Neighborhood Discovery via Network Community Structure

Author(s):  
Aaron Bramson
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.


NeuroImage ◽  
2012 ◽  
Vol 59 (4) ◽  
pp. 3889-3900 ◽  
Author(s):  
Aaron Alexander-Bloch ◽  
Renaud Lambiotte ◽  
Ben Roberts ◽  
Jay Giedd ◽  
Nitin Gogtay ◽  
...  

2016 ◽  
Vol 35 (2) ◽  
pp. 244-261 ◽  
Author(s):  
Frederic Guerrero-Solé

In November 9, 2014, the Catalan government called Catalan people to participate in a straw poll about the independence of Catalonia from Spain. This article analyzes the use of Twitter between November 8 and 10, 2014. Drawing on a methodology developed by Guerrero-Solé, Corominas-Murtra, and Lopez-Gonzalez, this work examines the structure of the retweet overlap network (RON), formed by those users whose communities of retweeters have nonzero overlapping, to detect the community structure of the network. The results show a high polarization of the resulting network and prove that the RON is a reliable method to determinate network community structures and users’ political leaning in political discussions.


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