Selective vulnerability related to aging in large-scale resting brain networks

Higher-Order Intrinsic Brain Network Trajectories After Antipsychotic Treatment in Medication-Naïve Patients With First-Episode Psychosis

BACKGROUND

Intrinsic brain network connectivity is already altered in first-episode psychosis (FEP), but the longitudinal trajectories of network connectivity, especially in response to antipsychotic treatment, remain poorly understood. The goal of this study was to investigate how antipsychotic medications affect higher-order intrinsic brain network connectivity in FEP.

METHODS

Data from 87 antipsychotic medication-naïve patients with FEP and 87 healthy control participants were used. Medication-naïve patients received antipsychotic treatment for 16 weeks. Resting-state functional connectivity (FC) of the default mode, salience, dorsal attention, and executive control networks were assessed prior to treatment and at 6 and 16 weeks after treatment. We evaluated baseline and FC changes using linear mixed models to test group × time interactions within each network. Associations between FC changes after 16 weeks and response to treatment were also evaluated.

RESULTS

Prior to treatment, significant group differences in all networks were found. However, significant trajectory changes in FC were found only in the default mode and executive control networks. Changes in FC in these networks were associated with treatment response. Several sensitivity analyses showed a consistent normalization of executive control network FC in response to antipsychotic treatment.

CONCLUSIONS

Here, we found that alterations in intrinsic brain network FC were not only alleviated with antipsychotic treatment, but the extent of this normalization was also associated with the degree of reduction in symptom severity. Taken together, our data suggest modulation of intrinsic brain network connectivity (mainly frontoparietal connectivity) as a mechanism underlying antipsychotic treatment response in FEP.

The influence of accelerated brain aging on coactivation pattern dynamics in Parkinson's disease

Aging is widely acknowledged as the primary risk factor for brain degeneration, with Parkinson's disease (PD) tending to follow accelerated aging trajectories. We aim to investigate the impact of structural brain aging on the temporal dynamics of a large-scale functional network in PD. We enrolled 62 PD patients and 32 healthy controls (HCs). The level of brain aging was determined by calculating global and local brain age gap estimates (G-brainAGE and L-brainAGE) from structural images. The neural network activity of the whole brain was captured by identifying coactivation patterns (CAPs) from resting-state functional images. Intergroup differences were assessed using the general linear model. Subsequently, a spatial correlation analysis between the L-brainAGE difference map and CAPs was conducted to uncover the anatomical underpinnings of functional alterations. Compared to HCs (-3.73 years), G-brainAGE was significantly higher in PD patients (+1.93 years), who also exhibited widespread elevation in L-brainAGE. G-brainAGE was correlated with disease severity and duration. PD patients spent less time in CAPs involving activated default mode and the fronto-parietal network (DMN-FPN), as well as the sensorimotor and salience network (SMN-SN), and had a reduced transition frequency from other CAPs to the DMN-FPN and SMN-SN CAPs. Furthermore, the pattern of localized brain age acceleration showed spatial similarities with the SMN-SN CAP. Accelerated structural brain aging in PD adversely affects brain function, manifesting as dysregulated brain network dynamics. These findings provide insights into the neuropathological mechanisms underlying neurodegenerative diseases and imply the possibility of interventions for modifying PD progression by slowing the brain aging process.

Higher handgrip strength is linked to higher salience ventral attention functional network segregation in older adults

Converging evidence suggests that handgrip strength is linked to cognition in older adults, and this may be subserved by shared age-related changes in brain function and structure. However, the interplay among handgrip strength, brain functional connectivity, and cognitive function remains poorly elucidated. Hence, our study sought to examine these relationships in 148 community-dwelling older adults. Specifically, we examined functional segregation, a measure of functional brain organization sensitive to ageing and cognitive decline, and its associations with handgrip strength and cognitive function. We showed that higher handgrip strength was related to better processing speed, attention, and global cognition. Further, higher handgrip strength was associated with higher segregation of the salience/ventral attention network, driven particularly by higher salience/ventral attention intra-network functional connectivity of the right anterior insula to the left posterior insula/frontal operculum and right midcingulate/medial parietal cortex. Importantly, these handgrip strength-related inter-individual differences in salience/ventral attention network functional connectivity were linked to cognitive function, as revealed by functional decoding and brain-cognition association analyses. Our findings thus highlight the importance of the salience/ventral attention network in handgrip strength and cognition, and suggest that inter-individual differences in salience/ventral attention network segregation and intra-network connectivity could underpin the handgrip strength-cognition relationship in older adults.

Comparing data-driven physiological denoising approaches for resting-state fMRI: implications for the study of aging

Introduction

Physiological nuisance contributions by cardiac and respiratory signals have a significant impact on resting-state fMRI data quality. As these physiological signals are often not recorded, data-driven denoising methods are commonly used to estimate and remove physiological noise from fMRI data. To investigate the efficacy of these denoising methods, one of the first steps is to accurately capture the cardiac and respiratory signals, which requires acquiring fMRI data with high temporal resolution.

Methods

In this study, we used such high-temporal resolution fMRI data to evaluate the effectiveness of several data-driven denoising methods, including global-signal regression (GSR), white matter and cerebrospinal fluid regression (WM-CSF), anatomical (aCompCor) and temporal CompCor (tCompCor), ICA-AROMA. Our analysis focused on the consequence of changes in low-frequency, cardiac and respiratory signal power, as well as age-related differences in terms of functional connectivity (fcMRI).

Results

Our results confirm that the ICA-AROMA and GSR removed the most physiological noise but also more low-frequency signals. These methods are also associated with substantially lower age-related fcMRI differences. On the other hand, aCompCor and tCompCor appear to be better at removing high-frequency physiological signals but not low-frequency signal power. These methods are also associated with relatively higher age-related fcMRI differences, whether driven by neuronal signal or residual artifact. These results were reproduced in data downsampled to represent conventional fMRI sampling frequency. Lastly, methods differ in performance depending on the age group.

Discussion

While this study cautions direct comparisons of fcMRI results based on different denoising methods in the study of aging, it also enhances the understanding of different denoising methods in broader fcMRI applications.

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.

The characteristics of glucose metabolism and functional connectivity in posterior default network during nondemented aging: relationship with executive function performance

BACKGROUND

Understanding the characteristics of intrinsic connectivity networks (ICNs) in terms of both glucose metabolism and functional connectivity (FC) is important for revealing cognitive aging and neurodegeneration, but the relationships between these two aspects during aging has not been well established in older adults.

OBJECTIVE

This study is to assess the relationship between age-related glucose metabolism and FC in key ICNs, and their direct or indirect effects on cognitive deficits in older adults.

METHODS

We estimated the individual-level standard uptake value ratio (SUVr) and FC of eleven ICNs in 59 cognitively unimpaired older adults, then analyzed the associations of SUVr and FC of each ICN and their relationships with cognitive performance.

RESULTS

The results showed both the SUVr and FC in the posterior default mode network (pDMN) had a significant decline with age, and the association between them was also significant. Moreover, both decline of metabolism and FC in the pDMN were significantly correlated with executive function decline. Finally, mediation analysis revealed the glucose metabolism mediated the FC decline with age and FC mediated the executive function deficits.

CONCLUSIONS

Our findings indicated that covariance between glucose metabolism and FC in the pDMN is one of the main routes that contributes to age-related executive function decline.

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.

Longitudinal resting-state functional connectivity and regional brain atrophy-based biomarkers of preclinical cognitive impairment in healthy old adults

BACKGROUND

Intervention against age-related neurodegenerative diseases may be difficult once extensive structural and functional deteriorations have already occurred in the brain.

AIM

Investigating 6-year longitudinal changes and implications of regional brain atrophy and functional connectivity in the triple-network model as biomarkers of preclinical cognitive impairment in healthy aging.

METHODS

We acquired longitudinal cognitive scores and magnetic resonance imaging (MRI) data from 74 healthy old adults. Resting-state functional MRI (rs-fMRI) analysis was conducted using FSL6.0.1 to examine functional connectivity changes and regional brain morphometries were quantified using FreeSurfer5.3. Finally, we cross-validated and compared two support vector machine (SVM) regression models to predict future 6-year cognition score from the baseline regional brain atrophy and resting-state functional connectivity (rs-FC) measures.

RESULTS

After a 6-year follow-up, our results (P < 0.05-corrected) indicated significant connectivity reduction within all the three brain networks, significant differences in regional brain volumes and cortical thickness. We also observed significant improvement in episodic memory and significant decline in executive functions. Finally, comparing the two models, we observed that regional brain atrophy predictors were more efficient in approximating future 6-year cognitive scores (R = 0.756, P < 0.0001) than rs-FC predictors (R = 0.6, P < 0.0001).

CONCLUSION

This study used longitudinal data to keep subject variability low and to increase the validity of the results. We demonstrated significant changes in structural and functional MRI over 6 years. Our findings present a potential neuroimaging-based biomarker to detect cognitive impairment and prevent risks of neurodegenerative diseases in healthy old adults.

Still Wanting to Win: Reward System Stability in Healthy Aging

Healthy aging is accompanied by multi-faceted changes. Especially within the brain, healthy aging exerts substantial impetus on core parts of cognitive and motivational networks. Rewards comprise basic needs, such as food, sleep, and social contact. Thus, a functionally intact reward system remains indispensable for elderly people to cope with everyday life and adapt to their changing environment. Research shows that reward system function is better preserved in the elderly than most cognitive functions. To investigate the compensatory mechanisms providing reward system stability in aging, we employed a well-established reward paradigm (Monetary Incentive Delay Task) in groups of young and old participants while undergoing EEG measurement. As a new approach, we applied EEG connectivity analyses to assess cortical reward-related network connectivity. At the behavioral level, our results confirm that the function of the reward system is preserved in old age. The mechanisms identified for maintaining reward system function in old age do not fit into previously described models of cognitive aging. Overall, older adults exhibit lower reward-related connectivity modulation, higher reliance on posterior and right-lateralized brain areas than younger adults, and connectivity modulation in the opposite direction than younger adults, with usually greater connectivity during non-reward compared to reward conditions. We believe that the reward system has unique compensatory mechanisms distinct from other cognitive functions, probably due to its etymologically very early origin. In summary, this study provides important new insights into cortical reward network connectivity in healthy aging.

Exploring attention in the bilingualism continuum: A resting-state functional connectivity study

This study explores the effects of bilingualism on the subcomponents of attention using resting state functional connectivity analysis (rsFC). Unlike previous studies, measures of bilingualism - L2 Age of Acquisition (AOA), L2 exposure, and L2 proficiency - were examined along a continuum to study attentional mechanisms using rsFC instead of dichotomizing them. 20 seed regions were pre-selected for the three subcomponents of attention. The results showed a positive association between behavioral performance and rsFC for the seeds in alerting and orienting network; this was not true for the seeds in the executive control network. Secondly, rsFC for attention networks varied with different levels of bilingualism. The objective measures of bilingualism modulate all three attention networks. While the subjective measures such as L2 AOA modulates specific attention network. Thus, language performance in contrast to self-reported information, as a measure of bilingualism, has a greater potential to tap into the role of bilingualism in attentional processes.

Cerebral topography of vesicular cholinergic transporter changes in neurologically intact adults: A [18F]FEOBV PET study

Acetylcholine plays a major role in brain cognitive and motor functions with regional cholinergic terminal loss common in several neurodegenerative disorders. We describe age-related declines of regional cholinergic neuron terminal density in vivo using the positron emission tomography (PET) ligand [¹⁸F](–)5-Fluoroethoxybenzovesamicol ([¹⁸F] FEOBV), a vesamicol analogue selectively binding to the vesicular acetylcholine transporter (VAChT). A total of 42 subjects without clinical evidence of neurologic disease (mean 50.55 [range 20–80] years, 24 Male/18 Female) underwent [¹⁸F]FEOBV brain PET imaging. We used SPM based voxel-wise statistical analysis to perform whole brain voxel-based parametric analysis (family-wise error corrected, FWE) and to also extract the most significant clusters of regions correlating with aging with gender as nuisance variable. Age-related VAChT binding reductions were found in primary sensorimotor cortex, visual cortex, caudate nucleus, anterior to mid-cingulum, bilateral insula, para-hippocampus, hippocampus, anterior temporal lobes/amygdala, dorsomedial thalamus, metathalamus, and cerebellum (gender and FWE-corrected, P < 0.05). These findings show a specific topographic pattern of regional vulnerability of cholinergic nerve terminals across multiple cholinergic systems accompanying aging.

Alterations in Brain Network Organization in Adults With Obesity as Compared With Healthy-Weight Individuals and Seniors

OBJECTIVE

Life expectancy and obesity rates have drastically increased in recent years. An unhealthy weight is related to long-lasting medical disorders that might compromise the normal course of aging. The aim of the current study of brain connectivity patterns was to examine whether adults with obesity would show signs of premature aging, such as lower segregation, in large-scale networks.

METHODS

Participants with obesity (n = 30, mean age = 32.8 ± 5.68 years) were compared with healthy-weight controls (n = 33, mean age = 30.9 ± 6.24 years) and senior participants who were stroke-free and without dementia (n = 30, mean age = 67.1 ± 6.65 years) using resting-state magnetic resonance imaging and graph theory metrics (i.e., small-world index, clustering coefficient, characteristic path length, and degree).

RESULTS

Contrary to our hypothesis, participants with obesity exhibited a higher clustering coefficient compared with senior participants (t = 5.06, p < .001, d = 1.23, 95% CIbca = 0.64 to 1.88). Participants with obesity also showed lower global degree relative to seniors (t = -2.98, p = .014, d = -0.77, 95% CIbca = -1.26 to -0.26) and healthy-weight controls (t = -2.92, p = .019, d = -0.72, 95% CIbca = -1.19 to -0.25). Regional degree alterations in this group were present in several functional networks.

CONCLUSIONS

Participants with obesity displayed greater network clustering than did seniors and also had lower degree compared with seniors and individuals with normal weight, which is not consistent with the notion that obesity is associated with premature aging of the brain. Although the cross-sectional nature of the study precludes causal inference, the overly clustered network patterns in obese participants could be relevant to age-related changes in brain function because regular networks might be less resilient and metabolically inefficient.

Strategies and cognitive reserve to preserve lexical production in aging

In the absence of any neuropsychiatric condition, older adults may show declining performance in several cognitive processes and among them, in retrieving and producing words, reflected in slower responses and even reduced accuracy compared to younger adults. To overcome this difficulty, healthy older adults implement compensatory strategies, which are the focus of this paper. We provide a review of mainstream findings on deficient mechanisms and possible neurocognitive strategies used by older adults to overcome the deleterious effects of age on lexical production. Moreover, we present findings on genetic and lifestyle factors that might either be protective or risk factors of cognitive impairment in advanced age. We propose that "aging-modulating factors" (AMF) can be modified, offering prevention opportunities against aging effects. Based on our review and this proposition, we introduce an integrative neurocognitive model of mechanisms and compensatory strategies for lexical production in older adults (entitled Lexical Access and Retrieval in Aging, LARA). The main hypothesis defended in LARA is that cognitive aging evolves heterogeneously and involves complementary domain-general and domain-specific mechanisms, with substantial inter-individual variability, reflected at behavioral, cognitive, and brain levels. Furthermore, we argue that the ability to compensate for the effect of cognitive aging depends on the amount of reserve specific to each individual which is, in turn, modulated by the AMF. Our conclusion is that a variety of mechanisms and compensatory strategies coexist in the same individual to oppose the effect of age. The role of reserve is pivotal for a successful coping with age-related changes and future research should continue to explore the modulating role of AMF.

Resting-state networks in the course of aging-differential insights from studies across the lifespan vs. amongst the old

Resting-state functional connectivity (RSFC) has widely been used to examine reorganization of functional brain networks during normal aging. The extraction of generalizable age trends, however, is hampered by differences in methodological approaches, study designs and sample characteristics. Distinct age ranges of study samples thereby represent an important aspect between studies especially due to the increase in inter-individual variability over the lifespan. The current review focuses on comparing age-related differences in RSFC in the course of the whole adult lifespan versus later decades of life. We summarize and compare studies assessing age-related differences in within- and between-network RSFC of major resting-state brain networks. Differential effects of the factor age on resting-state networks can be identified when comparing studies focusing on younger versus older adults with studies investigating effects within the older adult population. These differential effects pertain to higher order and primary processing resting-state networks to a varying extent. Especially during later decades of life, other factors beyond age might come into play to understand the high inter-individual variability in RSFC.

Accrual of functional redundancy along the lifespan and its effects on cognition

Despite the necessity to understand how the brain endures the initial stages of age-associated cognitive decline, no brain mechanism has been quantitatively specified to date. The brain may withstand the effects of cognitive aging through redundancy, a design feature in engineered and biological systems, which entails the presence of substitute elements to protect it against failure. Here, we investigated the relationship between functional network redundancy and age over the human lifespan and their interaction with cognition, analyzing resting-state functional MRI images and cognitive measures from 579 subjects. Network-wide redundancy was significantly associated with age, showing a stronger link with age than other major topological measures, presenting a pattern of accumulation followed by old-age decline. Critically, redundancy significantly mediated the association between age and executive function, with lower anti-correlation between age and cognition in subjects with high redundancy. The results suggest that functional redundancy accrues throughout the lifespan, mitigating the effects of age on cognition.

Modulation of OSCP mitigates mitochondrial and synaptic deficits in a mouse model of Alzheimer's pathology

Synaptic failure underlies cognitive impairment in Alzheimer's disease (AD). Cumulative evidence suggests a strong link between mitochondrial dysfunction and synaptic deficits in AD. We previously found that oligomycin-sensitivity-conferring protein (OSCP) dysfunction produces pronounced neuronal mitochondrial defects in AD brains and a mouse model of AD pathology (5xFAD mice). Here, we prevented OSCP dysfunction by overexpressing OSCP in 5xFAD mouse neurons in vivo (Thy-1 OSCP/5xFAD mice). This approach protected OSCP expression and reduced interaction of amyloid-beta (Aβ) with membrane-bound OSCP. OSCP overexpression also alleviated F1Fo ATP synthase deregulation and preserved mitochondrial function. Moreover, OSCP modulation conferred resistance to Aβ-mediated defects in axonal mitochondrial dynamics and motility. Consistent with preserved neuronal mitochondrial function, OSCP overexpression ameliorated synaptic injury in 5xFAD mice as demonstrated by preserved synaptic density, reduced complement-dependent synapse elimination, and improved synaptic transmission, leading to preserved spatial learning and memory. Taken together, our findings show the consequences of OSCP dysfunction in the development of synaptic stress in AD-related conditions and implicate OSCP modulation as a potential therapeutic strategy.

A Longitudinal Study of Changes in Resting-State Functional Magnetic Resonance Imaging Functional Connectivity Networks During Healthy Aging

Background: Vast increases in life expectancy over the last century have led to shifts in population demographics and the emergence of a largely aged population, globally. This has led to a need to understand neurobiological changes associated with healthy aging. Studies on age-related changes in functional connectivity networks have largely been cross-sectional and focused on the default mode network (DMN). The current study investigated longitudinal changes in functional connectivity in multiple resting-state networks over 4 years of aging in cognitively normal older adults. Methods: Resting-state functional magnetic resonance imaging scans from older adults (n = 16) who maintained "cognitive normal" status over 4 years were retrieved at baseline and follow-up from the Alzheimer's Disease Neuroimaging Initiative database. A seed-based approach was executed in Functional MRI of the Brain Software Library (FSL) to examine significant changes in functional connectivity within the DMN, frontoparietal network (FPN), and salience network (SN) within subjects over time. Results: Results indicated significantly (p < 0.05, corrected) reduced functional connectivity in the FPN and SN, but not in the DMN at year 4 compared with baseline in older adults who were cognitively stable. Conclusions: The current study highlights the importance of a longitudinal approach for understanding changes in functional connectivity. The findings also underscore the need to examine multiple networks within the same participants, given that changes were apparent in the FPN and SN but not in the DMN. Future studies should also examine changes in internetwork connectivity as well as shifts in structural connectivity over time. Impact statement Investigations of age-related changes in functional connectivity have largely been cross-sectional and focused on the default mode network (DMN). The current study examined the DMN as well as the frontoparietal network (FN) and salience network (SN), in a group of healthy aging adults over four years. The results revealed decreased functional connectivity over time, in the FN and SN, but not the DMN. These findings provide insights about the healthy aging brain. They also underscore the need to broaden the scope of functional connectivity analyses beyond the DMN and highlight the use of longitudinal methods.

Age-Related Decreases in Interhemispheric Resting-State Functional Connectivity and Their Relationship With Executive Function

Age-related alterations of functional brain networks contribute to cognitive decline. Current theories indicate that age-related intrinsic brain functional reorganization may be a critical marker of cognitive aging. Yet, little is known about how intrinsic interhemispheric functional connectivity changes with age in adults, and how this relates to critical executive functions. To address this, we examined voxel-mirrored homotopic connectivity (VMHC), a metric that quantifies interhemispheric communication, in 93 healthy volunteers (age range: 19-85) with executive function assessment using the Delis-Kaplan Executive Function System (D-KEFS) scales. Resting functional MRI data were analyzed to assess VMHC, and then a multiple linear regression model was employed to evaluate the relationship between age and the whole-brain VMHC. We observed age-related reductions in VMHC of ventromedial prefrontal cortex (vmPFC) and hippocampus in the medial temporal lobe subsystem, dorsal anterior cingulate cortex and insula in salience network, and inferior parietal lobule in frontoparietal control network. Performance on the color-word inhibition task was associated with VMHC of vmPFC and insula, and VMHC of vmPFC mediated the relationship between age and CWIT inhibition reaction times. The percent ratio of correct design scores in design fluency test correlated positively with VMHC of the inferior parietal lobule. The current study suggests that brain interhemispheric functional alterations may be a promising new avenue for understanding age-related cognitive decline.

A GICA-TVGL framework to study sex differences in resting state fMRI dynamic connectivity

BACKGROUND

Functional magnetic resonance imaging (fMRI) has been implemented widely to study brain connectivity. In particular, time-varying connectivity analysis has emerged as an important measure to uncover essential knowledge within the network. On the other hand, independent component analysis (ICA) has served as a powerful tool to preprocess fMRI data before performing network analysis. Together, they may lead to novel findings.

METHODS

We propose a new framework (GICA-TVGL) that combines group ICA (GICA) with time-varying graphical LASSO (TVGL) to improve the power of analyzing functional connectivity (FNC) changes, which is then applied for neuro-developmental study. To investigate the performance of our proposed approach, we apply it to capture dynamic FNC using both the Philadelphia Neurodevelopmental Cohort (PNC) and the Pediatric Imaging, Neurocognition, and Genetics (PING) datasets.

RESULTS

Our results indicate that females and males in young adult group possess substantial difference related to visual network. In addition, some other consistent conclusions have been reached by using these two datasets. Furthermore, the GICA-TVGL model indicated that females had a higher probability to stay in a stable state. Males had a higher tendency to remain in a globally disconnected mode.

COMPARISON WITH EXISTING METHOD

The performance of sliding window approach is largely affected by the window size selection. In addition, it also assumes temporal locality hypothesis.

CONCLUSION

Our proposed framework provides a feasible method to investigate brain dynamics and has the potential to become a widely used tool in neuroimaging studies.

Interaction of Cannabis Use and Aging: From Molecule to Mind

Given the aging Baby Boomer generation, changes in cannabis legislation, and the growing acknowledgment of cannabis for its therapeutic potential, it is predicted that cannabis use in the older population will escalate. It is, therefore, important to determine the interaction between the effects of cannabis and aging. The aim of this report is to describe the link between cannabis use and the aging brain. Our review of the literature found few and inconsistent empirical studies that directly address the impact of cannabis use on the aging brain. However, research focused on long-term cannabis use points toward cumulative effects on multimodal systems in the brain that are similarly affected during aging. Specifically, the effects of cannabis and aging converge on overlapping networks in the endocannabinoid, opioid, and dopamine systems that may affect functional decline particularly in the hippocampus and prefrontal cortex, which are critical areas for memory and executive functioning. To conclude, despite the limited current knowledge on the potential interactive effects between cannabis and aging, evidence from the literature suggests that cannabis and aging effects are concurrently present across several neurotransmitter systems. There is a great need for future research to directly test the interactions between cannabis and aging.

Age Group Differences in Executive Network Functional Connectivity and Relationships with Social Behavior in Men with Autism Spectrum Disorder

BACKGROUND

Research suggests adults with autism spectrum disorder (ASD) may use executive functions to compensate for social difficulties. Given hallmark age-related declines in executive functioning and the executive brain network in normal aging, there is concern that older adults with ASD may experience further declines in social functioning as they age. In a male-only sample, we hypothesized: 1) older adults with ASD would demonstrate greater ASD-related social behavior than young adults with ASD, 2) adults with ASD would demonstrate a greater age group reduction in connectivity of the executive brain network than neurotypical (NT) adults, and 3) that behavioral and neural mechanisms of executive functioning would predict ASD-related social difficulties in adults with ASD.

METHODS

Participants were a cross-sectional sample of non-intellectually disabled young (ages 18-25) and middle-aged (ages 40-70) adult men with ASD and NT development (young adult ASD: n=24; middle-age ASD: n=25; young adult NT: n=15; middle-age NT: n=21). We assessed ASD-related social behavior via the self-report Social Responsiveness Scale-2 (SRS-2) Total Score, with exploratory analyses of the Social Cognition Subscale. We assessed neural executive function via connectivity of the resting-state executive network (EN) as measured by independent component analysis. Correlations were investigated between SRS-2 Total Scores (with exploratory analyses of the Social Cognition Subscale), EN functional connectivity of the dorsolateral prefrontal cortex (dlPFC), and a behavioral measure of executive function, Tower of London (ToL) Total Moves.

RESULTS

We did not confirm a significant age group difference for adults with ASD on the SRS-2 Total Score; however, exploratory analysis revealed middle-age men with ASD had higher scores on the SRS-2 Social Cognition Subscale than young adult men with ASD. Exacerbated age group reductions in EN functional connectivity were confirmed (left dlPFC) in men with ASD compared to NT, such that older adults with ASD demonstrated the greatest levels of hypoconnectivity. A significant correlation was confirmed between dlPFC connectivity and the SRS-2 Total Score in middle-age men with ASD, but not young adult men with ASD. Furthermore, exploratory analysis revealed a significant correlation with the SRS-2 Social Cognition Subscale for young and middle-aged ASD groups and ToL Total Moves.

CONCLUSIONS

Our findings suggest that ASD-related difficulties in social cognition and EN hypoconnectivity may get worse with age in men with ASD and is related to executive functioning. Further, exacerbated EN hypoconnectivity associated with older age in ASD may be a mechanism of increased ASD-related social cognition difficulties in older adults with ASD. Given the cross-sectional nature of this sample, longitudinal replication is needed.

Age-Related Atrophy and Compensatory Neural Networks in Reading Comprehension

OBJECTIVES

Despite changes to brain integrity with aging, some functions like basic language processes remain remarkably preserved. One theory for the maintenance of function in light of age-related brain atrophy is the engagement of compensatory brain networks. This study examined age-related changes in the neural networks recruited for simple language comprehension.

METHODS

Sixty-five adults (native English-speaking, right-handed, and cognitively normal) aged 17-85 years underwent a functional magnetic resonance imaging (fMRI) reading paradigm and structural scanning. The fMRI data were analyzed using independent component analysis to derive brain networks associated with reading comprehension.

RESULTS

Two typical frontotemporal language networks were identified, and these networks remained relatively stable across the wide age range. In contrast, three attention-related networks showed increased activation with increasing age. Furthermore, the increased recruitment of a dorsal attention network was negatively correlated to gray matter thickness in temporal regions, whereas an anterior frontoparietal network was positively correlated to gray matter thickness in insular regions.

CONCLUSIONS

We found evidence that older adults can exert increased effort and recruit additional attentional resources to maintain their reading abilities in light of increased cortical atrophy.

Longitudinal Changes in the Cerebral Cortex Functional Organization of Healthy Elderly

Healthy aging is accompanied by disruptions in the functional modular organization of the human brain. Cross-sectional studies have shown age-related reductions in the functional segregation and distinctiveness of brain networks. However, less is known about the longitudinal changes in brain functional modular organization and their associations with aging-related cognitive decline. We examined age- and aging-related changes in functional architecture of the cerebral cortex using a dataset comprising a cross-sectional healthy young cohort of 57 individuals (mean ± SD age, 23.71 ± 3.61 years, 22 males) and a longitudinal healthy elderly cohort of 72 individuals (mean ± baseline age, 68.22 ± 5.80 years, 39 males) with 2-3 time points (18-24 months apart) of task-free fMRI data. We found both cross-sectional (elderly vs young) and longitudinal (in elderly) global decreases in network segregation (decreased local efficiency), integration (decreased global efficiency), and module distinctiveness (increased participation coefficient and decreased system segregation). At the modular level, whereas cross-sectional analyses revealed higher participation coefficient across all modules in the elderly compared with young participants, longitudinal analyses revealed focal longitudinal participation coefficient increases in three higher-order cognitive modules: control network, default mode network, and salience/ventral attention network. Cross-sectionally, elderly participants also showed worse attention performance with lower local efficiency and higher mean participation coefficient, and worse global cognitive performance with higher participation coefficient in the dorsal attention/control network. These findings suggest that healthy aging is associated with whole-brain connectome-wide changes in the functional modular organization of the brain, accompanied by loss of functional segregation, particularly in higher-order cognitive networks.SIGNIFICANCE STATEMENT Cross-sectional studies have demonstrated age-related reductions in the functional segregation and distinctiveness of brain networks. However, longitudinal aging-related changes in brain functional modular architecture and their links to cognitive decline remain relatively understudied. Using graph theoretical and community detection approaches to study task-free functional network changes in a cross-sectional young and longitudinal healthy elderly cohort, we showed that aging was associated with global declines in network segregation, integration, and module distinctiveness, and specific declines in distinctiveness of higher-order cognitive networks. Further, such functional network deterioration was associated with poorer cognitive performance cross-sectionally. Our findings suggest that healthy aging is associated with system-level changes in brain functional modular organization, accompanied by functional segregation loss particularly in higher-order networks specialized for cognition.

Dissociable Effects of Aging on Salience Subnetwork Connectivity Mediate Age-Related Changes in Executive Function and Affect

Aging is associated with both changes in affective experience and attention. An intrinsic brain network subserving these functions, the salience network, has not shown clear evidence of a corresponding age-related change. We propose a solution to this discrepancy: that aging differentially affects the connectivity of two dissociated subsystems of the salience network identified in our prior research (Touroutoglou et al., 2012). We examined the age-related changes in intrinsic connectivity between a dorsal and a ventral salience subsystem in a sample of 111 participants ranging in age from 18 years to 81 years old. We predicted that connectivity within the ventral subsystem is relatively preserved with age, while connectivity in the dorsal subsystem declines. Our findings showed that the connectivity within the ventral subsystem was not only preserved but it actually increased with age, whereas the connectivity within the dorsal subsystem decreased with age. Furthermore, age-related increase in arousal experience was partially mediated by age-related increases in ventral salience subsystem, whereas age-related decline in executive function was fully mediated by age-related decreases in dorsal salience subsystem connectivity. These findings explain previously conflicting results on age-related changes in the salience network, and suggest a mechanism for relatively preserved affective function in the elderly.

Capturing Dynamic Connectivity from Resting State fMRI using Time-Varying Graphical Lasso

Functional connectivity (FC) within the human brain evaluated through functional magnetic resonance imaging (fMRI) data has attracted increasing attention and has been employed to study the development of the brain or health conditions of the brain. Many different approaches have been proposed to estimate FC from fMRI data, whereas many of them rely on an implicit assumption that functional connectivity should be static throughout the fMRI scan session. Recently, the fMRI community has realized the limitation of assuming static connectivity and dynamic approaches are more prominent in the resting state fMRI (rs-fMRI) analysis. The sliding window technique has been widely used in many studies to capture network dynamics, but has a number of limitations. In this study, we apply a time-varying graphical lasso (TVGL) model, an extension from the traditional graphical lasso, to address the challenge, which can greatly improve the estimation of FC. The performance of estimating dynamic FC is evaluated with the TVGL through both simulated experiments and real rs-fMRI data from the Philadelphia Neurodevelopmental Cohort (PNC) project. Improved performance is achieved over the sliding window technique. In particular, group differences and transition behaviours between young adults and children are investigated using the estimated dynamic connectivity networks, which help us to better unveil the mechanisms underlying the evolution of the brain over time.

Cognitive Improvement in Healthy Older Adults Can Parallel That of Younger Adults Following Lifestyle Modification: Support for Cognitive Reserve During Aging

Executive function was assayed following a nutritional supplementation in healthy adults using the Trail Making Test. Comparison with published normative scores demonstrated that cohorts from 35-74 years of age displayed similar relative improvement compared to their own baseline performance. These findings support early, pro-active lifestyle modifications to maintain cognitive performance during aging and further demonstrate the persistence of cognitive reserve in healthy older adults.

"Walking" through the sensory, cognitive, and temporal degradations of healthy aging

As we age, there is a wide range of changes in motor, sensory, cognitive, and temporal processing due to alterations in the functioning of the central nervous and musculoskeletal systems. Specifically, aging is associated with degradations in gait; altered processing of the individual sensory systems; modifications in executive control, memory, and attention; and changes in temporal processing. These age-related alterations are often inter-related and have been suggested to result from shared neural substrates. Additionally, the overlap between these brain areas and those controlling walking raises the possibility of facilitating performance in several tasks by introducing protocols that can efficiently target all four domains. Attempts to counteract these negative effects of normal aging have been focusing on research to prevent falls and/or enhance cognitive processes, while ignoring the potential multisensory benefits accompanying old age. Research shows that the aging brain tends to increasingly rely on multisensory integration to compensate for degradations in individual sensory systems and for altered neural functioning. This review covers the age-related changes in the above-mentioned domains and the potential to exploit the benefits associated with multisensory integration in aging so as to improve one's mobility and enhance sensory, cognitive, and temporal processing.

The electrophysiological connectome is maintained in healthy elders: a power envelope correlation MEG study

Functional magnetic resonance imaging (fMRI) studies report age-related changes in resting-state functional connectivity (rsFC), suggesting altered or reorganized connectivity patterns with age. However, age-related changes in neurovascular coupling might also partially account for altered connectivity patterns. Here, we used resting-state magnetoencephalography (MEG) and a connectome approach in carefully selected healthy young adults and elders. The MEG connectome was estimated as rsFC matrices involving forty nodes from six major  resting-state networks. Source-level rsFC maps were computed in relevant frequency bands using leakage-corrected envelope correlations. Group differences were statistically assessed using non-parametric permutation tests. Our results failed to evidence significant age-related differences after correction for multiple comparisons in the α and the β bands both for static and dynamic rsFC, suggesting that the electrophysiological connectome is maintained in healthy ageing. Further studies should compare the evolution of the human brain connectome as estimated using fMRI and MEG in same healthy young and elder adults, as well as in ageing conditions associated with cognitive decline. At present, our results are in agreement with the brain maintenance theory for successful aging as they suggest that preserved intrinsic functional brain integration contributes to preserved cognitive functioning in healthy elders.

Default mode network abnormalities in children with autism spectrum disorder detected by resting-state functional magnetic resonance imaging

PURPOSE

The purpose of this study was to investigate changes in the functional connectivity of the default mode network (DMN) in normal aging and in children with autistic spectrum disorder (ASD) by using resting-state functional magnetic resonance imaging (rsfMRI) and independent component analysis.

METHODS

Thirty-one healthy controls (HC) in four age groups (1-3, 4-8, 20-29, and 50-59 years) and 14 childhood ASD cases (1-8 years of age) were examined by rsfMRI echo-planar imaging on a clinical 3-T MRI scanner. Imaging of all children (1-8 years) was conducted under sedation, while adults were scanned in the awake state with eyes closed.

RESULTS

The regions of DMN functional connectivity in the bilateral inferior parietal lobule and posterior cingulate cortex were smaller in HC children than in HC adults, and smaller in the ASD group than in the HC children.

CONCLUSION

It is possible to observe developmental and pathological changes in the DMN by rsfMRI. Reduced DMN functional connectivity in children may be a useful biomarker for ASD diagnosis. J. Med. Invest. 63: 204-208, August, 2016.

Sources of disconnection in neurocognitive aging: cerebral white-matter integrity, resting-state functional connectivity, and white-matter hyperintensity volume

Age-related decline in fluid cognition can be characterized as a disconnection among specific brain structures, leading to a decline in functional efficiency. The potential sources of disconnection, however, are unclear. We investigated imaging measures of cerebral white-matter integrity, resting-state functional connectivity, and white-matter hyperintensity volume as mediators of the relation between age and fluid cognition, in 145 healthy, community-dwelling adults 19-79 years of age. At a general level of analysis, with a single composite measure of fluid cognition and single measures of each of the 3 imaging modalities, age exhibited an independent influence on the cognitive and imaging measures, and the imaging variables did not mediate the age-cognition relation. At a more specific level of analysis, resting-state functional connectivity of sensorimotor networks was a significant mediator of the age-related decline in executive function. These findings suggest that different levels of analysis lead to different models of neurocognitive disconnection, and that resting-state functional connectivity, in particular, may contribute to age-related decline in executive function.

Increased sensitivity to age-related differences in brain functional connectivity during continuous multiple object tracking compared to resting-state

Age-related differences in cognitive agility vary greatly between individuals and cognitive functions. This heterogeneity is partly mirrored in individual differences in brain network connectivity as revealed using resting-state functional magnetic resonance imaging (fMRI), suggesting potential imaging biomarkers for age-related cognitive decline. However, although convenient in its simplicity, the resting state is essentially an unconstrained paradigm with minimal experimental control. Here, based on the conception that the magnitude and characteristics of age-related differences in brain connectivity is dependent on cognitive context and effort, we tested the hypothesis that experimentally increasing cognitive load boosts the sensitivity to age and changes the discriminative network configurations. To this end, we obtained fMRI data from younger (n=25, mean age 24.16±5.11) and older (n=22, mean age 65.09±7.53) healthy adults during rest and two load levels of continuous multiple object tracking (MOT). Brain network nodes and their time-series were estimated using independent component analysis (ICA) and dual regression, and the edges in the brain networks were defined as the regularized partial temporal correlations between each of the node pairs at the individual level. Using machine learning based on a cross-validated regularized linear discriminant analysis (rLDA) we attempted to classify groups and cognitive load from the full set of edge-wise functional connectivity indices. While group classification using resting-state data was highly above chance (approx. 70% accuracy), functional connectivity (FC) obtained during MOT strongly increased classification performance, with 82% accuracy for the young and 95% accuracy for the old group at the highest load level. Further, machine learning revealed stronger differentiation between rest and task in young compared to older individuals, supporting the notion of network dedifferentiation in cognitive aging. Task-modulation in edgewise FC was primarily observed between attention- and sensorimotor networks; with decreased negative correlations between attention- and default mode networks in older adults. These results demonstrate that the magnitude and configuration of age-related differences in brain functional connectivity are partly dependent on cognitive context and load, which emphasizes the importance of assessing brain connectivity differences across a range of cognitive contexts beyond the resting-state.

Gender Specific Re-organization of Resting-State Networks in Older Age

Advancing age is commonly associated with changes in both brain structure and function. Recently, the suggestion that alterations in brain connectivity may drive disruption in cognitive abilities with age has been investigated. However, the interaction between the effects of age and gender on the re-organization of resting-state networks is not fully understood. This study sought to investigate the effect of both age and gender on intra- and inter-network functional connectivity (FC) and the extent to which resting-state network (RSN) node definition may alter with older age. We obtained resting-state functional magnetic resonance images from younger (n = 20) and older (n = 20) adults and assessed the FC of three main cortical networks: default mode (DMN), dorsal attention (DAN), and saliency (SN). Older adults exhibited reduced DMN intra-network FC and increased inter-network FC between the anterior cingulate cortex (ACC) and nodes of the DAN, in comparison to younger participants. Furthermore, this increase in ACC-DAN inter-network FC with age was driven largely by male participants. However, further analyses suggested that the spatial location of ACC, bilateral anterior insula and orbitofrontal cortex RSN nodes changed with older age and that age-related gender differences in FC may reflect spatial re-organization rather than increases or decreases in FC strength alone. These differences in both the FC and spatial distribution of RSNs between younger and older adults provide evidence of re-organization of fundamental brain networks with age, which is modulated by gender. These results highlight the need to further investigate changes in both intra- and inter-network FC with age, whilst also exploring the modifying effect of gender. They also emphasize the difficulties in directly comparing the FC of RSN nodes between groups and suggest that caution should be taken when using the same RSN node definitions for different age or patient groups to investigate FC.

Putting age-related task activation into large-scale brain networks: A meta-analysis of 114 fMRI studies on healthy aging

Normal aging is associated with cognitive decline and underlying brain dysfunction. Previous studies concentrated less on brain network changes at a systems level. Our goal was to examine these age-related changes of fMRI-derived activation with a common network parcellation of the human brain function, offering a systems-neuroscience perspective of healthy aging. We conducted a series of meta-analyses on a total of 114 studies that included 2035 older adults and 1845 young adults. Voxels showing significant age-related changes in activation were then overlaid onto seven commonly referenced neuronal networks. Older adults present moderate cognitive decline in behavioral performance during fMRI scanning, and hypo-activate the visual network and hyper-activate both the frontoparietal control and default mode networks. The degree of increased activation in frontoparietal network was associated with behavioral performance in older adults. Age-related changes in activation present different network patterns across cognitive domains. The systems neuroscience approach used here may be useful for elucidating the underlying network mechanisms of various brain plasticity processes during healthy aging.

Reorganization of brain networks in aging: a review of functional connectivity studies

Healthy aging (HA) is associated with certain declines in cognitive functions, even in individuals that are free of any process of degenerative illness. Functional magnetic resonance imaging (fMRI) has been widely used in order to link this age-related cognitive decline with patterns of altered brain function. A consistent finding in the fMRI literature is that healthy old adults present higher activity levels in some brain regions during the performance of cognitive tasks. This finding is usually interpreted as a compensatory mechanism. More recent approaches have focused on the study of functional connectivity, mainly derived from resting state fMRI, and have concluded that the higher levels of activity coexist with disrupted connectivity. In this review, we aim to provide a state-of-the-art description of the usefulness and the interpretations of functional brain connectivity in the context of HA. We first give a background that includes some basic aspects and methodological issues regarding functional connectivity. We summarize the main findings and the cognitive models that have been derived from task-activity studies, and we then review the findings provided by resting-state functional connectivity in HA. Finally, we suggest some future directions in this field of research. A common finding of the studies included is that older subjects present reduced functional connectivity compared to young adults. This reduced connectivity affects the main brain networks and explains age-related cognitive alterations. Remarkably, the default mode network appears as a highly compromised system in HA. Overall, the scenario given by both activity and connectivity studies also suggests that the trajectory of changes during task may differ from those observed during resting-state. We propose that the use of complex modeling approaches studying effective connectivity may help to understand context-dependent functional reorganizations in the aging process.