Beyond nodes and edges: a bibliometric analysis on graph theory and neuroimaging modalities

Front Neurosci. 2024 Apr 23:18:1373264. doi: 10.3389/fnins.2024.1373264. eCollection 2024.

Abstract

Understanding the intricate architecture of the brain through the lens of graph theory and advanced neuroimaging techniques has become increasingly pivotal in unraveling the complexities of neural networks. This bibliometric analysis explores the evolving landscape of brain research by focusing on the intersection of graph theoretical approaches, neuroanatomy, and diverse neuroimaging modalities. A systematic search strategy was used that resulted in the retrieval of a comprehensive dataset of articles and reviews. Using CiteSpace and VOSviewer, a detailed scientometric analysis was conducted that revealed emerging trends, key research clusters, and influential contributions within this multidisciplinary domain. Our review highlights the growing synergy between graph theory methodologies and neuroimaging modalities, reflecting the evolving paradigms shaping our understanding of brain networks. This study offers comprehensive insight into brain network research, emphasizing growth patterns, pivotal contributions, and global collaborative networks, thus serving as a valuable resource for researchers and institutions navigating this interdisciplinary landscape.

Keywords: bibliometric analysis; brain network; graph theory; neuroimaging; research trends.

Publication types

  • Review

Grants and funding

The author(s) declare that no financial support was received for the research, authorship, and/or publication of this article.