Reorganization of brain structural networks in aging: A longitudinal study

Coelho, Ana; Fernandes, Henrique M.; Magalhães, Ricardo; Moreira, Pedro Silva; Marques, Paulo; Soares, José Miguel; Amorim, Liliana; Portugal‐Nunes, Carlos; Castanho, Teresa Costa; Santos, Nadine Correia; Sousa, Nuno

doi:10.1002/jnr.24795

Cited by 26 publications

(23 citation statements)

References 141 publications

(194 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…These results corroborate previous findings of age effects in multiple indicators of WM microstructure, including WM integrity (e.g., Sexton et al, 2014), WM fiber density (Choy et al, 2020), and number of streamline counts (Coelho et al, 2021). Together with the present results, these findings indicate robust and replicable effects of age on WM microstructure across measurements and using different biophysical models of water diffusion.…”

Section: Discussionsupporting

confidence: 92%

“…The finding of lower structural connectivity strength in older compared to younger adults also support previous computational work showing that the degree to which structural brain networks rely on geometric wiring rules is weakened with advancing age (Betzel et al, 2016; Zuo et al, 2017). This finding may also indicate less structural constraints on functional brain organization with advancing age, which might lead to disassociation of the topographical organizations between structural and function connectivity in older adults (Coelho et al, 2021; Zamani Esfahlani et al, 2022).…”

Section: Discussionmentioning

confidence: 91%

“…These studies typically include measures of fractional anisotropy (FA) and mean diffusivity (MD) based on tensor model in diffusion tensor imaging (DTI), but also on estimates of WM fiber density (FD) and cross-section (FC) based on constrained spherical deconvolution (CSD) model of WM fiber function. At the network level, a recent longitudinal study demonstrated structural connectome reorganization as indicated by both decreased integration and increased segregation, reflecting more differentiation of structural organization over a mean of 5-years follow-up (Coelho et al, 2021). This pattern is in contrast with age-related dedifferentiation of the brain networks derived from cortical thickness (Chen et al, 2011) and functional connectivity (e.g., Chan et al, 2014; Pedersen et al, 2021), and the underlying reason for structural changes is unknown.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Hub architecture of the human structural connectome: Links to aging and processing speed

Salami

Persson

2023

Preprint

View full text Add to dashboard Cite

The human structural brain network, or connectome, has a rich-club organization with a small number of brain regions showing high network connectivity, called hubs. Hubs are centrally located in the network, biological costly, and might be critical for human cognition. Normal aging is accompanied by cognitive decline, including processing speed, and has been linked to energy depletion in the neurons at a molecular level. However, it is still unclear how age affects hub connections in human connectome. Using a large healthy sample (N=137) with wide age range (25-85 years), we found that the anatomical locations of hubs are relatively age-invariant. However, there were wide-spread age effects on the connectivity strength in the connectome. Critically, these age effects were larger in connections within hubs compared to more peripheral brain regions. These findings were supported by both cross-sectional and longitudinal (N=83) analyses. Moreover, results demonstrated associations between connectivity strength and processing speed, which were more concentrated in hub connections than chance level, and the connectivity strength in hub connections mediated the age-effects on processing speed. Overall, our findings indicate that the hub connections are especially affected by aging, and their vulnerability to the age effects might explain the lower processing speed in older adults.

show abstract

Section: Discussionsupporting

confidence: 92%

Section: Discussionmentioning

confidence: 91%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Hub architecture of the human structural connectome: Links to aging and processing speed

Salami

Persson

2023

Preprint

View full text Add to dashboard Cite

show abstract

“…Distant and local interconnections exist between different brain regions, forming brain networks ( 52 , 53 ). To our knowledge, changes in regional synchronization and functional connectivity patterns in HIV-associated asymptomatic cognitive impairment have not been simultaneously investigated in previous rs-fMRI studies.…”

Section: Discussionmentioning

confidence: 99%

Altered regional homogeneity and functional connectivity of brain activity in young HIV-infected patients with asymptomatic neurocognitive impairment

Han

Aili

et al. 2022

Front. Neurol.

View full text Add to dashboard Cite

ObjectiveAsymptomatic neurocognitive impairment (ANI) is a predominant form of cognitive impairment in young HIV-infected patients. However, the neurophysiological mechanisms underlying this disorder have not been clarified. We aimed to evaluate the altered patterns of functional brain activity in young HIV-infected patients with ANI by quantifying regional homogeneity (ReHo) and region of interest (ROI)-based functional connectivity (FC).MethodsThe experiment involved 44 young HIV-infected patients with ANI and 47 well-matched healthy controls (HCs) undergoing resting-state functional magnetic resonance imaging (rs-fMRI) and neurocognitive tests. Reho alterations were first explored between the ANI group and HC groups. Subsequently, regions showing differences in ReHo were defined as ROIs for FC analysis. Finally, the correlation of ReHo and FC with cognitive function and clinical variables was assessed.ResultsCompared with HCs, ANI patients had a significant ReHo decrease in the right lingual gyrus (LING. R), right superior occipital gyrus (SOG. R), left superior occipital gyrus (SOG. L), left middle occipital gyrus (MOG. L), right middle frontal gyrus (MFG. R), cerebellar vermis, ReHo enhancement in the left middle frontal gyrus (MFG. L), and left insula (INS L). The ANI patients showed increased FC between the LING. R and MOG. L compared to HC. For ANI patients, verbal and language scores were negatively correlated with increased mean ReHo values in the MFG.L. Increased mean ReHo values in the INS. L was positively correlated with disease duration—the mean ReHo values in the LING. R was positively correlated with the abstraction and executive function scores. Increased FC between the LING. R and MOG. L was positively correlated with verbal and language performance.ConclusionThe results suggest that the visual network might be the most vulnerable area of brain function in young HIV-infected patients with ANI. The middle frontal gyrus, cerebellar vermis, and insula also play an important role in asymptomatic neurocognitive impairment. The regional homogeneity and functional connectivity of these regions have compound alterations, which may be related to the course of the disease and neurocognitive function. These neuroimaging findings will help us understand the characteristics of brain network modifications in young HIV-infected patients with ANI.

show abstract

“…The relationship between structural/functional networks and cognitive functions over 2 years (cognitive test ~ node connectivity + time + pseudo + age + sex + education) ventional studies have revealed that reorganization of brain structure (Coelho et al, 2021;Fjell et al, 2017;Hirsiger et al, 2016) and function (Bagarinao et al, 2019;Malagurski et al, 2020;Stumme et al, 2020) in advanced aging provides a compensatory mechanism to enhance, maintain, or reconfigure cognition over time. Hubs, which involve superior connections with the rest of the brain, maintain the optimal information segregation and integration balance that maximizes the communication efficiency by long range connections and minimizes the wiring cost (Bullmore & Sporns, 2009).…”

Section: Ta B L Ementioning

confidence: 99%

Topological reorganization of brain network might contribute to the resilience of cognitive functioning in mildly disabled relapsing remitting multiple sclerosis

Silemek

Nolte

Pöttgen

et al. 2022

J of Neuroscience Research

View full text Add to dashboard Cite

Multiple sclerosis (MS) is an inflammatory and demyelinating disease which leads to impairment in several functional systems including cognition. Alteration of brain networks is linked to disability and its progression. However, results are mostly cross‐sectional and yet contradictory as putative adaptive and maladaptive mechanisms were found. Here, we aimed to explore longitudinal reorganization of brain networks over 2‐years by combining diffusion tensor imaging (DTI), resting‐state functional MRI (fMRI), magnetoencephalography (MEG), and a comprehensive neuropsychological‐battery. In 37 relapsing‐remitting MS (RRMS) and 39 healthy‐controls, cognition remained stable over‐time. We reconstructed network models based on the three modalities and analyzed connectivity in relation to the hierarchical topology and functional subnetworks. Network models were compared across modalities and in their association with cognition using linear‐mixed‐effect‐regression models. Loss of hub connectivity and global reduction was observed on a structural level over‐years (p < .010), which was similar for functional MEG‐networks but not for fMRI‐networks. Structural hub connectivity increased in controls (p = .044), suggesting a physiological mechanism of healthy aging. Despite a general loss in structural connectivity in RRMS, hub connectivity was preserved (p = .002) over‐time in default‐mode‐network (DMN). MEG‐networks were similar to DTI and weakly correlated with fMRI in MS (p < .050). Lower structural (β between .23–.33) and both lower (β between .40–.59) and higher functional connectivity (β = −.54) in DMN was associated with poorer performance in attention and memory in RRMS (p < .001). MEG‐networks involved no association with cognition. Here, cognitive stability despite ongoing neurodegeneration might indicate a resilience mechanism of DMN hubs mimicking a physiological reorganization observed in healthy aging.

show abstract

Reorganization of brain structural networks in aging: A longitudinal study

Abstract: This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

Cited by 26 publications

References 141 publications

Hub architecture of the human structural connectome: Links to aging and processing speed

Hub architecture of the human structural connectome: Links to aging and processing speed

Altered regional homogeneity and functional connectivity of brain activity in young HIV-infected patients with asymptomatic neurocognitive impairment

Topological reorganization of brain network might contribute to the resilience of cognitive functioning in mildly disabled relapsing remitting multiple sclerosis

Contact Info

Product

Resources

About