Efficient network randomization using multiple edge swapping

Mite Mijalkov; Joana B. Pereira

doi:10.1117/12.2569944

20 August 2020 Efficient network randomization using multiple edge swapping

Mite Mijalkov, Joana B. Pereira

Proceedings Volume 11469, Emerging Topics in Artificial Intelligence 2020; 114691T (2020) https://doi.org/10.1117/12.2569944
Event: SPIE Nanoscience + Engineering, 2020, Online Only

Conference Poster

Abstract

The brain connectome can be modeled as a large-scale complex network characterized by high clustering and short network paths. Most studies assess these properties by comparing them to a null network model, generated by randomly rewiring the edges between the nodes of the original network, known as edge swapping. However, this method is computationally expensive and time consuming, mainly in networks with a high number of connections. In this study, we developed an alternative method to create null network models, the allin method. We show that both methods compute null networks with comparable topology, however, the allin method performed the randomization procedure in noticeably less time. The allin method is particularly more effective in the case of high-resolution networks and relatively higher densities. As such, these results suggest that the allin method is a more time efficient alternative to compute null model networks compared to the traditionally used edgeswap method.

Conference Presentation

Citation Download Citation

Mite Mijalkov and Joana B. Pereira "Efficient network randomization using multiple edge swapping", Proc. SPIE 11469, Emerging Topics in Artificial Intelligence 2020, 114691T (20 August 2020); https://doi.org/10.1117/12.2569944

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available