Age-Related Declines in Motor Performance are Associated With Decreased Segregation of Large-Scale Resting State Brain Networks

Brain-wide functional connectome analysis of 40,000 individuals reveals brain networks that show aging effects in older adults

The functional connectome changes with aging. We systematically evaluated aging related alterations in the functional connectome using a whole-brain connectome network analysis in 39,675 participants in UK Biobank project. We used adaptive dense network discovery tools to identify networks directly associated with aging from resting-state fMRI data. We replicated our findings in 499 participants from the Lifespan Human Connectome Project in Aging study. The results consistently revealed two motor-related subnetworks (both permutation test p-values <0.001) that showed a decline in resting-state functional connectivity (rsFC) with increasing age. The first network primarily comprises sensorimotor and dorsal/ventral attention regions from precentral gyrus, postcentral gyrus, superior temporal gyrus, and insular gyrus, while the second network is exclusively composed of basal ganglia regions, namely the caudate, putamen, and globus pallidus. Path analysis indicates that white matter fractional anisotropy mediates 19.6% (p<0.001, 95% CI [7.6% 36.0%]) and 11.5% (p<0.001, 95% CI [6.3% 17.0%]) of the age-related decrease in both networks, respectively. The total volume of white matter hyperintensity mediates 32.1% (p<0.001, 95% CI [16.8% 53.0%]) of the aging-related effect on rsFC in the first subnetwork.

Resting state brain network segregation is associated with walking speed and working memory in older adults

Older adults exhibit larger individual differences in walking ability and cognitive function than young adults. Characterizing intrinsic brain connectivity differences in older adults across a wide walking performance spectrum may provide insight into the mechanisms of functional decline in some older adults and resilience in others. Thus, the objectives of this study were to: (1) determine whether young adults and high- and low-functioning older adults show group differences in brain network segregation, and (2) determine whether network segregation is associated with working memory and walking function in these groups. The analysis included 21 young adults and 81 older adults. Older adults were further categorized according to their physical function using a standardized assessment; 54 older adults had low physical function while 27 were considered high functioning. Structural and functional resting state magnetic resonance images were collected using a Siemens Prisma 3T scanner. Working memory was assessed with the NIH Toolbox list sorting test. Walking speed was assessed with a 400 m-walk test at participants' self-selected speed. We found that network segregation in mobility-related networks (sensorimotor, vestibular, and visual networks) was higher in younger adults compared to older adults. There were no group differences in laterality effects on network segregation. We found multivariate associations between working memory and walking speed with network segregation scores. Higher right anterior cingulate cortex network segregation was associated with higher working memory function. Higher right sensorimotor, right vestibular, right anterior cingulate cortex, and lower left anterior cingulate cortex network segregation was associated with faster walking speed. These results are unique and significant because they demonstrate higher network segregation is largely related to higher physical function and not age alone.

Highlights

Segregation is lower in mobility-related networks in older adults vs younger adults.Older adults with high and low physical function have segregation differences.Laterality of functional network segregation is not different between age groups.Higher network segregation is associated with faster walking speed.

Age differences in functional connectivity track dedifferentiation of category representations

With advancing age, the distinctiveness of neural representations of information declines. While the finding of this so-called 'age-related neural dedifferentiation' in category-selective neural regions is well-described, the contribution of age-related changes in network organization to dedifferentiation is unknown. Here, we asked whether age differences in a) whole-brain network segregation (i.e., network dedifferentiation) and b) functional connectivity to category-selective neural regions contribute to regional dedifferentiation of categorical representations. Younger and older adults viewed blocks of face and house stimuli in the fMRI scanner. We found an age-related decline in neural distinctiveness for faces in the fusiform gyrus (FG) and for houses in the parahippocampal gyrus (PHG). Functional connectivity analyses revealed age-related dedifferentiation of global network structure as well as age differences in connectivity between the FG and early visual cortices. Interindividual correlations demonstrated that regional distinctiveness was related to network segregation as well as connectivity of the FG to the visual network. Together, our findings reveal that dedifferentiation of categorical representations may be linked to age-related reorganization of functional networks.

Brain signaling becomes less integrated and more segregated with age

The integration-segregation framework is a popular first step to understand brain dynamics because it simplifies brain dynamics into two states based on global vs. local signaling patterns. However, there is no consensus for how to best define what the two states look like. Here, we map integration and segregation to order and disorder states from the Ising model in physics to calculate state probabilities, P int and P seg , from functional MRI data. We find that integration/segregation decreases/increases with age across three databases, and changes are consistent with weakened connection strength among regions rather than topological connectivity based on structural and diffusion MRI data.

Sex-specific Neural Strategies During Fatiguing Work in Older Adults

BACKGROUND

Historical biases in ergonomics-related studies have been attributed to lack of participant diversity and sensitivity of measurements to capture variability between diverse groups. We posit that a neuroergonomics approach, that is, study of brain-behavior relationships during fatiguing work, allows for unique insights on sex differences in fatigue mechanisms that are not available via traditional "neck down" measurement approaches.

OBJECTIVE

This study examined the supraspinal mechanisms of exercise performance under fatigue and determined if there were any sex differences in these mechanisms.

METHODS

Fifty-nine older adults performed submaximal handgrip contractions until voluntary fatigue. Traditional ergonomics measures, namely, force variability, electromyography (EMG) of arm muscles, and strength and endurance times, and prefrontal and motor cortex hemodynamic responses were recorded.

RESULTS

There were no significant differences observed between older males and females in fatigability outcomes (i.e., endurance times, strength loss, and EMG activity) and brain activation. Effective connectivity from prefrontal to motor areas was significant for both sexes throughout the task, but during fatigue, males had higher interregional connectivity than females.

DISCUSSION

While traditional metrics of fatigue were comparable between the sexes, we observed distinct sex-specific neuromotor strategies (i.e., information flow between frontal-motor regions) that were adopted by older adults to maintain motor performance.

APPLICATION

The findings from this study offer insights into the capabilities and adaptation strategies of older men and women under fatiguing conditions. This knowledge can facilitate in the development of effective and targeted ergonomic strategies that accommodate for the varying physical capacities of diverse worker demographics.

Sensorimotor Network Segregation Predicts Long-Term Learning of Writing Skills in Parkinson's Disease

The prediction of motor learning in Parkinson's disease (PD) is vastly understudied. Here, we investigated which clinical and neural factors predict better long-term gains after an intensive 6-week motor learning program to ameliorate micrographia. We computed a composite score of learning through principal component analysis, reflecting better writing accuracy on a tablet in single and dual task conditions. Three endpoints were studied-acquisition (pre- to post-training), retention (post-training to 6-week follow-up), and overall learning (acquisition plus retention). Baseline writing, clinical characteristics, as well as resting-state network segregation were used as predictors. We included 28 patients with PD (13 freezers and 15 non-freezers), with an average disease duration of 7 (±3.9) years. We found that worse baseline writing accuracy predicted larger gains for acquisition and overall learning. After correcting for baseline writing accuracy, we found female sex to predict better acquisition, and shorter disease duration to help retention. Additionally, absence of FOG, less severe motor symptoms, female sex, better unimanual dexterity, and better sensorimotor network segregation impacted overall learning positively. Importantly, three factors were retained in a multivariable model predicting overall learning, namely baseline accuracy, female sex, and sensorimotor network segregation. Besides the room to improve and female sex, sensorimotor network segregation seems to be a valuable measure to predict long-term motor learning potential in PD.

Elevating understanding: Linking high-altitude hypoxia to brain aging through EEG functional connectivity and spectral analyses

High-altitude hypoxia triggers brain function changes reminiscent of those in healthy aging and Alzheimer's disease, compromising cognition and executive functions. Our study sought to validate high-altitude hypoxia as a model for assessing brain activity disruptions akin to aging. We collected EEG data from 16 healthy volunteers during acute high-altitude hypoxia (at 4,000 masl) and at sea level, focusing on relative changes in power and aperiodic slope of the EEG spectrum due to hypoxia. Additionally, we examined functional connectivity using wPLI, and functional segregation and integration using graph theory tools. High altitude led to slower brain oscillations, that is, increased δ and reduced α power, and flattened the 1/f aperiodic slope, indicating higher electrophysiological noise, akin to healthy aging. Notably, functional integration strengthened in the θ band, exhibiting unique topographical patterns at the subnetwork level, including increased frontocentral and reduced occipitoparietal integration. Moreover, we discovered significant correlations between subjects' age, 1/f slope, θ band integration, and observed robust effects of hypoxia after adjusting for age. Our findings shed light on how reduced oxygen levels at high altitudes influence brain activity patterns resembling those in neurodegenerative disorders and aging, making high-altitude hypoxia a promising model for comprehending the brain in health and disease.

High-intensity acute exercise impacts motor learning in healthy older adults

Healthy aging is associated with changes in motor sequence learning, with some studies indicating decline in motor skill learning in older age. Acute cardiorespiratory exercise has emerged as a potential intervention to improve motor learning, however research in healthy older adults is limited. The current study investigated the impact of high-intensity interval exercise (HIIT) on a subsequent sequential motor learning task. Twenty-four older adults (aged 55-75 years) completed either 20-minutes of cycling, or an equivalent period of active rest before practicing a sequential force grip task. Skill learning was assessed during acquisition and at a 6-hour retention test. In contrast to expectation, exercise was associated with reduced accuracy during skill acquisition compared to rest, particularly for the oldest participants. However, improvements in motor skill were retained in the exercise condition, while a reduction in skill was observed following rest. Our findings indicate that high-intensity exercise conducted immediately prior to learning a novel motor skill may have a negative impact on motor performance during learning in older adults. We also demonstrated that exercise may facilitate early offline consolidation of a motor skill within this population, which has implications for motor rehabilitation.

Intrinsic functional brain connectivity changes following aerobic exercise, computerized cognitive training, and their combination in physically inactive healthy late-middle-aged adults: the Projecte Moviment

Lifestyle interventions have positive neuroprotective effects in aging. However, there are still open questions about how changes in resting-state functional connectivity (rsFC) contribute to cognitive improvements. The Projecte Moviment is a 12-week randomized controlled trial of a multimodal data acquisition protocol that investigated the effects of aerobic exercise (AE), computerized cognitive training (CCT), and their combination (COMB). An initial list of 109 participants was recruited from which a total of 82 participants (62% female; age = 58.38 ± 5.47) finished the intervention with a level of adherence > 80%. Only in the COMB group, we revealed an extended network of 33 connections that involved an increased and decreased rsFC within and between the aDMN/pDMN and a reduced rsFC between the bilateral supplementary motor areas and the right thalamus. No global and especially local rsFC changes due to any intervention mediated the cognitive benefits detected in the AE and COMB groups. Projecte Moviment provides evidence of the clinical relevance of lifestyle interventions and the potential benefits when combining them.

Measures of resting-state brain network segregation and integration vary in relation to data quantity: implications for within and between subject comparisons of functional brain network organization

Measures of functional brain network segregation and integration vary with an individual's age, cognitive ability, and health status. Based on these relationships, these measures are frequently examined to study and quantify large-scale patterns of network organization in both basic and applied research settings. However, there is limited information on the stability and reliability of the network measures as applied to functional time-series; these measurement properties are critical to understand if the measures are to be used for individualized characterization of brain networks. We examine measurement reliability using several human datasets (Midnight Scan Club and Human Connectome Project [both Young Adult and Aging]). These datasets include participants with multiple scanning sessions, and collectively include individuals spanning a broad age range of the adult lifespan. The measurement and reliability of measures of resting-state network segregation and integration vary in relation to data quantity for a given participant's scan session; notably, both properties asymptote when estimated using adequate amounts of clean data. We demonstrate how this source of variability can systematically bias interpretation of differences and changes in brain network organization if appropriate safeguards are not included. These observations have important implications for cross-sectional, longitudinal, and interventional comparisons of functional brain network organization.

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.

Noninvasive theta-burst stimulation of the human striatum enhances striatal activity and motor skill learning

The stimulation of deep brain structures has thus far only been possible with invasive methods. Transcranial electrical temporal interference stimulation (tTIS) is a novel, noninvasive technology that might overcome this limitation. The initial proof-of-concept was obtained through modeling, physics experiments and rodent models. Here we show successful noninvasive neuromodulation of the striatum via tTIS in humans using computational modeling, functional magnetic resonance imaging studies and behavioral evaluations. Theta-burst patterned striatal tTIS increased activity in the striatum and associated motor network. Furthermore, striatal tTIS enhanced motor performance, especially in healthy older participants as they have lower natural learning skills than younger subjects. These findings place tTIS as an exciting new method to target deep brain structures in humans noninvasively, thus enhancing our understanding of their functional role. Moreover, our results lay the groundwork for innovative, noninvasive treatment strategies for brain disorders in which deep striatal structures play key pathophysiological roles.

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.

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.

Chronic motor performance following different traumatic brain injury severity-A systematic review

Introduction

Traumatic brain injury (TBI) is now known to be a chronic disease, causing ongoing neurodegeneration and linked to increased risk of neurodegenerative motor diseases, such as Parkinson's disease and amyotrophic lateral sclerosis. While the presentation of motor deficits acutely following traumatic brain injury is well-documented, however, less is known about how these evolve in the long-term post-injury, or how the initial severity of injury affects these outcomes. The purpose of this review, therefore, was to examine objective assessment of chronic motor impairment across the spectrum of TBI in both preclinical and clinical models.

Methods

PubMed, Embase, Scopus, and PsycINFO databases were searched with a search strategy containing key search terms for TBI and motor function. Original research articles reporting chronic motor outcomes with a clearly defined TBI severity (mild, repeated mild, moderate, moderate-severe, and severe) in an adult population were included.

Results

A total of 97 studies met the inclusion criteria, incorporating 62 preclinical and 35 clinical studies. Motor domains examined included neuroscore, gait, fine-motor, balance, and locomotion for preclinical studies and neuroscore, fine-motor, posture, and gait for clinical studies. There was little consensus among the articles presented, with extensive differences both in assessment methodology of the tests and parameters reported. In general, an effect of severity was seen, with more severe injury leading to persistent motor deficits, although subtle fine motor deficits were also seen clinically following repeated injury. Only six clinical studies investigated motor outcomes beyond 10 years post-injury and two preclinical studies to 18-24 months post-injury, and, as such, the interaction between a previous TBI and aging on motor performance is yet to be comprehensively examined.

Conclusion

Further research is required to establish standardized motor assessment procedures to fully characterize chronic motor impairment across the spectrum of TBI with comprehensive outcomes and consistent protocols. Longitudinal studies investigating the same cohort over time are also a key for understanding the interaction between TBI and aging. This is particularly critical, given the risk of neurodegenerative motor disease development following TBI.

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).

The effect of acute exercise on cognitive and motor inhibition - Does fitness moderate this effect?

BACKGROUND

Given the extensive evidence on improvements in cognitive inhibition immediately following exercise, and the literature indicating that cognitive and motor inhibitory functions are mediated by overlapping brain networks, the aim of this study was to assess, for the first time, the effect of moderate intensity acute aerobic exercise on multi-limb motor inhibition, as compared to cognitive inhibition.

METHOD

Participants were 36 healthy adults aged 40-60 years old (mean age 46.8 ± 5.7), who were randomly assigned to experimental or control groups. One-to-two weeks following baseline assessment, participants were asked to perform a three-limb (3-Limb) inhibition task and a vocal version of the Stroop before and after either acute moderate-intense aerobic exercise (experimental group) or rest (control).

RESULTS

Similar rates of improvement were observed among both groups from baseline to the pre-test. Conversely, a meaningful, yet non-significant trend was seen among the experimental group in their pretest to posttest improvement in both cognitive and motor tasks. In addition, exploratory analysis revealed significant group differences in favor of the experimental group among highly fit participants on the 3-Limb task. A significant correlation was indicated between the inhibition conditions, i.e., choice in the motor inhibition and color/word (incongruent) in the cognitive inhibition, especially in the improvement observed following the exercise.

DISCUSSION

Moderate-intensity acute aerobic exercise is a potential stimulator of both multi-limb motor inhibition and cognitive inhibition. It appears that high-fit participants benefit from exercise more than low-fit people. Additionally, performance on behavioral tasks that represent motor and cognitive inhibition is related. This observation suggests that fitness levels and acute exercise contribute to the coupling between cognitive and motor inhibition. Neuroimaging methods would allow examining brain-behavior associations of exercise-induced changes in the brain.

[Late-life depression and frailty-Epidemiological, clinical and neurobiological associations]

BACKGROUND

Depression is the most common mental disorder in older adults and is influenced by age-related processes. Frailty is a well-established clinical expression of ageing that implies a state of increased vulnerability to stressor events as well as increased risks of disability, hospitalization and death. Neurobiological findings will disentangle the comorbidity of frailty and depression and may inform future management of depression in old age.

OBJECTIVE

This narrative review provides an overview of the comorbidity of late-life depression and frailty, with a focus on neuroscientific findings that are organized within the research domain criteria (RDoC) framework.

RESULTS

More than one third of old people with depression are affected by frailty, which results in more chronic depression and in poorer efficacy and tolerability of antidepressant medication. Depression and frailty share motivational and psychomotor characteristics, particularly apathy, decreased physical activity and fatigue. In patients with frailty, altered activity of the supplementary motor cortex is associated with motor performance deficits. Patients with late-life depression and apathy are characterized by abnormal structure and altered functional connectivity of the reward network and the salience network, along with altered functional connectivity of these networks with premotor brain areas.

CONCLUSION

Identifying frailty in older adults with depression is relevant for prognostic assessment and treatment. A better understanding of the neuronal mechanisms of comorbidity will provide potential targets for future personalized therapeutic interventions.

Stability of sensorimotor network sculpts the dynamic repertoire of resting state over lifespan

Temporally stable patterns of neural coordination among distributed brain regions are crucial for survival. Recently, many studies highlight association between healthy aging and modifications in organization of functional brain networks, across various time-scales. Nonetheless, quantitative characterization of temporal stability of functional brain networks across healthy aging remains unexplored. This study introduces a data-driven unsupervised approach to capture high-dimensional dynamic functional connectivity (dFC) via low-dimensional patterns and subsequent estimation of temporal stability using quantitative metrics. Healthy aging related changes in temporal stability of dFC were characterized across resting-state, movie-viewing, and sensorimotor tasks (SMT) on a large (n = 645) healthy aging dataset (18-88 years). Prominent results reveal that (1) whole-brain temporal dynamics of dFC movie-watching task is closer to resting-state than to SMT with an overall trend of highest temporal stability observed during SMT followed by movie-watching and resting-state, invariant across lifespan aging, (2) in both tasks conditions stability of neurocognitive networks in young adults is higher than older adults, and (3) temporal stability of whole brain resting-state follows a U-shaped curve along lifespan-a pattern shared by sensorimotor network stability indicating their deeper relationship. Overall, the results can be applied generally for studying cohorts of neurological disorders using neuroimaging tools.

Organization of neurochemical interactions in young and older brains as revealed with a network approach: Evidence from proton magnetic resonance spectroscopy (1H-MRS)

Aging is associated with alterations in the brain including structural and metabolic changes. Previous research has focused on neurometabolite level differences associated to age in a variety of brain regions, but the relationship among metabolites across the brain has been much less studied. Investigating these relationships can reveal underlying neurometabolic processes, their interdependency, and their progress throughout the lifespan. Using ¹H-MRS, we investigated the relationship among metabolite concentrations of N-acetylaspartate (NAA), creatine (Cr), choline (Cho), myo-Inositol (mIns) and glutamate-glutamine complex (Glx) in seven voxel locations, i.e., bilateral sensorimotor cortex, bilateral striatum, pre-supplementary motor area, right inferior frontal gyrus and occipital cortex. These measurements were performed on 59 human participants divided in two age groups: young adults (YA: 23.2 ± 4.3; 18-34 years) and older adults (OA: 67.5 ± 3.9; 61-74 years). Our results showed age-related differences in NAA, Cho, and mIns across brain regions, suggesting the presence of neurodegeneration and altered gliosis. Moreover, associative patterns among NAA, Cho and Cr were observed across the selected brain regions, which differed between young and older adults. Whereas most of metabolite concentrations were inhomogeneous across different brain regions, Cho levels were shown to be strongly related across brain regions in both age groups. Finally, we found metabolic associations between homologous brain regions (SM1 and striatum) in the OA group, with NAA showing a significant correlation between bilateral sensorimotor cortices (SM1) and mIns levels being correlated between the bilateral striata. We posit that a network perspective provides important insights regarding the potential interactions among neurochemicals underlying metabolic processes at a local and global level and their relationship with aging.

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.

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.

Interactions between the aging brain and motor task complexity across the lifespan: balancing brain activity resource demand and supply

The Compensation Related Utilization of Neural Circuits Hypothesis (CRUNCH) proposes a framework for understanding task-related brain activity changes as a function of healthy aging and task complexity. Specifically, it affords the following predictions: (i) all adult age groups display more brain activation with increases in task complexity, (ii) older adults show more brain activation compared with younger adults at low task complexity levels, and (iii) disproportionately increase brain activation with increased task complexity, but (iv) show smaller (or no) increases in brain activation at the highest complexity levels. To test these hypotheses, performance on a bimanual tracking task at 4 complexity levels and associated brain activation were assessed in 3 age groups (20-40, 40-60, and 60-80 years, n = 99). All age groups showed decreased tracking accuracy and increased brain activation with increased task complexity, with larger performance decrements and activation increases in the older age groups. Older adults exhibited increased brain activation at a lower complexity level, but not the predicted failure to further increase brain activity at the highest complexity level. We conclude that older adults show more brain activation than younger adults and preserve the capacity to deploy increased neural resources as a function of task demand.

Age-related differences in functional network segregation in the context of sex and reproductive stage

Age is accompanied by differences in the organization of functional brain networks, which impact behavior in adulthood. Functional networks become less segregated and more integrated with age. However, sex differences in network segregation declines with age are not well-understood. Further, network segregation in the context of female reproductive stage is relatively understudied, though unmasking such relationships would be informative for elucidating biological mechanisms that contribute to sex-specific differences in aging. In the current work, we used data from the Cambridge Centre for Ageing and Neuroscience (Cam-CAN) repository to evaluate differences in resting-state network segregation as a product of sex and reproductive stage. Reproductive stage was categorized using the Stages of Reproductive Aging Workshop (STRAW+10) criteria. Replicating prior work, we investigated the following functional networks: auditory, cerebellar-basal ganglia, cingulo-opercular task control, default mode, dorsal attention, fronto-parietal task control, salience, sensory somatomotor mouth, sensory somatomotor hand, ventral attention, and visual. First, our results mirror findings from previous work indicating that network segregation is lower with increasing age. Second, when analyzing associations between network segregation and age within each sex separately, we find qualitative differences between females and males. Finally, we report significant effects of reproductive stage on network segregation, though these findings are likely driven by age. Broadly, our results suggest that impacts of sex may be important to evaluate when investigating network segregation differences across adulthood, though further work is needed to determine the unique role of menopause and sex hormones on the organization of functional brain networks within aging females.

Age differences in the functional architecture of the human brain

The intrinsic functional organization of the brain changes into older adulthood. Age differences are observed at multiple spatial scales, from global reductions in modularity and segregation of distributed brain systems, to network-specific patterns of dedifferentiation. Whether dedifferentiation reflects an inevitable, global shift in brain function with age, circumscribed, experience-dependent changes, or both, is uncertain. We employed a multimethod strategy to interrogate dedifferentiation at multiple spatial scales. Multi-echo (ME) resting-state fMRI was collected in younger (n = 181) and older (n = 120) healthy adults. Cortical parcellation sensitive to individual variation was implemented for precision functional mapping of each participant while preserving group-level parcel and network labels. ME-fMRI processing and gradient mapping identified global and macroscale network differences. Multivariate functional connectivity methods tested for microscale, edge-level differences. Older adults had lower BOLD signal dimensionality, consistent with global network dedifferentiation. Gradients were largely age-invariant. Edge-level analyses revealed discrete, network-specific dedifferentiation patterns in older adults. Visual and somatosensory regions were more integrated within the functional connectome; default and frontoparietal control network regions showed greater connectivity; and the dorsal attention network was more integrated with heteromodal regions. These findings highlight the importance of multiscale, multimethod approaches to characterize the architecture of functional brain aging.

No evidence for a difference in lateralization and distinctiveness level of transcranial magnetic stimulation-derived cortical motor representations over the adult lifespan

This study aimed to investigate the presence and patterns of age-related differences in TMS-based measures of lateralization and distinctiveness of the cortical motor representations of two different hand muscles. In a sample of seventy-three right-handed healthy participants over the adult lifespan, the first dorsal interosseus (FDI) and abductor digiti minimi (ADM) cortical motor representations of both hemispheres were acquired using transcranial magnetic stimulation (TMS). In addition, dexterity and maximum force levels were measured. Lateralization quotients were calculated for homolog behavioral and TMS measures, whereas the distinctiveness between the FDI and ADM representation within one hemisphere was quantified by the center of gravity (CoG) distance and cosine similarity. The presence and patterns of age-related changes were examined using linear, polynomial, and piecewise linear regression. No age-related differences could be identified for the lateralization quotient of behavior or cortical motor representations of both intrinsic hand muscles. Furthermore, no evidence for a change in the distinctiveness of the FDI and ADM representation with advancing age was found. In conclusion this work showed that lateralization and distinctiveness of cortical motor representations, as determined by means of TMS-based measures, remain stable over the adult lifespan.

Individual functional parcellation revealed compensation of dynamic limbic network organization in healthy ageing

Using group-level functional parcellations and constant-length sliding window analysis, dynamic functional connectivity studies have revealed network-specific impairment and compensation in healthy ageing. However, functional parcellation and dynamic time windows vary across individuals; individual-level ageing-related brain dynamics are uncertain. Here, we performed individual parcellation and individual-length sliding window clustering to characterize ageing-related dynamic network changes. Healthy participants (n = 637, 18-88 years) from the Cambridge Centre for Ageing and Neuroscience dataset were included. An individual seven-network parcellation, varied from group-level parcellation, was mapped for each participant. For each network, strong and weak cognitive brain states were revealed by individual-length sliding window clustering and canonical correlation analysis. The results showed negative linear correlations between age and change ratios of sizes in the default mode, frontoparietal, and salience networks and a positive linear correlation between age and change ratios of size in the limbic network (LN). With increasing age, the occurrence and dwell time of strong states showed inverted U-shaped patterns or a linear decreasing pattern in most networks but showed a linear increasing pattern in the LN. Overall, this study reveals a compensative increase in emotional networks (i.e., the LN) and a decline in cognitive and primary sensory networks in healthy ageing. These findings may provide insights into network-specific and individual-level targeting during neuromodulation in ageing and ageing-related diseases.

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.

High-order functional redundancy in ageing explained via alterations in the connectome in a whole-brain model

The human brain generates a rich repertoire of spatio-temporal activity patterns, which support a wide variety of motor and cognitive functions. These patterns of activity change with age in a multi-factorial manner. One of these factors is the variations in the brain’s connectomics that occurs along the lifespan. However, the precise relationship between high-order functional interactions and connnectomics, as well as their variations with age are largely unknown, in part due to the absence of mechanistic models that can efficiently map brain connnectomics to functional connectivity in aging. To investigate this issue, we have built a neurobiologically-realistic whole-brain computational model using both anatomical and functional MRI data from 161 participants ranging from 10 to 80 years old. We show that the differences in high-order functional interactions between age groups can be largely explained by variations in the connectome. Based on this finding, we propose a simple neurodegeneration model that is representative of normal physiological aging. As such, when applied to connectomes of young participant it reproduces the age-variations that occur in the high-order structure of the functional data. Overall, these results begin to disentangle the mechanisms by which structural changes in the connectome lead to functional differences in the ageing brain. Our model can also serve as a starting point for modeling more complex forms of pathological ageing or cognitive deficits.

Modern neuroimaging techniques allow us to study how the human brain’s anatomical architecture (a.k.a. structural connectome) changes under different conditions or interventions. Recently, using functional neuroimaging data, we have shown that complex patterns of interactions between brain areas change along the lifespan, exhibiting increased redundant interactions in the older population. However, the mechanisms that underlie these functional differences are still unclear. Here, we extended this work and hypothesized that the variations of functional patterns can be explained by the dynamics of the brain’s anatomical networks, which are known to degenerate as we age. To test this hypothesis, we implemented a whole-brain model of neuronal activity, where different brain regions are anatomically wired using real connectomes from 161 participants with ages ranging from 10 to 80 years old. Analyzing different functional aspects of brain activity when varying the empirical connectomes, we show that the increased redundancy found in the older group can indeed be explained by precise rules affecting anatomical connectivity, thus emphasizing the critical role that the brain connectome plays for shaping complex functional interactions and the efficiency in the global communication of the human brain.

Bridging cognition and action: executive functioning mediates the relationship between white matter fiber density and complex motor abilities in older adults

Aging may be associated with motor decline that is attributed to deteriorating white matter microstructure of the corpus callosum (CC), among other brain-related factors. Similar to motor functioning, executive functioning (EF) typically declines during aging, with age-associated changes in EF likewise being linked to altered white matter connectivity in the CC. Given that both motor and executive functions rely on white matter connectivity via the CC, and that bimanual control is thought to rely on EF, the question arises whether EF can at least party account for the proposed link between CC-connectivity and motor control in older adults. To address this, diffusion magnetic resonance imaging data were obtained from 84 older adults. A fiber-specific approach was used to obtain fiber density (FD), fiber cross-section (FC), and a combination of both metrics in eight transcallosal white matter tracts. Motor control was assessed using a bimanual coordination task. EF was determined by a domain-general latent EF-factor extracted from multiple EF tasks, based on a comprehensive test battery. FD of transcallosal prefrontal fibers was associated with cognitive and motor performance. EF partly accounted for the relationship between FD of prefrontal transcallosal pathways and motor control. Our results underscore the multidimensional interrelations between callosal white matter connectivity (especially in prefrontal brain regions), EF across multiple domains, and motor control in the older population. They also highlight the importance of considering EF when investigating brain-motor behavior associations in older adults.

Bimanual motor impairments in older adults: an updated systematic review and meta-analysis

This updated systematic review and meta-analysis further examined potential effects of aging on bimanual movements. Forty-seven qualified studies that compared bimanual motor performances between elderly and younger adults were included in this meta-analysis. Moderator variable analyses additionally determined whether altered bimanual motor performances in older adults were different based on the task types (i.e., symmetry vs. asymmetry vs. complex) or outcome measures (i.e., accuracy vs. variability vs. movement time). The random effects model meta-analysis on 80 comparisons from 47 included studies revealed significant negative overall effects indicating more bimanual movement impairments in the elderly adults than younger adults. Moderator variable analyses found that older adults showed more deficits in asymmetrical bimanual movement tasks than symmetrical and complex tasks, and the bimanual movement impairments in the elderly adults included less accurate, more variable, and greater movement execution time than younger adults. These findings suggest that rehabilitation programs for improving motor actions in older adults are necessary to focus on functional recovery of interlimb motor control including advanced motor performances as well coordination.

A Neuroimaging Signature of Cognitive Aging from Whole-Brain Functional Connectivity

Cognitive decline is amongst one of the most commonly reported complaints during normal aging. Despite evidence that age and cognition are linked with similar neural correlates, no previous studies have directly ascertained how these two constructs overlap in the brain in terms of neuroimaging-based prediction. Based on a long lifespan healthy cohort (CamCAN, aged 19-89 years, n = 567), it is shown that both cognitive function (domains spanning executive function, emotion processing, motor function, and memory) and human age can be reliably predicted from unique patterns of functional connectivity, with models generalizable in two external datasets (n = 533 and n = 453). Results show that cognitive decline and normal aging both manifest decrease within-network connections (especially default mode and ventral attention networks) and increase between-network connections (somatomotor network). Whereas dorsal attention network is an exception, which is highly predictive on cognitive ability but is weakly correlated with aging. Further, the positively weighted connections in predicting fluid intelligence significantly mediate its association with age. Together, these findings offer insights into why normal aging is often associated with cognitive decline in terms of brain network organization, indicating a process of neural dedifferentiation and compensational theory.

Effect of senescence on the tyrosine hydroxylase and S100B immunoreactivity in the nigrostriatal pathway of the rat

Senescence is a natural and progressive physiological event that leads to a series of morphophysiological alterations in the organism. The brain is the most vulnerable organ to both structural and functional changes during this process. Dopamine is a key neurotransmitter for the proper functioning of the brain, directly involved in circuitries related with emotions, learning, motivation and reward. One of the main dopamine- producing nuclei is the substantia nigra pars compacta (SNpc), which establish connections with the striatum forming the so-called nigrostriatal pathway. S100B is a calcium binding protein mainly expressed by astrocytes, involved in both intracellular and extracellular processes, and whose expression is increased following injury in the nervous tissue, being a useful marker in altered status of central nervous system. The present study aimed to analyze the impact of senescence on the cells immunoreactive for tyrosine hydroxylase (TH) and S100B along the nigrostriatal pathway of the rat. Our results show an decreased expression of S100B⁺ cells in SNpc. In addition, there was a significant decrease in TH immunoreactivity in both projection fibers and TH⁺ cell bodies. In the striatum, a decrease in TH immunoreactivity was also observed, as well as an enlargement of the white matter bundles. Our findings point out that senescence is related to the anatomical and neurochemical changes observed throughout the nigrostriatal pathway.

The interaction between endogenous GABA, functional connectivity, and behavioral flexibility is critically altered with advanced age

The flexible adjustment of ongoing behavior challenges the nervous system’s dynamic control mechanisms and has shown to be specifically susceptible to age-related decline. Previous work links endogenous gamma-aminobutyric acid (GABA) with behavioral efficiency across perceptual and cognitive domains, with potentially the strongest impact on those behaviors that require a high level of dynamic control. Our analysis integrated behavior and modulation of interhemispheric phase-based connectivity during dynamic motor-state transitions with endogenous GABA concentration in adult human volunteers. We provide converging evidence for age-related differences in the preferred state of endogenous GABA concentration for more flexible behavior. We suggest that the increased interhemispheric connectivity observed in the older participants represents a compensatory neural mechanism caused by phase-entrainment in homotopic motor cortices. This mechanism appears to be most relevant in the presence of a less optimal tuning of the inhibitory tone as observed during healthy aging to uphold the required flexibility of behavioral action. Future work needs to validate the relevance of this interplay between neural connectivity and GABAergic inhibition for other domains of flexible human behavior.

An integrated analysis of GABA concentration, interhemispheric phase-based connectivity behavior and in healthy human participants revealed a task-specific association between GABA concentration and motor-cortical connectivity. These results shed light on how GABA is involved in neural oscillations and behavioral performance.

Connectivity in Large-Scale Resting-State Brain Networks Is Related to Motor Learning: A High-Density EEG Study

Previous research has shown that resting-state functional connectivity (rsFC) between different brain regions (seeds) is related to motor learning and motor memory consolidation. Using high-density electroencephalography (hdEEG), we addressed this question from a brain network perspective. Specifically, we examined frequency-dependent functional connectivity in resting-state networks from twenty-nine young healthy participants before and after they were trained on a motor sequence learning task. Consolidation was assessed with an overnight retest on the motor task. Our results showed training-related decreases in gamma-band connectivity within the motor network, and between the motor and functionally distinct resting-state networks including the attentional network. Brain-behavior correlation analyses revealed that baseline beta, delta, and theta rsFC were related to subsequent motor learning and memory consolidation such that lower connectivity within the motor network and between the motor and several distinct resting-state networks was correlated with better learning and overnight consolidation. Lastly, training-related increases in beta-band connectivity between the motor and the visual networks were related to greater consolidation. Altogether, our results indicate that connectivity in large-scale resting-state brain networks is related to—and modulated by—motor learning and memory consolidation processes. These finding corroborate previous seed-based connectivity research and provide evidence that frequency-dependent functional connectivity in resting-state networks is critically linked to motor learning and memory consolidation.

Prefrontal Cortical Connectivity Mediates Locus Coeruleus Noradrenergic Regulation of Inhibitory Control in Older Adults

Response inhibition is a core executive function enabling adaptive behavior in dynamic environments. Human and animal models indicate that inhibitory control and control networks are modulated by noradrenaline, arising from the locus coeruleus. The integrity (i.e., cellular density) of the locus coeruleus noradrenergic system can be estimated from magnetization transfer (MT)-sensitive magnetic resonance imaging (MRI), in view of neuromelanin present in noradrenergic neurons of older adults. Noradrenergic psychopharmacological studies indicate noradrenergic modulation of prefrontal and frontostriatal stopping-circuits in association with behavioral change. Here, we test the noradrenergic hypothesis of inhibitory control, in healthy adults. We predicted that locus coeruleus integrity is associated with age-adjusted variance in response inhibition, mediated by changes in connectivity between frontal inhibitory control regions. In a preregistered analysis, we used MT MRI images from N = 63 healthy humans aged above 50 years (of either sex) who performed a Stop-Signal Task (SST), with atlas-based measurement of locus coeruleus contrast. We confirm that better response inhibition is correlated with locus coeruleus integrity and stronger connectivity between presupplementary motor area (preSMA) and right inferior frontal gyrus (rIFG), but not volumes of the prefrontal cortical regions. We confirmed a significant role of prefrontal connectivity in mediating the effect of individual differences in the locus coeruleus on behavior, where this effect was moderated by age, over and above adjustment for the mean effects of age. Our results support the hypothesis that in normal populations, as in clinical settings, the locus coeruleus noradrenergic system regulates inhibitory control.SIGNIFICANCE STATEMENT We show that the integrity of the locus coeruleus, the principal source of cortical noradrenaline, is related to the efficiency of response inhibition in healthy older adults. This effect is in part mediated by its effect on functional connectivity in a prefrontal cortical stopping-network. The behavioral effect, and its mediation by connectivity, are moderated by age. This supports the psychopharmacological and genetic evidence for the noradrenergic regulation of behavioral control, in a population-based normative cohort. Noradrenergic treatment strategies may be effective to improve behavioral control in impulsive clinical populations, but age, and locus coeruleus integrity, are likely to be important stratification factors.

Network-specific differences in transient brain activity at rest are associated with age-related reductions in motor performance

Multiple functional changes occur in the brain with increasing age. Among those, older adults typically display more restricted fluctuations of brain activity, both during resting-state and task execution. These altered dynamic patterns have been linked to reduced task performance across multiple behavioral domains. Windowed functional connectivity, which is typically employed in the study of connectivity dynamics, however, might not be able to properly characterize moment-to-moment variations of individual networks. In the present study, we used innovation-driven co-activation patterns (ICAP) to overcome this limitation and investigate the length (duration) and frequency (innovation) in which various brain networks emerged across the adult lifespan (N= 92) during a resting-state period. We identified a link between increasing age and a tendency to engage brain areas with distinct functional associations simultaneously as a single network. The emergence of isolated and spatially well-defined visual, motor, frontoparietal, and posterior networks decreased with increased age. This reduction in dynamics of specialized networks mediated age-related performance decreases (i.e., increases in interlimb interference) in a bimanual motor task. Altogether, our findings demonstrated that older compared to younger adults tend to activate fewer network configurations, which include multiple functionally distinct brain areas. The reduction in independent emergence of functionally well-defined and task-relevant networks may reflect an expression of brain dedifferentiation and is likely associated with functional modulatory deficits, negatively impacting motor behavior.

Identifying a whole-brain connectome-based model in drug-naïve Parkinson's disease for predicting motor impairment

Identifying a whole‐brain connectome‐based predictive model in drug‐naïve patients with Parkinson's disease and verifying its predictions on drug‐managed patients would be useful in determining the intrinsic functional underpinnings of motor impairment and establishing general brain–behavior associations. In this study, we constructed a predictive model from the resting‐state functional data of 47 drug‐naïve patients by using a connectome‐based approach. This model was subsequently validated in 115 drug‐managed patients. The severity of motor impairment was assessed by calculating Unified Parkinson's Disease Rating Scale Part III scores. The predictive performance of model was evaluated using the correlation coefficient (r_true) between predicted and observed scores. As a result, a connectome‐based model for predicting individual motor impairment in drug‐naïve patients was identified with significant performance (r_true = .845, p < .001, p_permu = .002). Two patterns of connection were identified according to correlations between connection strength and the severity of motor impairment. The negative motor‐impairment‐related network contained more within‐network connections in the motor, visual‐related, and default mode networks, whereas the positive motor‐impairment‐related network was constructed mostly with between‐network connections coupling the motor‐visual, motor‐limbic, and motor‐basal ganglia networks. Finally, this predictive model constructed around drug‐naïve patients was confirmed with significant predictive efficacy on drug‐managed patients (r = .209, p = .025), suggesting a generalizability in Parkinson's disease patients under long‐term drug influence. In conclusion, this study identified a whole‐brain connectome‐based model that could predict the severity of motor impairment in Parkinson's patients and furthers our understanding of the functional underpinnings of the disease.

Differential Effects of a Nap on Motor Sequence Learning-Related Functional Connectivity Between Young and Older Adults

In older adults, motor sequence learning (MSL) is largely intact. However, consolidation of newly learned motor sequences is impaired compared to younger adults, and there is evidence that brain areas supporting enhanced consolidation via sleep degrade with age. It is known that brain activity in hippocampal-cortical-striatal areas is important for sleep-dependent, off-line consolidation of motor-sequences. Yet, the intricacies of how both age and sleep alter communication within this network of brain areas, which facilitate consolidation, are not known. In this study, 37 young (age 20-35) and 49 older individuals (age 55-75) underwent resting state functional magnetic resonance imaging (fMRI) before and after training on a MSL task as well as after either a nap or a period of awake rest. Young participants who napped showed strengthening of functional connectivity (FC) between motor, striatal, and hippocampal areas, compared to older subjects regardless of sleep condition. Follow-up analyses revealed this effect was driven by younger participants who showed an increase in FC between striatum and motor cortices, as well as older participants who showed decreased FC between the hippocampus, striatum, and precuneus. Therefore, different effects of sleep were observed in younger vs. older participants, where young participants primarily showed increased communication in the striatal-motor areas, while older participants showed decreases in key nodes of the default mode network and striatum. Performance gains correlated with FC changes in young adults, and this association was much greater in participants who napped compared to those who stayed awake. Performance gains also correlated with FC changes in older adults, but only in those who napped. This study reveals that, while there is no evidence of time-dependent forgetting/deterioration of performance, older adults exhibit a completely different pattern of FC changes during consolidation compared to younger adults, and lose the benefit that sleep affords to memory consolidation.

Neurophysiological modulations in the (pre)motor-motor network underlying age-related increases in reaction time and the role of GABA levels - a bimodal TMS-MRS study

It has been argued that age-related changes in the neurochemical and neurophysiological properties of the GABAergic system may underlie increases in reaction time (RT) in older adults. However, the role of GABA levels within the sensorimotor cortices (SMC) in mediating interhemispheric interactions (IHi) during the processing stage of a fast motor response, as well as how both properties explain interindividual differences in RT, are not yet fully understood. In this study, edited magnetic resonance spectroscopy (MRS) was combined with dual-site transcranial magnetic stimulation (dsTMS) for probing GABA+ levels in bilateral SMC and task-related neurophysiological modulations in corticospinal excitability (CSE), and primary motor cortex (M1)-M1 and dorsal premotor cortex (PMd)-M1 IHi, respectively. Both CSE and IHi were assessed during the preparatory and premotor period of a delayed choice RT task. Data were collected from 25 young (aged 18-33 years) and 28 older (aged 60-74 years) healthy adults. Our results demonstrated that older as compared to younger adults exhibited a reduced bilateral CSE suppression, as well as a reduced magnitude of long latency M1-M1 and PMd-M1 disinhibition during the preparatory period, irrespective of the direction of the IHi. Importantly, in older adults, the GABA+ levels in bilateral SMC partially accounted for task-related neurophysiological modulations as well as individual differences in RT. In contrast, in young adults, neither task-related neurophysiological modulations, nor individual differences in RT were associated with SMC GABA+ levels. In conclusion, this study contributes to a comprehensive initial understanding of how age-related differences in neurochemical properties and neurophysiological processes are related to increases in RT.

Prefrontal stimulation prior to motor sequence learning alters multivoxel patterns in the striatum and the hippocampus

Motor sequence learning (MSL) is supported by dynamical interactions between hippocampal and striatal networks that are thought to be orchestrated by the prefrontal cortex. In the present study, we tested whether individually-tailored theta-burst stimulation of the dorsolateral prefrontal cortex (DLPFC) prior to MSL can modulate multivoxel response patterns in the stimulated cortical area, the hippocampus and the striatum. Response patterns were assessed with multivoxel correlation structure analyses of functional magnetic resonance imaging data acquired during task practice and during resting-state scans before and after learning/stimulation. Results revealed that, across stimulation conditions, MSL induced greater modulation of task-related DLPFC multivoxel patterns than random practice. A similar learning-related modulatory effect was observed on sensorimotor putamen patterns under inhibitory stimulation. Furthermore, MSL as well as inhibitory stimulation affected (posterior) hippocampal multivoxel patterns at post-intervention rest. Exploratory analyses showed that MSL-related brain patterns in the posterior hippocampus persisted into post-learning rest preferentially after inhibitory stimulation. These results collectively show that prefrontal stimulation can alter multivoxel brain patterns in deep brain regions that are critical for the MSL process. They also suggest that stimulation influenced early offline consolidation processes as evidenced by a stimulation-induced modulation of the reinstatement of task pattern into post-learning wakeful rest.

Altered resting-state functional connectome in major depressive disorder: a mega-analysis from the PsyMRI consortium

Major depressive disorder (MDD) is associated with abnormal neural circuitry. It can be measured by assessing functional connectivity (FC) at resting-state functional MRI, that may help identifying neural markers of MDD and provide further efficient diagnosis and monitor treatment outcomes. The main aim of the present study is to investigate, in an unbiased way, functional alterations in patients with MDD using a large multi-center dataset from the PsyMRI consortium including 1546 participants from 19 centers ( www.psymri.com ). After applying strict exclusion criteria, the final sample consisted of 606 MDD patients (age: 35.8 ± 11.9 y.o.; females: 60.7%) and 476 healthy participants (age: 33.3 ± 11.0 y.o.; females: 56.7%). We found significant relative hypoconnectivity within somatosensory motor (SMN), salience (SN) networks and between SMN, SN, dorsal attention (DAN), and visual (VN) networks in MDD patients. No significant differences were detected within the default mode (DMN) and frontoparietal networks (FPN). In addition, alterations in network organization were observed in terms of significantly lower network segregation of SMN in MDD patients. Although medicated patients showed significantly lower FC within DMN, FPN, and SN than unmedicated patients, there were no differences between medicated and unmedicated groups in terms of network organization in SMN. We conclude that the network organization of cortical networks, involved in processing of sensory information, might be a more stable neuroimaging marker for MDD than previously assumed alterations in higher-order neural networks like DMN and FPN.

Inhibitory Control of Adjacent Finger Movements while Performing a Modified Version of the Halstead Finger Tapping Test: Effects of Age, Education and Sex

OBJECTIVE

Selective motor inhibition is known to decline with age. The purpose of this study was to determine the frequency of failures at inhibitory control of adjacent finger movements while performing a repetitive finger tapping task in young, middle-aged and older adults. Potential education and sex effects were also evaluated.

METHODS

Kinematic recordings of adjacent finger movements were obtained on 107 healthy adults (ages 20-80) while they performed a modified version of the Halstead Finger Tapping Test (HTFF). Study participants were instructed to inhibit all finger movements while tapping with the index finger.

RESULTS

Inability to inhibit adjacent finger movements while performing the task was infrequent in young adults (2.9% of individuals between 20 and 39 years of age) but increased with age (23.3% between the ages of 40 and 59; 31.0% between ages 60 and 80). Females and males did not differ in their inability to inhibit adjacent finger movements, but individuals with a college education showed a lower frequency of failure to inhibit adjacent finger movements (10.3%) compared to those with a high school education (28.6%). These findings were statistically significant only for the dominant hand.

CONCLUSION

Selective motor inhibition failures are most common in the dominant hand and occur primarily in older healthy adults while performing the modified version of the HFTT. Monitoring selective motor inhibition failures may have diagnostic significance.

Alzheimer's Pathology Is Associated with Dedifferentiation of Intrinsic Functional Memory Networks in Aging

In presymptomatic Alzheimer's disease (AD), beta-amyloid plaques (Aβ) and tau tangles accumulate in distinct spatiotemporal patterns within the brain, tracking closely with episodic memory decline. Here, we tested whether age-related changes in the segregation of the brain's intrinsic functional episodic memory networks-anterior-temporal (AT) and posterior-medial (PM) networks-are associated with the accumulation of Aβ, tau, and memory decline using fMRI and PET. We found that AT and PM networks were less segregated in older than that in younger adults and this reduced specialization was associated with more tau and Aβ in the same regions. The effect of network dedifferentiation on memory depended on the amount of Aβ and tau, with low segregation and pathology associated with better performance at baseline and low segregation and high pathology related to worse performance over time. This pattern suggests a compensation phase followed by a degenerative phase in the early, preclinical phase of AD.

Hippocampal and striatal responses during motor learning are modulated by prefrontal cortex stimulation

While it is widely accepted that motor sequence learning (MSL) is supported by a prefrontal-mediated interaction between hippocampal and striatal networks, it remains unknown whether the functional responses of these networks can be modulated in humans with targeted experimental interventions. The present proof-of-concept study employed a multimodal neuroimaging approach, including functional magnetic resonance (MR) imaging and MR spectroscopy, to investigate whether individually-tailored theta-burst stimulation of the dorsolateral prefrontal cortex can modulate responses in the hippocampus and the basal ganglia during motor learning. Our results indicate that while stimulation did not modulate motor performance nor task-related brain activity, it influenced connectivity patterns within hippocampo-frontal and striatal networks. Stimulation also altered the relationship between the levels of gamma-aminobutyric acid (GABA) in the stimulated prefrontal cortex and learning-related changes in both activity and connectivity in fronto-striato-hippocampal networks. This study provides the first experimental evidence, to the best of our knowledge, that brain stimulation can alter motor learning-related functional responses in the striatum and hippocampus.

Integration and Segregation of Dynamic Functional Connectivity States for Mild Cognitive Impairment Revealed by Graph Theory Indicators

Mild cognitive impairment (MCI) is an intermediate stage between normal aging and dementia. Researchers tend to discuss its early state (early MCI, eMCI) due to its high conversion rate of dementia and poor treatment effect in the middle and late stages. Currently, the research on the disease evolution of the brain functional networks of patients with MCI has gradually become a research hotspot. In this study, we compare the differences in dynamic functional connectivity among eMCI, late MCI (lMCI), and normal control (NC) groups, and their graph theory indicators reveal the integration and segregation of functional connectivity states. Firstly, dynamic functional network windows were constructed based on the sliding time window method, and then these window samples were clustered by k-means to extract the functional connectivity states. The differences in the three groups were compared by analyzing the graph theory indicators, such as the participation coefficient, module degree distribution, clustering coefficient, global efficiency, and local efficiency, which distinguish the functional connectivity states. The results reveal that the NC group has the strongest integration and segregation, followed by the eMCI group, and the lMCI group has the weakest integration and segregation. We conclude that with the aggravation of MCI, the integration and segregation of dynamic functional connectivity states tend to decline. The results also reflect that the lMCI group has significantly more brain functional connections in some states, such as IPL.L-MTG.R and DCG.R-SMG.L, than the eMCI group, while the lMCI group has significantly less OLF.L-SPG.L than the NC group.

The organization of functional neurocognitive networks in focal epilepsy correlates with domain-specific cognitive performance

Understanding and diagnosing cognitive impairment in epilepsy remains a prominent challenge. New etiological models suggest that cognitive difficulties might not be directly linked to seizure activity, but are rather a manifestation of a broader brain pathology. Consequently, treating seizures is not sufficient to alleviate cognitive symptoms, highlighting the need for novel diagnostic tools. Here, we investigated whether the organization of three intrinsic, resting-state functional connectivity networks was correlated with domain-specific cognitive test performance. Using individualized EEG source reconstruction and graph theory, we examined the association between network small worldness and cognitive test performance in 23 patients with focal epilepsy and 17 healthy controls, who underwent a series of standardized pencil-and-paper and digital cognitive tests. We observed that the specific networks robustly correlated with test performance in distinct cognitive domains. Specifically, correlations were evident between the default mode network and memory in patients, the central-executive network and executive functioning in controls, and the salience network and social cognition in both groups. Interestingly, the correlations were evident in both groups, but in different domains, suggesting an alteration in these functional neurocognitive networks in focal epilepsy. The present findings highlight the potential clinical relevance of functional brain network dysfunction in cognitive impairment.