The connectivity patterns among the DMN nodes when the brain is resting are still in great debate. Among the unknowns is whether a dominant node exists in the network and if any, how does it influences the other nodes. Resting state functional magnetic resonance imaging (rsfMRI) was utilized in data acquisition on 25 healthy male and female participants. The DMN nodes selected were posterior cingulate cortex (PCC), bilateral inferior parietal cortex (IPL) and medial prefrontal cortex (mPFC). Fully connected causal models were constructed comprising four DMN nodes. The time invariant covariance of the random fluctuations between nodes was then estimated to obtain the effective connectivity (EC) between the DMN nodes. The EC values among the DMN nodes were averaged over the participants using Bayesian Parameter Averaging (BPA). All the DMN nodes have self-inhibitory dynamics. All connections between nodes were significant (P > 0.9) with a condition for any of the two nodes, one node inhibited the others. The PCC which exhibited the highest signal intensity was in fact inhibited by others. Inter-hemispheric RIPC to LIPC connections acted the same way, with excitatory LIPC to RIPC and inhibitory RIPC to LIPC connections. The results also showed a stronger mPFC to RIPC connection in the right hemisphere (as compared to mPFC to LIPC connection in the left hemisphere) and a weaker PCC to RIPC connection in the right hemisphere (as compared to PCC to LIPC connection in the left hemisphere). PCC can be regarded as a dominant node among the four nodes, being connected to all other nodes in different ways. All the four nodes were significantly activated and connected to each other even though the brain was in a state of resting.