR co-agonist, D-Serine. However, it is unclear if chronic D-serine supplementation could revert the age-detriment in brain functions. Our results show that D-serine supplementation reverts the age-associated decrease in cognitive flexibility, functional brain connectivity, and neuronal morphology. Our findings raise the possibility that restoring the brain levels of D-serine could be used as a therapeutic target to recover brain alterations associated with aging.

Resting-state BOLD functional connectivity depends on the heterogeneity of capillary transit times in the human brain A combined lesion and simulation study about the influence of blood flow response timing

Functional connectivity (FC) derived from blood oxygenation level dependent (BOLD) functional magnetic resonance imaging at rest (rs-fMRI), is commonly interpreted as indicator of neuronal connectivity. In a number of brain disorders, however, metabolic, vascular, and hemodynamic impairments can be expected to alter BOLD-FC independently from neuronal activity. By means of a neurovascular coupling (NVC) model of BOLD-FC, we recently demonstrated that aberrant timing of cerebral blood flow (CBF) responses may influence BOLD-FC. In the current work, we support and extend this finding by empirically linking BOLD-FC with capillary transit time heterogeneity (CTH), which we consider as an indicator of delayed and broadened CBF responses. We assessed 28 asymptomatic patients with unilateral high-grade internal carotid artery stenosis (ICAS) as a hemodynamic lesion model with largely preserved neurocognitive functioning and 27 age-matched healthy controls. For each participant, we obtained rs-fMRI, arterial spin labeling, and dynamic susceptibility contrast MRI to study the dependence of left-right homotopic BOLD-FC on local perfusion parameters. Additionally, we investigated the dependency of BOLD-FC on CBF response timing by detailed simulations. Homotopic BOLD-FC was negatively associated with increasing CTH differences between homotopic brain areas. This relation was more pronounced in asymptomatic ICAS patients even after controlling for baseline CBF and relative cerebral blood volume influences. These findings match simulation results that predict an influence of delayed and broadened CBF responses on BOLD-FC. Results demonstrate that increasing CTH differences between homotopic brain areas lead to BOLD-FC reductions. Simulations suggest that CTH increases correspond to broadened and delayed CBF responses to fluctuations in ongoing neuronal activity.

Resting-state functional magnetic resonance imaging signal variations in aging: The role of neural activity

Resting‐state functional magnetic resonance imaging (rs‐fMRI) has been extensively used to study brain aging, but the age effect on the frequency content of the rs‐fMRI signal has scarcely been examined. Moreover, the neuronal implications of such age effects and age–sex interaction remain unclear. In this study, we examined the effects of age and sex on the rs‐fMRI signal frequency using the Leipzig mind–brain–body data set. Over a frequency band of up to 0.3 Hz, we found that the rs‐fMRI fluctuation frequency is higher in the older adults, although the fluctuation amplitude is lower. The rs‐fMRI signal frequency is also higher in men than in women. Both age and sex effects on fMRI frequency vary with the frequency band examined but are not found in the frequency of physiological‐noise components. This higher rs‐fMRI frequency in older adults is not mediated by the electroencephalograph (EEG)‐frequency increase but a likely link between fMRI signal frequency and EEG entropy, which vary with age and sex. Additionally, in different rs‐fMRI frequency bands, the fMRI‐EEG amplitude ratio is higher in young adults. This is the first study to investigate the neuronal contribution to age and sex effects in the frequency dimension of the rs‐fMRI signal and may lead to the development of new, frequency‐based rs‐fMRI metrics. Our study demonstrates that Fourier analysis of the fMRI signal can reveal novel information about aging. Furthermore, fMRI and EEG signals reflect different aspects of age‐ and sex‐related brain differences, but the signal frequency and complexity, instead of amplitude, may hold their link.

Distinct alterations in cerebellar connectivity with substantia nigra and ventral tegmental area in Parkinson's disease

In Parkinson's disease (PD), neurodegeneration of dopaminergic neurons occurs in the midbrain, specifically targeting the substantia nigra (SN), while leaving the ventral tegmental area (VTA) relatively spared in early phases of the disease. Although the SN and VTA are known to be functionally dissociable in healthy adults, it remains unclear how this dissociation is altered in PD. To examine this issue, we performed a whole-brain analysis to compare functional connectivity in PD to healthy adults using resting-state functional magnetic resonance imaging (rs-fMRI) data compiled from three independent datasets. Our analysis showed that across the sample, the SN had greater connectivity with the precuneus, anterior cingulate gyrus, and areas of the occipital cortex, partially replicating our previous work in healthy young adults. Notably, we also found that, in PD, VTA-right cerebellum connectivity was higher than SN-right cerebellum connectivity, whereas the opposite trend occurred in healthy controls. This double dissociation may reflect a compensatory role of the cerebellum in PD and could provide a potential target for future study and treatment.

Cannabis Use and Resting State Functional Connectivity in the Aging Brain

Several lines of evidence suggest that older adults (aged 65+) sharply increased their cannabis use over the last decade, highlighting a need to understand the effects of cannabis in this age group. Pre-clinical models suggest that cannabinoids affect the brain and cognition in an age-dependent fashion, having generally beneficial effects on older animals and deleterious effects on younger ones. However, there is little research on how cannabis affects the brains of older adults or how older adults differ from younger adults who use cannabis. Resting state functional connectivity (rsFC) measures provide sensitive metrics of age-related cognitive decline. Here we compared rsFC in older adults who are either regular users of cannabis or non-users. We found stronger connectivity between sources in the hippocampus and parahippocampal cortex, and targets in the anterior lobes of the cerebellum in older adult cannabis users relative to non-users. A similar pattern of strengthened connectivity between hippocampal and cerebellar structures was also present in 25-35 year old non-users in comparison to 60-88 year old non-users. These findings suggest that future studies should examine both the potential risks of cannabinoids, as well as a potential benefits, on cognition and brain health for older adults.

The Effect of Aging on Brain Glucose Metabolic Connectivity Revealed by [18F]FDG PET-MR and Individual Brain Networks

Contrary to group-based brain connectivity analyses, the aim of this study was to construct individual brain metabolic networks to determine age-related effects on brain metabolic connectivity. Static 40–60 min [¹⁸F]FDG positron emission tomography (PET) images of 67 healthy subjects between 20 and 82 years were acquired with an integrated PET-MR system. Network nodes were defined by brain parcellation using the Schaefer atlas, while connectivity strength between two nodes was determined by comparing the distribution of PET uptake values within each node using a Kullback–Leibler divergence similarity estimation (KLSE). After constructing individual brain networks, a linear and quadratic regression analysis of metabolic connectivity strengths within- and between-networks was performed to model age-dependency. In addition, the age dependency of metrics for network integration (characteristic path length), segregation (clustering coefficient and local efficiency), and centrality (number of hubs) was assessed within the whole brain and within predefined functional subnetworks. Overall, a decrease of metabolic connectivity strength with healthy aging was found within the whole-brain network and several subnetworks except within the somatomotor, limbic, and visual network. The same decrease of metabolic connectivity was found between several networks across the whole-brain network and the functional subnetworks. In terms of network topology, a less integrated and less segregated network was observed with aging, while the distribution and the number of hubs did not change with aging, suggesting that brain metabolic networks are not reorganized during the adult lifespan. In conclusion, using an individual brain metabolic network approach, a decrease in metabolic connectivity strength was observed with healthy aging, both within the whole brain and within several predefined networks. These findings can be used in a diagnostic setting to differentiate between age-related changes in brain metabolic connectivity strength and changes caused by early development of neurodegeneration.

Genetic Influence Underlying Brain Connectivity Phenotype: A Study on Two Age-Specific Cohorts

Background: Human brain structural connectivity is an important imaging quantitative trait for brain development and aging. Mapping the network connectivity to the phenotypic variation provides fundamental insights in understanding the relationship between detailed brain topological architecture, function, and dysfunction. However, the underlying neurobiological mechanism from gene to brain connectome, and to phenotypic outcomes, and whether this mechanism changes over time, remain unclear. Methods: This study analyzes diffusion-weighted imaging data from two age-specific neuroimaging cohorts, extracts structural connectome topological network measures, performs genome-wide association studies of the measures, and examines the causality of genetic influences on phenotypic outcomes mediated via connectivity measures. Results: Our empirical study has yielded several significant findings: 1) It identified genetic makeup underlying structural connectivity changes in the human brain connectome for both age groups. Specifically, it revealed a novel association between the minor allele (G) of rs7937515 and the decreased network segregation measures of the left middle temporal gyrus across young and elderly adults, indicating a consistent genetic effect on brain connectivity across the lifespan. 2) It revealed rs7937515 as a genetic marker for body mass index in young adults but not in elderly adults. 3) It discovered brain network segregation alterations as a potential neuroimaging biomarker for obesity. 4) It demonstrated the hemispheric asymmetry of structural network organization in genetic association analyses and outcome-relevant studies. Discussion: These imaging genetic findings underlying brain connectome warrant further investigation for exploring their potential influences on brain-related complex diseases, given the significant involvement of altered connectivity in neurological, psychiatric and physical disorders.

Network controllability mediates the relationship between rigid structure and flexible dynamics

Precisely how the anatomical structure of the brain supports a wide range of complex functions remains a question of marked importance in both basic and clinical neuroscience. Progress has been hampered by the lack of theoretical frameworks explaining how a structural network of relatively rigid interareal connections can produce a diverse repertoire of functional neural dynamics. Here, we address this gap by positing that the brain's structural network architecture determines the set of accessible functional connectivity patterns according to predictions of network control theory. In a large developmental cohort of 823 youths aged 8 to 23 years, we found that the flexibility of a brain region's functional connectivity was positively correlated with the proportion of its structural links extending to different cognitive systems. Notably, this relationship was mediated by nodes' boundary controllability, suggesting that a region's strategic location on the boundaries of modules may underpin the capacity to integrate information across different cognitive processes. Broadly, our study provides a mechanistic framework that illustrates how temporal flexibility observed in functional networks may be mediated by the controllability of the underlying structural connectivity.