First Results on Graph Similarity Search in Resting-State Functional Connectivity Networks Using Spectral and Graph Edit Distances

M. A. G. Carvalho, M. A. G. Carvalho, M. A. G. Carvalho, R. Frayne, R. Frayne, R. Frayne, R. Frayne

2025

Abstract

The application of graph theory in the modeling and analysis of brain networks has generated both new opportunities as well as new challenges in neuroscience. Resting state functional connectivity (RSFC) networks studied with graphs is an important field of investigation because of the potential benefits in understanding function in healthy individuals and identifying evidence of brain diseases and injury in patients. This work is unique because it applies information retrieval techniques to create ranked lists from RSFC graph theory-derived networks. In our analysis, we used a sample of whole-brain resting-state functional magnetic resonance imaging (rs-fMRI) data obtained from Young (n = 10, age: 20.1 ± 2.1) and Old (n = 10, 65.6 ± 0.4) sex-balanced groups drawn from a healthy, i.e., neurotypical, cohort. We estimated two well-known distance metrics (graph edit distance and graph spectral distance) and by using information-retrieval graph ranking methods achieved precision measures at the top-5 positions of ranked lists of up to 80%.

Paper Citation

in Harvard Style

Carvalho M. and Frayne R. (2025). First Results on Graph Similarity Search in Resting-State Functional Connectivity Networks Using Spectral and Graph Edit Distances. In Proceedings of the 18th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 1: BIOIMAGING; ISBN 978-989-758-731-3, SciTePress, pages 357-362. DOI: 10.5220/0013261400003911

in Bibtex Style

@conference{bioimaging25,
author={M. Carvalho and R. Frayne},
title={First Results on Graph Similarity Search in Resting-State Functional Connectivity Networks Using Spectral and Graph Edit Distances},
booktitle={Proceedings of the 18th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 1: BIOIMAGING},
year={2025},
pages={357-362},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013261400003911},
isbn={978-989-758-731-3},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 18th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 1: BIOIMAGING
TI - First Results on Graph Similarity Search in Resting-State Functional Connectivity Networks Using Spectral and Graph Edit Distances
SN - 978-989-758-731-3
AU - Carvalho M.
AU - Frayne R.
PY - 2025
SP - 357
EP - 362
DO - 10.5220/0013261400003911
PB - SciTePress