scholarly journals Graph Theory Analysis of Functional Brain Networks and Mobility Disability in Older Adults

2014 ◽  
Vol 69 (11) ◽  
pp. 1399-1406 ◽  
Author(s):  
C. E. Hugenschmidt ◽  
J. H. Burdette ◽  
A. R. Morgan ◽  
J. D. Williamson ◽  
S. B. Kritchevsky ◽  
...  
Keyword(s):  
Older Adults ◽  
Graph Theory ◽  
Brain Networks ◽  
Theory Analysis ◽  
Mobility Disability ◽  
Functional Brain ◽  
Functional Brain Networks ◽  
Graph Theory Analysis

scholarly journals Effects of a Motor Imagery Task on Functional Brain Network Community Structure in Older Adults: Data from the Brain Networks and Mobility Function (B-NET) Study

2021 ◽  
Vol 11 (1) ◽  
pp. 118
Author(s):  
Blake R. Neyland ◽  
Christina E. Hugenschmidt ◽  
Robert G. Lyday ◽  
Jonathan H. Burdette ◽  
Laura D. Baker ◽  
...  
Keyword(s):  
Older Adults ◽  
Graph Theory ◽  
Community Structure ◽  
Resting State ◽  
Brain Networks ◽  
Brain Network ◽  
Functional Brain ◽  
Network Community ◽  
Functional Brain Networks ◽  
The Brain

Elucidating the neural correlates of mobility is critical given the increasing population of older adults and age-associated mobility disability. In the current study, we applied graph theory to cross-sectional data to characterize functional brain networks generated from functional magnetic resonance imaging data both at rest and during a motor imagery (MI) task. Our MI task is derived from the Mobility Assessment Tool–short form (MAT-sf), which predicts performance on a 400 m walk, and the Short Physical Performance Battery (SPPB). Participants (n = 157) were from the Brain Networks and Mobility (B-NET) Study (mean age = 76.1 ± 4.3; % female = 55.4; % African American = 8.3; mean years of education = 15.7 ± 2.5). We used community structure analyses to partition functional brain networks into communities, or subnetworks, of highly interconnected regions. Global brain network community structure decreased during the MI task when compared to the resting state. We also examined the community structure of the default mode network (DMN), sensorimotor network (SMN), and the dorsal attention network (DAN) across the study population. The DMN and SMN exhibited a task-driven decline in consistency across the group when comparing the MI task to the resting state. The DAN, however, displayed an increase in consistency during the MI task. To our knowledge, this is the first study to use graph theory and network community structure to characterize the effects of a MI task, such as the MAT-sf, on overall brain network organization in older adults.

scholarly journals Brain Resilience: The Effect of White Matter Disease on Brain Networks in Cognitively Normal Older Adults

2020 ◽  
Vol 4 (Supplement_1) ◽  
pp. 918-918
Author(s):  
Blake Neyland ◽  
Christina Hugenschmidt ◽  
Samuel Lockhart ◽  
Laura Baker ◽  
Suzanne Craft ◽  
...  
Keyword(s):  
Older Adults ◽  
White Matter ◽  
White Matter Hyperintensities ◽  
Brain Networks ◽  
Network Connectivity ◽  
Anterior Cingulate ◽  
Functional Brain ◽  
Mobility Function ◽  
Functional Brain Networks ◽  
Brain Resilience

Abstract Brain pathologies are increasingly understood to confer mobility risk, but the malleability of functional brain networks may be a mechanism for mobility reserve. In particular, white matter hyperintensities (WMH) are strongly associated with mobility and alter functional network connectivity. To assess the potential role of brain networks as a mechanism of mobility reserve, 116 participants with MRI from the Brain Networks and Mobility Function (B-NET) were categorized into 4 groups based on median splits of SPPB scores and WMH burden: Expected Healthy (EH: low WMH, SPPB>10, N=45), Expected Impaired (EI: high WMH, SPPB10, N=24), Unexpected Impaired (EI: low WMH, SPPB<10, N=10) and Unexpected Unhealthy (UH: low WMH, SPPB<10, N=37). Functional brain networks were calculated using graph theory methods and white matter hyperintensities were quantified with the Lesion Segmentation Toolbox (LST) in SPM12. Somatomotor cortex community structure (SMC-CS) was similar between UH and EH with both having higher consistency than EI and UI. However, UH displayed a unique increase in second-order connections between the motor cortex and the anterior cingulate. It is possible that this increase in connections is a signal of higher reserve or resilience in UH participants and may indicate a mechanism of compensation in regards to mobility function and advanced WMH burden. These data suggest functional brain networks may be a mechanism for mobility resilience in older adults at mobility risk due to WMH burden.

Differences in Functional Brain Networks Between Subjective Cognitive Decline with and without Worry Groups: A Graph Theory Study from SILCODE

2021 ◽  
pp. 1-11
Author(s):  
Yi Liu ◽  
Zhuoyuan Li ◽  
Xueyan Jiang ◽  
Wenying Du ◽  
Xiaoqi Wang ◽  
...  
Keyword(s):  
Graph Theory ◽  
Cognitive Decline ◽  
Path Length ◽  
Brain Networks ◽  
Brain Network ◽  
Clustering Coefficient ◽  
Subjective Cognitive Decline ◽  
Functional Brain ◽  
Functional Brain Network ◽  
Functional Brain Networks

Background: Evidence suggests that subjective cognitive decline (SCD) individuals with worry have a higher risk of cognitive decline. However, how SCD-related worry influences the functional brain network is still unknown. Objective: In this study, we aimed to explore the differences in functional brain networks between SCD subjects with and without worry. Methods: A total of 228 participants were enrolled from the Sino Longitudinal Study on Cognitive Decline (SILCODE), including 39 normal control (NC) subjects, 117 SCD subjects with worry, and 72 SCD subjects without worry. All subjects completed neuropsychological assessments, APOE genotyping, and resting-state functional magnetic resonance imaging (rs-fMRI). Graph theory was applied for functional brain network analysis based on both the whole brain and default mode network (DMN). Parameters including the clustering coefficient, shortest path length, local efficiency, and global efficiency were calculated. Two-sample T-tests and chi-square tests were used to analyze differences between two groups. In addition, a false discovery rate-corrected post hoc test was applied. Results: Our analysis showed that compared to the SCD without worry group, SCD with worry group had significantly increased functional connectivity and shortest path length (p = 0.002) and a decreased clustering coefficient (p = 0.013), global efficiency (p = 0.001), and local efficiency (p <  0.001). The above results appeared in both the whole brain and DMN. Conclusion: There were significant differences in functional brain networks between SCD individuals with and without worry. We speculated that worry might result in alterations of the functional brain network for SCD individuals and then result in a higher risk of cognitive decline.

scholarly journals Brain networks in eating disorders: a systematic review of graph theory studies

2021 ◽  
Author(s):  
Enrico Collantoni ◽  
Francesco Alberti ◽  
Valentina Meregalli ◽  
Paolo Meneguzzo ◽  
Elena Tenconi ◽  
...  
Keyword(s):  
Systematic Review ◽  
Eating Disorders ◽  
Graph Theory ◽  
Brain Networks ◽  
Neural Systems ◽  
Theory Analysis ◽  
Level Of Evidence ◽  
Network Properties ◽  
Level I ◽  
Graph Theory Analysis

Abstract Purpose Recent evidence from neuroimaging research has shown that eating disorders (EDs) are characterized by alterations in interconnected neural systems, whose characteristics can be usefully described by connectomics tools. The present paper aimed to review the neuroimaging literature in EDs employing connectomic tools, and, specifically, graph theory analysis. Methods A systematic review of the literature was conducted to identify studies employing graph theory analysis on patients with eating disorders published before the 22nd of June 2020. Results Twelve studies were included in the systematic review. Ten of them address anorexia nervosa (AN) (AN = 199; acute AN = 85, weight recovered AN with acute diagnosis = 24; fully recovered AN = 90). The remaining two articles address patients with bulimia nervosa (BN) (BN = 48). Global and regional unbalance in segregation and integration properties were described in both disorders. Discussion The literature concerning the use of connectomics tools in EDs evidenced the presence of alterations in the topological characteristics of brain networks at a global and at a regional level. Changes in local characteristics involve areas that have been demonstrated to be crucial in the neurobiology and pathophysiology of EDs. Regional imbalances in network properties seem to reflect on global patterns. Level of evidence Level I, systematic review.

scholarly journals The independent influences of age and education on functional brain networks and cognition in healthy older adults

2017 ◽  
Author(s):  
Alistair Perry ◽  
Wei Wen ◽  
Nicole A. Kochan ◽  
Anbupalam Thalamuthu ◽  
Perminder S. Sachdev ◽  
...  
Keyword(s):  
Older Adults ◽  
Functional Connectivity ◽  
Cognitive Processes ◽  
Brain Networks ◽  
Later Life ◽  
Healthy Ageing ◽  
Resting State Functional Connectivity ◽  
Healthy Older Adults ◽  
Functional Brain ◽  
Functional Brain Networks

AbstractHealthy ageing is accompanied by a constellation of changes in cognitive processes and alterations in functional brain networks. The relationships between brain networks and cognition during ageing in later life are moderated by demographic and environmental factors, such as prior education, in a poorly understood manner. Using multivariate analyses, we identify three latent patterns (or modes) linking resting-state functional connectivity to demographic and cognitive measures in 101 cognitively-normal elders. The first mode (p=0.00043) captures an opposing association between age and core cognitive processes such as attention and processing speed on functional connectivity patterns. The functional subnetwork expressed by this mode links bilateral sensorimotor and visual regions through key areas such as the parietal operculum. A strong, independent association between years of education and functional connectivity loads onto a second mode (p=0.012), characterised by the involvement of key hub-regions. A third mode (p=0.041) captures weak, residual brain-behaviour relations. Our findings suggest that circuits supporting lower-level cognitive processes are most sensitive to the influence of age in healthy older adults. Education, and to a lesser extent, executive functions, load independently onto functional networks - suggesting that the moderating effect of education acts upon networks distinct from those vulnerable with ageing. This has important implications in understanding the contribution of education to cognitive reserve during healthy ageing.

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