scholarly journals Deficit in switching between functional brain networks underlies the impact of multitasking on working memory in older adults

2011 ◽  
Vol 108 (17) ◽  
pp. 7212-7217 ◽  
Author(s):  
W. C. Clapp ◽  
M. T. Rubens ◽  
J. Sabharwal ◽  
A. Gazzaley
Keyword(s):  
Older Adults ◽  
Working Memory ◽  
Brain Networks ◽  
Functional Brain ◽  
Functional Brain Networks ◽  
The Impact

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.

scholarly journals Author Correction: Dynamic reconfiguration of functional brain networks during working memory training

2020 ◽  
Vol 11 (1) ◽  
Author(s):  
Karolina Finc ◽  
Kamil Bonna ◽  
Xiaosong He ◽  
David M. Lydon-Staley ◽  
Simone Kühn ◽  
...  
Keyword(s):  
Working Memory ◽  
Brain Networks ◽  
Dynamic Reconfiguration ◽  
Working Memory Training ◽  
Memory Training ◽  
Functional Brain ◽  
Functional Brain Networks

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

Task-merging for finer separation of functional brain networks in working memory

Cortex ◽  
2020 ◽  
Vol 125 ◽  
pp. 246-271 ◽  
Author(s):  
Nicole Sanford ◽  
Jennifer C. Whitman ◽  
Todd S. Woodward
Keyword(s):  
Working Memory ◽  
Brain Networks ◽  
Functional Brain ◽  
Functional Brain Networks

scholarly journals Sparse Graphical Models for Functional Connectivity Networks: Best Methods and the Autocorrelation Issue

2017 ◽  
Author(s):  
Yunan Zhu ◽  
Ivor Cribben
Keyword(s):  
Graphical Models ◽  
Graphical Model ◽  
Brain Networks ◽  
Information Criterion ◽  
Selection Method ◽  
Absolute Deviation ◽  
Data Set ◽  
Functional Brain ◽  
Functional Brain Networks ◽  
The Impact

AbstractSparse graphical models are frequently used to explore both static and dynamic functional brain networks from neuroimaging data. However, the practical performance of the models has not been studied in detail for brain networks. In this work, we have two objectives. First, we compare several sparse graphical model estimation procedures and several selection criteria under various experimental settings, such as different dimensions, sample sizes, types of data, and sparsity levels of the true model structures. We discuss in detail the superiority and deficiency of each combination. Second, in the same simulation study, we show the impact of autocorrelation and whitening on the estimation of functional brain networks. We apply the methods to a resting-state functional magnetic resonance imaging (fMRI) data set. Our results show that the best sparse graphical model, in terms of detection of true connections and having few false-positive connections, is the smoothly clipped absolute deviation (SCAD) estimating method in combination with the Bayesian information criterion (BIC) and cross-validation (CV) selection method. In addition, the presence of autocorrelation in the data adversely affects the estimation of networks but can be helped by using the CV selection method. These results question the validity of a number of fMRI studies where inferior graphical model techniques have been used to estimate brain networks.

scholarly journals Impact of Transcutaneous Auricular Vagus Nerve Stimulation on Large-Scale Functional Brain Networks: From Local to Global

2021 ◽  
Vol 12 ◽  
Author(s):  
Thorsten Rings ◽  
Randi von Wrede ◽  
Timo Bröhl ◽  
Sophia Schach ◽  
Christoph Helmstaedter ◽  
...  
Keyword(s):  
Vagus Nerve ◽  
Nerve Stimulation ◽  
Mode Of Action ◽  
Vagus Nerve Stimulation ◽  
Large Scale ◽  
Brain Networks ◽  
Short Term ◽  
Functional Brain ◽  
Functional Brain Networks ◽  
The Impact

Transcutaneous auricular vagus nerve stimulation (taVNS) is a novel non-invasive brain stimulation technique considered as a potential supplementary treatment option for a wide range of diseases. Although first promising findings were obtained so far, the exact mode of action of taVNS is not fully understood yet. We recently developed an examination schedule to probe for immediate taVNS-induced modifications of large-scale epileptic brain networks. With this schedule, we observed short-term taVNS to have a topology-modifying, robustness- and stability-enhancing immediate effect on large-scale functional brain networks from subjects with focal epilepsies. We here expand on this study and investigate the impact of short-term taVNS on various local and global characteristics of large-scale evolving functional brain networks from a group of 30 subjects with and without central nervous system diseases. Our findings point to differential, at first glance counterintuitive, taVNS-mediated alterations of local and global topological network characteristics that result in a reconfiguration of networks and a modification of their stability and robustness properties. We propose a model of a stimulation-related stretching and compression of evolving functional brain networks that may help to better understand the mode of action of taVNS.

Sign in / Sign up

Export Citation Format

Share Document