  The oxytocin effects on large-scale brain networks such as Default Mode
Network (DMN) and Frontoparietal Network (FPN) have been largely studied using
fMRI data. However, these studies are mainly based on the statistical
correlation or Bayesian causality inference, lacking interpretability at
physical and neuroscience level. Here, we propose a physics-based framework of
Kuramoto model to investigate oxytocin effects on the phase dynamic neural
coupling in DMN and FPN. Testing on fMRI data of 59 participants administrated
with either oxytocin or placebo, we demonstrate that oxytocin changes the
topology of brain communities in DMN and FPN, leading to higher synchronization
in the FPN and lower synchronization in the DMN, as well as a higher variance
of the coupling strength within the DMN and more flexible coupling patterns
across time. These results together indicate that oxytocin may increase the
ability to overcome the corresponding internal oscillation dispersion and
support the flexibility in neural synchrony in various social contexts,
providing new evidence for explaining the oxytocin modulated social behaviors.
Our proposed Kuramoto model-based framework can be a potential tool in network
neuroscience and offers physical and neural insights into phase dynamics of the
brain.

Neurons and Cognition;Quantitative Methods