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 ◽  
...  

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.

2017 ◽  
Vol 38 (10) ◽  
pp. 5094-5114 ◽  
Author(s):  
Alistair Perry ◽  
Wei Wen ◽  
Nicole A. Kochan ◽  
Anbupalam Thalamuthu ◽  
Perminder S. Sachdev ◽  
...  

2021 ◽  
Vol 11 (1) ◽  
pp. 118
Author(s):  
Blake R. Neyland ◽  
Christina E. Hugenschmidt ◽  
Robert G. Lyday ◽  
Jonathan H. Burdette ◽  
Laura D. Baker ◽  
...  

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.


2020 ◽  
Vol 4 (Supplement_1) ◽  
pp. 918-918
Author(s):  
Blake Neyland ◽  
Christina Hugenschmidt ◽  
Samuel Lockhart ◽  
Laura Baker ◽  
Suzanne Craft ◽  
...  

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.


2019 ◽  
Author(s):  
Aya Kabbara ◽  
Veronique Paban ◽  
Arnaud Weill ◽  
Julien Modolo ◽  
Mahmoud Hassan

AbstractIntroductionIdentifying the neural substrates underlying the personality traits is a topic of great interest. On the other hand, it is now established that the brain is a dynamic networked system which can be studied using functional connectivity techniques. However, much of the current understanding of personality-related differences in functional connectivity has been obtained through the stationary analysis, which does not capture the complex dynamical properties of brain networks.ObjectiveIn this study, we aimed to evaluate the feasibility of using dynamic network measures to predict personality traits.MethodUsing the EEG/MEG source connectivity method combined with a sliding window approach, dynamic functional brain networks were reconstructed from two datasets: 1) Resting state EEG data acquired from 56 subjects. 2) Resting state MEG data provided from the Human Connectome Project. Then, several dynamic functional connectivity metrics were evaluated.ResultsSimilar observations were obtained by the two modalities (EEG and MEG) according to the neuroticism, which showed a negative correlation with the dynamic variability of resting state brain networks. In particular, a significant relationship between this personality trait and the dynamic variability of the temporal lobe regions was observed. Results also revealed that extraversion and openness are positively correlated with the dynamics of the brain networks.ConclusionThese findings highlight the importance of tracking the dynamics of functional brain networks to improve our understanding about the neural substrates of personality.


2014 ◽  
Vol 69 (11) ◽  
pp. 1399-1406 ◽  
Author(s):  
C. E. Hugenschmidt ◽  
J. H. Burdette ◽  
A. R. Morgan ◽  
J. D. Williamson ◽  
S. B. Kritchevsky ◽  
...  

2019 ◽  
Author(s):  
Tommer Nir ◽  
Yael Jacob ◽  
Kuang-Han Huang ◽  
Arthur E. Schwartz ◽  
Jess W. Brallier ◽  
...  

ABSTRACTThough a growing body of literature is addressing the possible longer-term cognitive effects of anesthetics, to date no study has delineated the normal trajectory of neural recovery due to anesthesia alone in older adults. We obtained resting state functional magnetic resonance imaging scans on 62 healthy human volunteers between ages forty and eighty before, during, and after sevoflurane (general) anesthesia, in the absence of surgery, as part of a larger study on cognitive function post-anesthesia. Resting state networks expression decreased consistently one hour after emergence from anesthesia. This corresponded to a global reduction in anticorrelated functional connectivity post-anesthesia, seen across individual regions-of-interest. Positively correlated functional connectivity remained constant across peri-anesthetic states. All measures returned to baseline 1 day later, with individual regions-of-interest essentially returning to their pre-anesthesia connectivity levels. These results define normal peri-anesthetic changes in resting state connectivity in healthy older adults.


2017 ◽  
Author(s):  
Annika C. Linke ◽  
Conor Wild ◽  
Leire Zubiaurre-Elorza ◽  
Charlotte Herzmann ◽  
Hester Duffy ◽  
...  

AbstractObjectiveFunctional connectivity magnetic resonance imaging (fcMRI) of neonates with perinatal brain injury could improve prediction of motor impairment before symptoms manifest, and establish how early brain organization relates to subsequent development. Methods: This cohort study is the first to describe and quantitatively assess functional brain networks and their relation to later motor skills in neonates with a diverse range of perinatal brain injuries. Infants (n=65, included in final analyses: n=53) were recruited from the neonatal intensive care unit (NICU) and were stratified based on their age at birth (premature vs. term), and on whether neuropathology was diagnosed from structural MRI. Functional brain networks and a measure of disruption to functional connectivity were obtained from 14 minutes of fcMRI acquired during natural sleep at term-equivalent age.ResultsDisruption to connectivity of the somatomotor and frontoparietal executive networks predicted motor impairment at 4 and 8 months. This disruption in functional connectivity was not found to be driven by differences between clinical groups, or by any of the specific measures we captured to describe the clinical course.ConclusionfcMRI was predictive over and above other clinical measures available at discharge from the NICU, including structural MRI. Motor learning was affected by disruption to somatomotor networks, but also frontoparietal executive networks, which supports the functional importance of these networks in early development. Disruption to these two networks might be best addressed by distinct intervention strategies.


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