Synchronization in functional networks of the human brain
Decoding the fundamental mechanisms underlying large-scale brain integration is one of the major challenges of neuroscience. In this article, the authors discuss the concept of brain networks, which can be studied using methods from graph theory. More precisely, a summary of a data-driven computational model of synchronization between distant cortical areas that share a large number of overlapping neighboring (anatomical) connections is presented. The coupled oscillatory systems are represented by the Kuramoto phase oscillators, thus modeling phase synchrony between regional activities. The authors investigate the role that synchrony and its variations play in brain activity based on simulated neural/blood-oxygen-level-dependent time series. The main goal is to reconstruct long-distance functional correlations that emerge from the main anatomical pathways. The studies summarized in this article contribute to a better understanding of the relationship between complex brain networks and temporal dynamics of brain activity. The article also raises other interesting issues that may be the subject of future research by specialists working in this field.
scientific article; zbMATH DE number 7341400
scientific article