Application of EEG Time-Varying Networks in the Evaluation of Dynamic Functional Brain Networks

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.

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Interactions Between Large-Scale Functional Brain Networks are Captured by Sparse Coupled HMMs

IEEE Transactions on Medical Imaging ◽

10.1109/tmi.2017.2755369 ◽

2018 ◽

Vol 37 (1) ◽

pp. 230-240 ◽

Cited By ~ 19

Author(s):

Thomas A. W. Bolton ◽

Anjali Tarun ◽

Virginie Sterpenich ◽

Sophie Schwartz ◽

Dimitri Van De Ville

Keyword(s):

Large Scale ◽

Brain Networks ◽

Functional Brain ◽

Functional Brain Networks

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Altered regional activity and connectivity of functional brain networks in congenital unilateral conductive hearing loss

NeuroImage Clinical ◽

10.1016/j.nicl.2021.102819 ◽

2021 ◽

pp. 102819

Author(s):

Tengyu Yang ◽

Qiang Liu ◽

Xinmiao Fan ◽

Bo Hou ◽

Jian Wang ◽

...

Keyword(s):

Hearing Loss ◽

Conductive Hearing Loss ◽

Brain Networks ◽

Functional Brain ◽

Regional Activity ◽

Functional Brain Networks ◽

Conductive Hearing

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

Innovation in Aging ◽

10.1093/geroni/igaa057.3372 ◽

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.

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