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, those studies are mainly based on the statistical correlation or bayesian causality inference, lacking of physical and neuroscience level interpretability. Here, we propose a Kuramoto model physical based framework to investigate oxytocin effects on the phase dynamical neural coupling in DMN and FPN. Tested on fMRI data from 59 participants adminstrated 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 DMN and lower synchronization in the FPN, as well as  higher variance of the coupling strength within the DMN and more flexible coupling patterns across time. These results together imply that oxytocin may increase  capability to overcome the dispersion of corresponding intrinsic oscillations and yield flexibility in neural synchrony under various social contexts, providing new evidence to account for 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 in  brain.
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, those studies are mainly based on the statistical correlation or bayesian causality inference, lacking physical and neuroscience level interpretability. Here, we propose a Kuramoto model physical-based framework to investigate oxytocin effects on the phase dynamical neural coupling in DMN and FPN. Tested on fMRI data from 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 DMN and lower synchronization in the FPN, as well as a higher variance of the coupling strength within the DMN and more flexible coupling patterns across time. These results together imply that oxytocin may increase the capability to overcome the dispersion of corresponding intrinsic oscillations and yield flexibility in neural synchrony under various social contexts, providing new evidence to account for 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 in the brain.
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