Identifying the human olfactory and chemosignaling neural networks using event related fMRI and graph theory

This study aims to characterize and compare the functional neural networks associated with different olfactory stimuli, including air, non-social odours, and human body odours. We introduce a novel processing pipeline based on event-related functional magnetic resonance imaging (fMRI) and graph theory for network identification. To ensure the stability and small worldness of the characterized networks, we conduct statistical validations, network modularity assessments, and robustness measurement against local attacks. The key hypothesis is that human body odours (so-called social odours) and non-social odours engage distinct neural networks, particularly in regions responsible for social processing. We found that the posterior medial orbitofrontal cortex (pmOFC) and fusiform face area (FFA) demonstrate stronger centrality in the body odour network than the non-social odour and air networks. This observation supports the idea that social and olfactory information are integrated in the body odour network. Additionally, the anterior insula (INSa), posterior piriform cortex (PPC), and amygdala (AMY) exhibit high influence in air and odour networks by achieving higher centrality indices and playing a major role in improving the global efficiency. These findings offer impactful insight into how air, non-social, and social odours recruit distinct neural circuits, reinforcing the role of olfaction in human social behavior.