Hypergraph representation in brain network analysis
P. Anagha,R. Rubesh Selvakumar +1 more
- 05 May 2023
TL;DR: In this article , the authors introduce an inequality that can be used to construct a modular brain network using hypergraph representation, which can measure how many multifunctioning regions each function contains and thereby the correlation of other functions with each function.
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Abstract: For the study of functional aspects of the brain network, hypergraph representation is more powerful than normal graph representation. This paper is a study on the hypergraph representation, based on the functional regions of the brain network. A new parameter that can measure how many multifunctioning regions each function contains and thereby the correlation of other functions with each function. This paper introduces an inequality that can be used to construct a modular brain network using hypergraph representation.
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